Pinterest Stock price
📊 Peer Group
📈 What is it?
The peer group consists of the companies with the most similar business model. They serve as a benchmark for putting a stock into context.
🧮 How is it selected?
Based on similarity of business model, meaning companies from the same industry with comparable products and a similar customer base. That's the only way to compare apples to apples.
🏛️ Why does it matter?
Whether a stock is cheap or expensive is best judged by comparison. A P/E of 18 or an EV/FCF of 20 can look cheap or expensive depending on the yardstick. The peer group gives you the most accurate one: companies with a similar business model that operate under the same conditions.
🎯 What does it mean for investors?
When a metric sits below the peer average, the stock is valued more cheaply relative to its competitors, and above the average more expensively. A discount to the peer group can be an opportunity, but it can also have a reason (for example lower growth). The comparison is a starting point, not a verdict.
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Invest better with AI
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Key metrics
📘 Market Capitalization
📈 What is it?
Market capitalization shows how much a company is currently worth on the stock market.
🧮 How is it calculated?
🏛️ Why is it important?
It helps classify companies by size (Large, Mid, Small Cap) and indicates their market presence and relative stability.
🧮 Calculation
🎯 What does this mean for investors?
- Large-cap companies tend to be more stable, often pay dividends, but may grow more slowly.
- Smaller firms may offer higher growth potential but come with more volatility.
- Market capitalization is a useful indicator of company size — but not a measure of whether a stock is undervalued or overvalued.
📘 Enterprise Value (EV)
📈 What is it?
Enterprise Value represents the total cost to acquire a company — including its debt and excluding its cash reserves.
🧮 How is it calculated?
(= Market Cap + Net Debt)
🏛️ Why is it important?
EV gives a more complete picture of a company's value than market cap alone and is used in key valuation ratios like EV/FCF or EV/Sales.
🧮 Calculation
🎯 What does this mean for investors?
- Enterprise Value shows the true cost of buying a company, including all financial obligations.
- It is more accurate than just looking at market cap, especially when comparing companies with different levels of debt or cash.
- Professional investors prefer EV-based multiples because they better reflect the company’s full financial footprint.
📘 Net Debt
📈 What is it?
Net Debt shows how much debt remains after subtracting a company’s available cash reserves.
🧮 How is it calculated?
🏛️ Why is it important?
It indicates how dependent a company is on borrowed money and how easily it can service its debt in the short term.
🧮 Calculation
🎯 What does this mean for investors?
- Low or negative net debt signals financial strength and flexibility.
- Companies with strong cash positions are better positioned in crises.
- High net debt increases financial risk — especially in environments with rising interest rates or economic downturns.
📘 Cash
📈 What is it?
Cash represents all liquid assets a company can access immediately — including cash, bank deposits, and short-term investments.
🧮 How is it calculated?
🏛️ Why is it important?
It reflects a company’s financial flexibility and resilience — enabling investments, buybacks, or buffer in downturns.
🧮 Calculation
🎯 What does this mean for investors?
- A strong cash position means greater room for maneuver and crisis resistance.
- Cash-rich companies can invest, pay down debt, or repurchase shares.
- But excess idle cash might indicate a lack of growth opportunities.
📘 Shares Outstanding
📈 What is it?
Shares outstanding represent the total number of a company’s shares currently held by investors — excluding treasury stock.
🧮 How is it calculated?
🏛️ Why is it important?
It’s the basis for key metrics like Earnings Per Share (EPS), Market Capitalization, or the Price/Earnings ratio (P/E).
🧮 Calculation
🎯 What does this mean for investors?
- Fewer shares in circulation typically increase earnings per share — making each share more valuable.
- Share buybacks reduce the number of shares and boost per-share metrics.
- Issuing new shares does the opposite — diluting shareholder value and lowering per-share figures.
📘 Price-to-Earnings Ratio (P/E)
📈 What is it?
The P/E ratio shows how many times a company's earnings per share are reflected in its current share price — in other words, how "expensive" the stock appears relative to its profits.
🧮 How is it calculated?
🏛️ Why is it important?
The P/E ratio is one of the most widely used valuation metrics. It helps investors assess whether a stock appears cheap or expensive compared to its earnings power.
🧮 Calculation
📊 P/E (TTM) = Based on earnings from the last 12 months (Trailing Twelve Months):🎯 What does this mean for investors?
- A low P/E may indicate undervaluation — or signal underlying issues.
- A high P/E may reflect strong growth expectations — or an overvalued stock.
📘 Price-to-Sales Ratio (P/S)
📈 What is it?
The P/S ratio shows how much investors are paying for $1 of the company’s revenue – regardless of profitability.
🧮 How is it calculated?
🏛️ Why is it important?
P/S is especially useful for evaluating growth companies or businesses not yet profitable. It reflects how the market values the company’s sales.
🧮 Calculation
Market Cap = $10.56b | Revenue (TTM) = $4.56b
Market Cap = $10.56b | Estimated Revenue = $5.01b
🎯 What does this mean for investors?
- A low P/S may indicate undervaluation — or low profitability.
- A high P/S can reflect strong growth expectations — or excessive optimism.
- Especially helpful when evaluating companies where profits are low, volatile, or negative.
📘 Enterprise Value to Sales (EV/Sales)
📈 What is it?
EV/Sales shows how much investors are paying for $1 of revenue — considering not just equity, but also debt and cash. It’s the capital structure–adjusted version of the P/S ratio.
🧮 How is it calculated?
🏛️ Why is it important?
It’s ideal for comparing companies with different levels of debt. It reflects a company's true cost relative to its revenue.
🧮 Calculation
Enterprise Value = $10.27b | Revenue (TTM) = $4.56b
Enterprise Value = $10.27b | Forward Revenue = $5.01b
🎯 What does this mean for investors?
- EV/Sales allows for capital structure–neutral company comparisons.
- A lower ratio may indicate undervaluation; a higher one may signal strong growth expectations or overvaluation.
- Especially helpful when evaluating high-growth companies with low or negative earnings.
📘 Enterprise Value to Free Cash Flow (EV/FCF)
📈 What is it?
EV/FCF shows how many years it would take for a company to "pay back" its enterprise value using its free cash flow.
🧮 How is it calculated?
🏛️ Why is it important?
It focuses on real cash generation, ignoring accounting noise — ideal for assessing profitability and value based on liquidity, not earnings.
🧮 Calculation
🎯 What does this mean for investors?
- A low EV/FCF may signal undervaluation and strong cash generation.
- A high EV/FCF might reflect weak recent cash flow or aggressive growth expectations.
- Best suited for stable, mature businesses with predictable free cash flows.
📘 Price-to-Book Ratio (P/B)
📈 What is it?
The P/B ratio compares a company’s market value to its book value — showing how much investors are paying for each dollar of net assets.
🧮 How is it calculated?
🏛️ Why is it important?
P/B is commonly used for asset-heavy industries like banks or industrials. It helps assess whether a stock is trading above or below its net asset value.
🧮 Calculation
🎯 What does this mean for investors?
- A P/B below 1 may signal undervaluation — or weak profitability.
- A P/B above 1 implies the market expects future value creation (e.g., brand, IP, growth).
- Best used for companies with tangible assets and strong balance sheets.
📘 Equity Ratio
📈 What is it?
The equity ratio indicates what portion of a company’s total assets is financed by shareholders’ equity – in other words, how much it relies on its own capital.
🧮 How is it calculated?
🏛️ Why is it important?
A high equity ratio reflects financial strength and stability, especially during downturns. It’s a key indicator of a company’s solvency and long-term risk profile.
🧮 Calculation
🎯 What does this mean for investors?
- Companies with high equity ratios are generally more resilient and less dependent on external debt.
- Low equity ratios can signal higher risk or aggressive financial strategies.
- Important: Always assess the equity ratio in combination with the return on equity (ROE). This shows not just how stable the company is – but also how efficiently it uses shareholder capital.
📘 Return on Equity (ROE)
📈 What is it?
Return on equity (ROE) shows how efficiently a company uses its shareholders’ equity to generate profit. In other words: how much net income is earned per dollar of equity.
🧮 How is it calculated?
🏛️ Why is it important?
ROE is a core profitability metric. It helps investors understand whether a company delivers attractive returns on the capital provided by its shareholders.
🧮 Calculation
🎯 What does this mean for investors?
- A high ROE indicates that the company is using its capital efficiently and profitably.
- It’s especially meaningful for capital-intensive businesses or firms with high equity bases.
- Important: A very high ROE can also result from high debt levels – always interpret it alongside the equity ratio to assess financial health.
📘 Return on Capital Employed (ROCE)
📈 What is it?
ROCE measures how efficiently a company generates profits from its total capital – including both equity and interest-bearing debt.
🧮 How is it calculated?
It evaluates the return on all capital employed, regardless of how it’s financed.
🏛️ Why is it important?
ROCE is ideal for comparing companies with different financing structures. It shows how well management uses capital to create value for both shareholders and creditors.
🧮 Calculation
🎯 What does this mean for investors?
- A high ROCE means the company uses its capital efficiently – regardless of whether it's funded by debt or equity.
- The higher the ROCE compared to peers, the more value the company creates with its invested capital.
- Especially relevant for capital-intensive sectors like industrials, energy, or infrastructure.
📘 Return on Invested Capital (ROIC)
📈 What is it?
ROIC measures how efficiently a company generates returns from the capital invested in its core operations – regardless of whether the capital comes from equity or debt.
🧮 How is it calculated?
- NOPAT = Net Operating Profit After Taxes
- Invested Capital = Operating assets minus non-interest-bearing liabilities
🏛️ Why is it important?
ROIC is one of the most accurate indicators of capital efficiency. Unlike return on equity, it is not distorted by leverage and shows how much value is created for all capital providers.
🎯 What does this mean for investors?
- A high ROIC shows how effectively a company uses the capital that is truly invested in its core operations.
- Unlike ROCE, ROIC focuses only on the capital that is actively used to run the business – and that requires a return (i.e. interest-bearing).
- Especially useful when comparing companies with large amounts of excess cash or non-interest-bearing liabilities – giving a more realistic picture of capital efficiency.
📘 Leverage Ratio (Debt-to-Equity)
📈 What is it?
The leverage ratio indicates how much a company relies on interest-bearing debt (such as loans and bonds) relative to its shareholders’ equity.
🧮 How is it calculated?
🏛️ Why is it important?
This ratio helps assess a company’s financial structure and risk profile. High leverage can enhance returns – but also increases exposure to interest rate changes and financial stress.
🧮 Calculation
🎯 What does this mean for investors?
- A low leverage ratio signals financial strength and independence.
- A higher ratio can improve returns in good times but increases risk during downturns or rising interest rate periods.
- 👉 Always interpret in the context of industry, capital intensity, and interest rate environment.
📘 Revenue
📈 What is it?
Revenue shows how much a company earns in total from selling its products and services – the gross income before any costs are deducted.
🧮 How is it calculated?
🏛️ Why is it important?
Revenue is one of the key figures to assess a company’s size, market position, and growth potential.
🧮 Calculation
🎯 What does this mean for investors?
- Growing revenue indicates rising demand and can be an early signal of future earnings growth.
- Comparing actual and expected revenue reveals trends in the market environment and analyst sentiment.
- Note: Strong revenue alone isn’t enough – margins and profitability matter just as much.
📘 EBITDA
📈 What is it?
EBITDA stands for “Earnings Before Interest, Taxes, Depreciation, and Amortization.” It reflects a company’s operating profit before the effects of financing, taxes, and accounting depreciation.
🧮 How is it calculated?
🏛️ Why is it important?
EBITDA is widely used to evaluate a company’s operating performance – especially across capital-intensive sectors or international comparisons.
🧮 Calculation
🎯 What does this mean for investors?
- A high or growing EBITDA indicates strong operational profitability – independent of taxes, interest, or accounting methods.
- It’s especially useful for comparing companies across sectors or geographies.
- Important: EBITDA is not a net income figure – it excludes key costs like depreciation and interest.
📘 EBIT
📈 What is it?
EBIT stands for “Earnings Before Interest and Taxes.” It reflects a company’s operating profit after depreciation, but before interest and tax expenses.
🧮 How is it calculated?
🏛️ Why is it important?
EBIT is a core profitability metric that shows how well the company performs in its main business operations – independent of capital structure and tax environment.
🧮 Calculation
🎯 What does this mean for investors?
- A high EBIT indicates strong profitability from the company’s core business – before financial and tax effects.
- It allows better comparison between companies with different debt levels or tax structures.
- Compared to EBITDA, EBIT already accounts for depreciation and reflects capital intensity more clearly.
📘 Net Income
📈 What is it?
Net income is the company’s total profit – the amount left after all expenses, taxes, interest, and depreciation have been deducted.
🧮 How is it calculated?
🏛️ Why is it important?
Net income is the most comprehensive measure of a company’s profitability – showing how much actual profit remains after all business and financing costs.
🧮 Calculation
🎯 What does this mean for investors?
- Growing net income indicates that the company is managing all of its costs efficiently.
- It directly influences valuation metrics like P/E ratio and the company’s dividend capacity.
- Over time, net income trends reveal how resilient and profitable the business model really is.
📘 Free Cash Flow (FCF)
📈 What is it?
Free Cash Flow shows how much actual cash remains after a company covers its operating expenses and capital expenditures.
🧮 How is it calculated?
🏛️ Why is it important?
FCF reflects a company’s real financial strength – regardless of accounting profits. It shows how much flexibility a company has for dividends, share buybacks, or debt reduction.
🧮 Calculation
🎯 What does this mean for investors?
- High free cash flow means the company generates real, usable cash – independent of reported net income.
- It’s often the most reliable base for sustainable dividends and buybacks.
- Declining FCF can be an early warning sign – even when profits appear stable.
📘 Revenue Growth
📈 What is it?
Revenue growth shows how much a company’s sales have changed compared to the previous year – both on a trailing basis (TTM) and based on forward projections.
🧮 How is it calculated?
Forward = (Expected revenue ÷ Revenue in prior year − 1) × 100
Forward growth is based on analyst estimates for the current fiscal year.
🏛️ Why is it important?
Rising revenue signals growing demand, business expansion, and market share gains – especially important for growth-oriented companies.
🧮 Calculation
🎯 What does this mean for investors?
- Growth is the engine of long-term value creation – especially in tech and growth sectors.
- What matters is not just current growth, but its sustainability.
- Forward projections reflect whether analysts expect continued momentum – or a slowdown.
📘 EBITDA Growth
📈 What is it?
EBITDA growth shows how much a company’s operating profit (before interest, taxes, depreciation, and amortization) has increased or decreased compared to the previous year.
🧮 How is it calculated?
Forward = (Expected EBITDA ÷ EBITDA from prior year − 1) × 100
The forward estimate is based on analyst projections for the current fiscal year.
🏛️ Why is it important?
Growing EBITDA indicates improving operational profitability – regardless of financing or accounting effects.
🧮 Calculation
🎯 What does this mean for investors?
- Strong EBITDA growth signals operational efficiency and scalability – especially during growth phases.
- EBITDA growth can be an early indicator of margin and earnings expansion – but should be assessed alongside revenue and EBIT.
📘 EBIT Growth
📈 What is it?
EBIT growth shows how much a company’s operating profit (after depreciation, but before interest and taxes) has increased compared to the previous year.
🧮 How is it calculated?
Forward = (Expected EBIT ÷ EBIT from prior year − 1) × 100
The forward estimate is based on analyst projections for the current fiscal year.
🏛️ Why is it important?
EBIT growth is a direct indicator of a company’s business performance – taking into account capital intensity through depreciation.
🧮 Calculation
🎯 What does this mean for investors?
- Rising EBIT signals improving operating profitability – even after accounting for depreciation.
- It’s especially important for evaluating companies with significant capital expenditures.
- Combined with revenue and EBITDA growth, EBIT growth provides a well-rounded view of operational progress.
📘 Net Income Growth
📈 What is it?
Net income growth shows how much a company’s bottom-line profit has increased or decreased compared to the previous year – both on a trailing basis (TTM) and based on analyst projections.
🧮 How is it calculated?
Forward = (Expected net income ÷ Net income from prior year − 1) × 100
The forward estimate reflects analysts’ expectations for the current fiscal year.
🏛️ Why is it important?
Net income is the ultimate measure of profitability. Growing net income signals stronger efficiency, cost control, and sustainable earnings power.
🧮 Calculation
🎯 What does this mean for investors?
- Stronger net income boosts valuation, dividend potential, and investor confidence.
- If profits stall while revenue grows, it may signal margin pressure.
📘 Free Cash Flow Growth
📈 What is it?
Free cash flow (FCF) growth shows how a company’s available cash – after covering operating expenses and capital expenditures – has changed compared to the previous year.
🧮 How is it calculated?
🏛️ Why is it important?
Free cash flow reflects real financial strength. Growing FCF indicates more flexibility for dividends, share buybacks, and reinvestment.
🧮 Calculation
🎯 What does this mean for investors?
- Declining FCF may point to rising investments, increasing costs, or weaker operating performance.
- Especially for dividend investors, FCF growth is critical – since dividends are paid from actual available cash.
- A negative trend isn't always bad, but it deserves closer attention.
📘 Gross Margin
📈 What is it?
Gross margin shows how much of a company’s revenue remains after deducting the direct costs of goods sold (like materials and production). It represents the company’s “raw profit” before fixed costs, taxes, and interest.
🧮 How is it calculated?
Or simply: Gross Margin = Gross Profit ÷ Revenue × 100
🏛️ Why is it important?
Gross margin indicates how efficiently a company can produce or procure what it sells. It is a key measure of product-level profitability and pricing power.
🧮 Calculation
🎯 What does this mean for investors?
- A high gross margin suggests strong pricing power and efficient production.
- Falling margins may signal rising input costs or competitive pressure.
- Compared to peers, gross margin offers insights into the quality of a business model.
📘 EBITDA Margin
📈 What is it?
The EBITDA margin shows how much of a company’s revenue remains as operating profit before interest, taxes, depreciation, and amortization.It reflects operating efficiency without being distorted by financing or accounting factors.
🧮 How is it calculated?
🏛️ Why is it important?
The EBITDA margin reveals how much operating income a company generates per dollar of revenue – independent of capital structure and tax effects.
🧮 Calculation
🎯 What does this mean for investors?
- A high EBITDA margin reflects strong core profitability – before accounting distortions.
- It allows for effective comparisons across companies and sectors.
- A stable or growing margin signals efficient cost control and business scalability.
📘 EBIT Margin
📈 What is it?
The EBIT margin shows what percentage of revenue remains as operating profit after depreciation but before interest and taxes.
🧮 How is it calculated?
🏛️ Why is it important?
The EBIT margin reflects a company’s core profitability while accounting for capital intensity (e.g. machinery, infrastructure). It’s especially useful for comparing businesses with different levels of depreciation.
🧮 Calculation
🎯 What does this mean for investors?
- A high EBIT margin shows that the company remains efficient even after factoring in depreciation.
- It’s especially relevant for capital-intensive industries.
- Stable or rising EBIT margins over time are a strong indicator of pricing power and business quality.
📘 Net margin
📈 What is it?
Net margin shows how much of a company’s revenue remains as bottom-line profit after deducting all costs, interest, taxes, and depreciation.
🧮 How is it calculated?
🏛️ Why is it important?
Net margin reflects a company’s overall efficiency – across operations, financing, and taxation. It shows how much actual profit is generated from each dollar of revenue.
🧮 Calculation
🎯 What does this mean for investors?
- A high net margin means the company is not only strong operationally but also manages financing and taxes efficiently.
- Peer comparisons reveal business quality and competitiveness.
- Declining margins despite revenue growth can be a red flag for rising costs or inefficiencies.
📘 Free cash flow margin
📈 What is it?
The free cash flow (FCF) margin shows how much of a company’s revenue remains as actual free cash after covering all operating expenses and capital expenditures.
🧮 How is it calculated?
🏛️ Why is it important?
This margin reflects the true liquidity generated by the business – independent of accounting rules or depreciation. It’s especially relevant for dividends, buybacks, and reinvestment decisions.
🧮 Calculation
🎯 What does this mean for investors?
- A high FCF margin means a company consistently generates strong cash flow.
- It’s a positive signal for financial stability and shareholder returns.
- The long-term trend is key – a declining margin may indicate rising investments or weakening operating efficiency.
📘 Earnings per share (EPS)
📈 What is it?
Earnings per Share (EPS) shows how much profit is attributable to a single share – and is one of the most important metrics for evaluating a company's performance.
🧮 How is it calculated?
The diluted share count reflects potential new shares that could be issued through options, convertible bonds, or other rights.
🏛️ Why is it important?
EPS is the basis for many key valuation metrics like P/E ratio, PEG ratio, or payout ratio. It enables comparisons of profitability across companies, regardless of their size.
🧮 Calculation
🎯 What does this mean for investors?
- EPS captures per-share profitability and is especially useful for comparisons over time or with analyst estimates.
- Rising EPS may signal consistent growth or share buybacks.
- Important: Always use diluted EPS for more realistic valuations – especially in companies with stock-based compensation.
📘 Free cash flow per share (FCF per share)
📈 What is it?
Free Cash Flow per Share shows how much free cash flow a company generates per outstanding share – after investments, but before dividends or debt repayments.
🧮 How is it calculated?
Free cash flow is calculated as operating cash flow minus capital expenditures (CapEx).
🏛️ Why is it important?
FCF per Share reveals how much real cash is available per share – useful for dividends, buybacks, or reducing debt. Unlike net income, free cash flow is harder to manipulate and often seen as a more reliable metric.
🧮 Calculation
🎯 What does this mean for investors?
- High FCF per share signals strong financial flexibility.
- It shows how much capital the company can effectively reinvest or return to shareholders.
- Particularly relevant for dividend payers and capital-efficient businesses.
📘 Short interest
📈 What is it?
Short interest indicates how many shares of a company are currently sold short – that is, borrowed and sold by investors who expect the price to decline.
🧮 How is it calculated?
It reflects the percentage of a company’s shares that are being shorted relative to the total shares available.
🏛️ Why is it important?
Short interest serves as a sentiment indicator: A high value may signal skepticism or bearish expectations – but also increases the potential for a short squeeze if prices rise unexpectedly.
🧮 Calculation
🎯 What does this mean for investors?
- Low short interest usually indicates market confidence in the company.
- High short interest can be a warning sign – or an opportunity if sentiment shifts.
- Especially relevant in volatile markets or ahead of key earnings releases.
📘 Employees
📈 What is it?
The employee count shows how many people a company employs worldwide – offering insights into its size, structure, and business model.
🧮 How is it calculated?
🏛️ Why is it important?
It helps assess operational scale, labor intensity, and cost structure. Combined with revenue and profit, it enables key metrics like revenue per employee or productivity.
🧮 Calculation
🎯 What does this mean for investors?
- A high headcount can signal operational complexity – but also significant growth capacity.
- Revenue per employee is a key indicator of efficiency.
- Especially useful for comparing tech, industrial, or service-heavy companies.
📘 Turnover per employee
📈 What is it?
Revenue per employee indicates how much revenue a company generates on average per employee – a key measure of efficiency and productivity.
🧮 How is it calculated?
The employee count is typically taken from the most recent annual report.
🏛️ Why is it important?
This metric helps compare business models – especially between labor-intensive and technology-driven companies. A high value suggests automation, operational efficiency, or strong value creation per head.
🧮 Calculation
🎯 What does this mean for investors?
- A high revenue per employee indicates a scalable and margin-strong business model.
- A low figure may reflect labor-intensive operations or lower value-add.
- Especially helpful when comparing tech companies to industrial or service sectors.
Pinterest Stock Analysis
Analyst Opinions
45 Analysts have issued a Pinterest forecast:
Analyst Opinions
45 Analysts have issued a Pinterest forecast:
Pinterest Events
Past Events
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SEP
9
Goldman Sachs Communacopia + Technology Conference 2026
8 days ago
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AUG
4
Q2 2026 Earnings Call
about one month ago
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MAY
4
Q1 2026 Earnings Call
5 months ago
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FEB
12
Q4 2025 Earnings Call
7 months ago
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NOV
4
Q3 2025 Earnings Call
11 months ago
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SEP
9
Goldman Sachs Communacopia + Technology Conference 2025
about one year ago
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StocksGuide Free
Pinterest — Goldman Sachs Communacopia + Technology Conference 2026
1. Question Answer
Interest of time and for the webcast, we're going to get going. It's my privilege to kick off our first fireside chat of day 2 with Bill Ready, the CEO of Pinterest. I'm going to read a quick safe harbor, and then we're going to get into this. Some of the statements that Pinterest will make today may be considered forward-looking. These statements involve a number of risks and uncertainties that could cause actual results to differ materially.
Any forward-looking statements that Pinterest makes are based on assumptions as of today, and Pinterest undertakes no obligation to update them. Please refer to Pinterest's latest Form 10-Q and Form 10-K for a discussion of the risk factors that may affect its results. Okay. Bill, thanks so much for being part of the conference this year.
Thanks...
It's always great to have a chance to talk to you. It's been a few years now since you've joined Pinterest as the CEO. I think the anchoring theme I always consistently hear from you is about making Pinterest as a platform more actionable. Can you talk about the journey you've been on measured against that goal from when you came into the company?
Yes, absolutely. I mean the headlines is like Pinterest has become an AI-driven shopping assistant for 640 million-plus users, becoming one of the fastest-growing platforms in social media, consistent double-digit growth in users, strong engagement growth. And at the core of that has been the actionability that you just mentioned.
Coming into Pinterest 4 years ago, it was pretty much a platform for visual discovery and browsing, but it wasn't a place to buy things. And it's now the case that more than half the users that come to our platform are there to shop. Gen Z is the largest, fastest-growing cohort, more than half our users and primary use case is shopping.
And at the core of that is making so that you can discover more of what you're looking for, make more of those purchases. And that has been at the core of the revitalization of the platform, both in terms of the user side of it, where we're getting much deeper engagement, particularly with those Gen Z users. Stated simply, Pinterest is where Gen Z goes to shop. And it's a place where they're thinking of as a first place to go search increasingly as well.
So there's an Adobe study that we've cited previously that 39% of Gen Z thinks of Pinterest as the first place to go search. Why? 71% of Gen Z sees Pinterest as more personalized than other places to go search. So at the core of it is it's not just us using AI, it's us using really unique data that we get around the human curation on our platform.
So AI doesn't have style and taste on its own, humans do, but that's what people do on our platform is curate that style and taste, and we've used AI to go really superpower our recommendations to users, giving them great recommendations before they even know what they're looking for, that users will say, "Oh my gosh, Pinterest just gets me," and increasingly make it so that they can shop and buy.
And that's why now you see that from a platform that was almost entirely upper funnel ads 4 years ago, we've talked consistently about 2/3 plus of the business is lower funnel performance. We talked about more than 5x the number of clicks to advertisers over the last 3 years. Those things all get to like the deep actionability on the platform. And so we've had great progress there.
At the same time, in the course of like monetizing a platform like this, we're still relatively early on. There's still a lot more opportunities. So one of the strongest parts of the story has been our growth in user engagement. And then the monetization, I talked about the shift to lower funnel. We've made great progress on that, especially in our home market here in the U.S.
But then international, where we have more than 80% of our users, still roughly 20% of our monetization. So a lot more of that to go there. So when I sort of look at the progress, we've clearly proven out Pinterest as a shopping destination, clearly proven out we can make it actionable, clearly proven out that we have differentiated signal to train the AI on to give fantastic recommendations to users so they want to come back and shop more.
That's a global phenomenon. And then the monetization always follows in behind the user behavior. And so we've made great progress in the U.S. We're translating more of that international, but there's a lot more of that to do.
Okay. Building on that answer about your future vision for the company, we got the news in the last week of Julia's departure from the CFO role. Can you talk to us when measured against where you want the platform to go, what you'll be looking for in a new CFO?
Yes, certainly. So having built from zero to many billions multiple times, these things are like relay races, right? When you think about sort of what's the team and the things you need to do for each leg of the race. And I sort of touched on this a little bit in the last comment of like what were the things that we needed to address.
And 4 years ago, this is basically a single product platform in a single geography. And we're now moving into multiple products, much more -- many more geographies, much greater complexity. And we've been building up a team for that leg of the race.
And so if you look at what we've been doing more recently across the team, started with a new Chief Product and Technology Officer that led shopping at Google, is doing a fantastic job with what we're doing with the tech platform, bringing in a great team there, recently a new Head of Product Engineering for ads, new Head of Infrastructure, that new head of sort of the internationalization of the platform on the product side, new Chief Business Officer, new Chief Marketing Officer.
And so we're really building up the team for where we need to go next. And so similarly for the CFO, when I think about that, we have now proven out that we can monetize our audience beyond just one surface. We did the acquisition of tvScientific. We've got multiple products within Pinterest, now monetizing beyond the one surface, going into many more geographies.
So when you look at that complexity of the next leg of the race, we've been building a team around that. And these are things that we'll be solving for with our next CFO and that we'll want a deep operational partner. Grateful to Julia, she ran her leg of the race well, a very good partner through that. I'm sure she'll be great in the next thing that she goes and does.
But if you look at where we were 4 years ago, there's a lot of what we were doing was sort of addressing a lot of things that ideally probably should have been done before the company was public. And so we were really getting a lot of that operational rigor and hygiene. And now we're in this place of expanding to more products, more geos that brings greater complexity.
So we'll look for another great operational partner, but one that has done a lot of that kind of operational complexity at scale and across the rest of the team, that's what we've been building for. And we're seeing really great talent, really great candidates for our CFO search. So I'm quite confident that we'll get a really exceptional person in that role that will be a great partner for the next leg of the race.
Okay. There's so many themes of convergence that we've been talking about over the last 12, 18 months, search, social media, commerce, AI. When you think about the broader discovery process that consumers are going on right now against those themes of convergence, how do you think about positioning Pinterest against consumer discovery over the medium to long term?
Yes. Well, I touched on this a little bit but we've made tremendous progress. I think it's been the strongest part of our story is the, and it's a big change in the story. 4 years ago, Pinterest was a platform that was rapidly declining in users, had missed the next generation. Now to a platform of 12 straight quarters of record high users.
Gen Z is more than half the platform, our largest, fastest-growing audience. We've talked about many times how we're growing across every geography that we track, across the generations that we track. And so it's broad-based. And so at the core of that is people are thinking about different ways to engage in their shopping experiences than what they did previously.
I said this before that the first 25 years of e-commerce in a lot of ways sort of solved buying but killed shopping. And the distinction being that if you knew what you wanted and then you wanted to get the cheapest and the fastest, there are a lot of things built for helping you do that.
But a lot of the rest of the shopping journey was about, well, I don't know what I want to buy yet. It's the sort of I'll know it when I see a problem. And if you think about how people shop in the real world, that's a lot of it, that whether they want to update the wardrobe for fall or they're thinking about what to make for dinner that night, they'll go into a shopping setting with a sort of loose idea, but if you ask them like, "Hey, tell me exactly what it is you want to buy," they say, "No, I know when I see it."
And that's what Pinterest is solving. But we're solving it now in a way that is going from that upper funnel discovery all the way to basically sort of dream, decide and do. So like what's that initial kernel of the idea? How do I refine that? How do I make a decision and then how do I easily take action on that? And we're solving across all of those.
And a thing I'll share one of the questions that we'll often get, especially on the strength of our Gen Z usage. And it's funny, I used to get this question all the time in the early days of Venmo where people say, are these millennials ever going to like spend money? And it's like, of course, they're going to graduate college, and they're going to spend money in like all of these things.
And then we get that question about Gen Z, a lot of like, well, can you monetize those users? And with Gen Z, not only are they our largest, fastest-growing demographic, more than half the platform, they have the deepest engagement, the highest retention. They're also the most AI native. So they're building AI native capabilities, things like that.
They are deeply versed in those things, like so our assistant capabilities we put out there, deeply versed in those things. But Gen Z on our platform, we now see the ARPU of our Gen Z users in the U.S. is roughly consistent with the ARPU of our older generations like millennials.
And so I think that bodes really well for the future monetization of those Gen Z users that, of course, they're going to shop. They are shopping. They're shopping quite a bit, which is why their ARPU is now consistent with the next generation up with millennials.
And I think that bodes really well for the future monetization of our platform because the purchasing power of those Gen Z users is only going to increase, and they see Pinterest as a place for them. Again, Pinterest is where Gen Z goes to shop. And so we see that, even as their purchasing power is early in its growth, they've already equaled the ARPU of millennials on our platform.
So we hadn't shared that previously, but that's what we're seeing on the platform. It's exactly what I would have expected having built commerce experiences previously as these generations mature, but the depth of the engagement with our Gen Z users is just quite significant and it outpaces the other generations on our platform.
Okay. Understood. You spent some time on the Q2 earnings call talking about your approach to AI as a company. Against the landscape of what's available to you, models, products, things you can bring into your ecosystem. Talk to us a little bit about your AI strategy, both in terms of what you can pull into your ecosystem from the AI landscape and then how you can take elements of your data and build personalized unique experiences at Pinterest in a cost-efficient manner.
Yes. So this is, from the time I came over from Google, I spoke most consistently that in this coming wave of AI, the sort of model capabilities will be available to many, but then there's going to be a lot of opportunity for places that had unique data that AI thrives on feedback loops. So what are the places that had unique data, unique user feedback loops.
And for Pinterest, I talked about how we're using that unique human curation on our platform to train our AI to give really, really distinct recommendations. That's at the core of the reacceleration of the platform that basically everything you see on Pinterest is served by AI and has been for a couple of years. That's one of the first things I said about doing coming into Pinterest.
But we use a combination of compact fit-for-purpose models and taking open-source, open-weight models and post-training on our data to really great effect. And we've been talking about this for years. Now there's a lot of discussion of open-source, open-weight. We are very early on that. There's a lot of discussion like model routing. We are very early on that.
There's a lot of talk about, oh, well, maybe you don't need the frontier for every task. Maybe that is oversolving a problem at much too great an expense. Well, check the tape, like we've been on this for several years. And it's part of why even as we have made it so that everything you see on Pinterest is served by AI, we've also had significant expansion of margins in our business over that period of time because we have been able to not only align those AI use cases with highly monetizable events that are very, very commercial.
It's also the case that we've been able to do it at very, very good cost effectiveness, and that's because we use compact models trained on our unique data. We get great results from post-training open-source, open-weight. And I think that's a really important thing as you look forward that in the initial sort of wave of adoption, sort of everybody is just racing to make sure they didn't miss out and particularly less sophisticated companies like that, which is like just give me whatever I can adopt.
And as you now see token bills coming in and things like that, people are thinking a lot more about, I probably should think about the right tool for the job. And like using the frontier for everything, it might be a little bit like using a Formula 1 engine to like mow your lawn. You may have like not only massively overpaid, you may not have solved the problem as well as something that was built fit for purpose for the thing that you're trying to do.
And I think one of the most exciting things that has happened in the industry is the advancement of open-source and open-weight. I said on our last earnings call that, and I'll say it again because I think it's really important. A CEO that's not heavily leveraging open-source, open-weight models is almost certainly wasting a lot of shareholder money because you can get similar capabilities at dramatically lower cost.
For us, we shared that when we use open-source, open-weight compared to a comparable sized model, we are able to get cost at less than 8% of what the comparable closed models would be. But we also see greater effectiveness because you can't train the closed models on your own data. So when you can train on your own data, that's greater effectiveness.
And it's actually greater safety as well because you can run it in your own secure environment, which you can't do with the closed models. And so you know where your data is going with the open-weight models when you're running in your own environment. And not only do you have a very good thriving open-source, open-weight ecosystem now, including here in the U.S. with U.S.-based models, you have the hyperscalers leaning in and doing what they've always done.
If you look at how important open-source software was over the last 30 years, a big part of that was that hyperscalers came and sort of packaged up open-source to make it easy for others to use like most of the Internet runs on Linux. Well, Linux, most people would have thought it like sort of harder to use earlier on, but then you had hyperscalers sort of package that up and make it really easy for others to consume.
And the same thing is happening with models now that you have these open-source, open-weight models that are just only a few months behind on any comparable size, tend to be only a few months behind the frontier. And then you can post-train on your data, get better results, much lower cost and now much easier and safer to do because you can do it in your own environment, whatever hyperscaler you use, you can do it in the environment where your data already exists, your data is secure, it's not going out someplace else.
And so I think that's a really important trend. And it's a good thing for the thriving of the overall ecosystem just as open-source was. Most of the companies in the valley wouldn't exist if not for open-source software. And so I think that just says that this sort of world-changing technology will be in the hands of the many rather than the few.
The innovation will be for the many rather than a few because of what's happening with open-source and open-weight and having chip makers like NVIDIA really behind that, having hyperscalers behind that. I think just says like there's clearly a good ecosystem there. And it's what we've been doing for several years now, saying like right tool for the right task gets you better effectiveness, better cost and you can do it safely and securely. And so I think that's a really, really good thing for the broader tech ecosystem.
Okay. I wanted to turn to the advertising landscape. We're sitting here in early September. What are you seeing in the ad market today? And away from sort of the environment, how are you also thinking about the competitive landscape and where Pinterest fits in to the broader ad ecosystem right now?
Yes. So as I get started on this one, I want to make sure I'm really clear that I'm not updating or addressing guidance with this. It's not our practice to give intra-quarter updates on trends. That said, the puts and takes are consistent with what I talked about on the earnings call. So I'll spend just a minute sort of going back through like what we talked about on the earnings call with regard to the puts and takes in our business.
So we talked about the user growth a bunch. One of the really exciting things in H1 of this year is the reacceleration of our UCAN business. There's a lot that we're working through with adjusting the tariffs last year, being a shopping destination and sort of the impact on retailers. That was a lot that we're working through last year. So the reacceleration of our UCAN business is quite noteworthy through H1.
We talked about how the AI-driven ad platform, our ROAS improvements for advertisers that we feel like those things were durable as we looked into Q3. And so that's something we're really, really excited about.
We also talked about, though, on our international business that we were seeing pressure there on 2 fronts. One, new regulation in Europe that puts limits on Asia cross-border sellers. So technically not tariffs, you can think about it similar to like what happened in the U.S. with tariffs where EU is putting up new restrictions on Asia cross-border sellers. So it's a new thing in Q3, and so that creates pressure in the international business.
And the other thing is we're restructuring on the international business with our go-to-market, just as we did in the U.S. So you saw in the U.S. that we, as we reaccelerated, it was the AI-based ad platform improvements as well as significant overhaul of our go-to-market and some of the early signs of benefits of that.
We're basically taking that playbook from the U.S. of shopping in the U.S., the go-to-market in the U.S. and now deploying that internationally. We talk about, okay, that will create some near-term pain to restructure those things, but that we think is very good for us in the medium to long term, just as it was in UCAN. So those are some of the puts and takes in terms of what we see in the business consistent with what we talked about on the call.
Stepping back from sort of these near-term things like new regulation in the EU and sort of short-term restructuring of our go-to-market and things like that, the shopping behavior of our users is a global phenomenon. The AI-driven platform improvements are a global phenomenon for us.
And we are, continue to be very excited about that because what we're proving out is that not only can we drive great actionability, great outcomes for advertisers, we're creating a truly full funnel experience where historically, you have upper funnel, mid-funnel, lower funnel happening in different consumer surfaces. We're bringing that together.
And we're proving out that not only can we drive great lower funnel performance, but as advertisers are seeing more and more that, well, sort of discovery and research may happen in one place, the last click may happen in another, our ability to tie that together and drive great performance is really shining through with advertisers.
And I've shared previously that what great CMOs always knew that the last click wasn't the only thing that mattered, but that when we had advertisers doing multiple objectives, thinking of sort of upper and lower funnel together, that was 2x the conversion on that, but now 3x the conversion for us.
So like that benefit of doing multiple objectives with us because they can span upper, mid- and lower, that's now 3x the conversion. And so we see that as we get the sort of flywheel of more users curating their taste on the platform, our AI-driven recommendations get better and better off of that signal, more and more differentiated off that signal, drives better and better outcomes for advertisers and let advertisers engage across discovery sort of decision-making and then ultimately purchasing, we think that is something that is quite unique.
And as we talked about the reacceleration of our UCAN business and the AI-driven ad platform improvements, retail is a strength for us, right? Shopping is a strength for us. And so we think that's something that bodes really well.
And as we're rolling out new AI-driven capabilities to consumers, I think we're striking a great balance between the AI sort of powering their experiences, but in a way that the users feel like is very human-centric to them. And as there's a discussion of AI slop and like all these things, Pinterest is a place where users actually get to directly engage in how they're refining their style and taste and AI is there for the assist, but it's not sort of overpowering the experience.
And so I think that is not only good for users, but advertisers are really liking how we're driving great results, but in a way that's like brand authentic to them across all those stages of the funnel.
Maybe just one quick follow-up on that. When you think about where you're going over the medium to long term, has your view with respect to agentic commerce evolved at all? Because I think that's been a big talking point over the first day plus of the conference because you're trying to get to more shoppable, you're talking about conversions. What role does agentic commerce, either on platform or off-platform have to play?
Yes. So we've had some really exciting progress on this. I've talked about how Pinterest has become an AI-driven shopping assistant. We took a different approach than others. In the same way that I've said the first 25 years of e-commerce sort of solved buying but killed shopping. And you saw a lot of others go after agentic commerce, they went after the buy first.
And I said very consistently that clicking the buy button is one of the easiest things not only for the consumer, but also technically, one of the easiest things. The real promise of agentic and where consumers wanted the help the most was making the recommendation before they knew what to ask.
So that promise of agentic of the agent sort of out there shopping for me before I even know what to ask, before I know what to do or I was looking for something and I come back the next day and like, "Oh my gosh, I found the things that I was looking for." This is what we've been doing on our platform, what we've been focusing on and what's driving the depth of engagement.
So we've been consistent on that. It's at the core of how we're driving engagement, and we continue to progress on that. Our new assistant capabilities where basically you can think about we've had AI in the background on a lot of these things, like making all the recommendations, every pin you see is served by AI, the really powerful personalization experiences, all being driven by AI, and that was in the background.
We've now brought that more to the foreground. So our new assistant has been made available to virtually all users in the U.S. And we're seeing some really exciting things there. And that in the same way that we took Pinterest deeper into the lower funnel with actionability with clicking and purchasing.
It's also the case that we see that we're driving so much discovery and decisioning that those Gen Z users on our platform, like they've all used AI, right? They've all used chatbots. And we see that they start with Pinterest and then like, oh, they find on Pinterest, they purchase on Pinterest, but they may have like a research question like, "Oh, hey, I want to buy that pair of shoes, but I haven't bought that brand before. Do they run bigger, they run small?"
Well, now as our assistant, you can just ask that right inside of Pinterest. And the encouraging early signs we're seeing there, we've talked about how on our platform, overall, we now see over 80 billion searches per month and more than half of those are commercial, which is a much greater commercial skew than you would see in other places to go search.
So we are clearly a shopping-centric destination. With our assistant, we're seeing that while searches overall for us, more than half would be commercial with the assistant, it's 80% commerciality. So back to us aligning AI with like highly monetizable use cases, that continues to play out as we bring those assistant capabilities more in the foreground in a way that still is very visual first, but lets you ask some of those follow-on questions right inside the platform in a way that's really effective and very cost efficient.
So it is notable, we said this on the call that at the same time, we made our assistant capabilities available to all of our users in the U.S. or virtually all of our users in the U.S. We also took up margin guidance, which gets back to using AI in a way that is very effective because of our unique signal, but also in a way that is very efficient from a cost perspective.
Okay. Super helpful. We have a few minutes left, I just want to try to get through maybe 1 or 2 big picture topics. One we've written about and we've talked about on earnings calls is the evolution and the scale you've been building around Performance+. Can you talk a little bit about Performance+, how it fits into your broader advertising ecosystem and how to think about what that does for the platform over the medium to long term?
Yes. So this is a place that we've been very excited about, and we've seen really good results with advertisers. And obviously, we were setting out on that journey sort of after some of the larger platforms, but we've seen really, really good progress. We only went GA with Pinterest Performance+, our AI-driven ad platform at the start of last year, sort of 1.5 years into GA.
And so adding lots and lots of features. I think for us and other platforms, we'll be adding features to this in perpetuity, right? So you shouldn't think about it as like, oh, there's a launch and then did you get everything out of it from just that one launch, like you're building on that in perpetuity.
But we shared previously 30% of our lower funnel revenue now going through Pinterest Performance+. Well, the pace of that adoption has been quite exciting. And I think when you compare it to the pace of adoption on the larger platforms that were at it for multiple years before Pinterest, I think that pace of adoption compares really favorably.
I'd say almost roughly half the time of what that would have taken from the public commentary of other platforms. So we feel really good about the pace of that adoption and the fact that it's helping advertisers tap into really unique shopping behavior with really good incrementality and again, meeting those users in a place that is not only letting the advertiser get great results, but also really tell their story in a way that differentiates.
I think this is something that every advertiser is struggling with is as sort of traditional sort of SEO-based web traffic declines, which you see in all kinds of data out there that, that is declining and more of these decisions happen in other places. Well, as those decisions are happening in other places, how much can the advertiser engage?
And advertisers, they've been doing a lot of things to try to figure out like, well, if I do this thing over here, does it eventually some way trickle into something that happens on the other side, like in a lot of ways, you're sort of competing to be the salt in the soup on that. Like how do you, and like for us, we're making so they can engage directly, and they're not competing to be the salt in the soup, like they get to be the main course and that they get to have their brand show up exactly how they want to show up in a way that is actually really compelling for the user also because since we're a shopping destination, ads can be great content on our platform.
So these things, I think, again, we're quite excited about that and the rollout of Performance+ is just making it easier and easier for advertisers to take advantage. We talked about cutting the time in half for them to create campaigns while also getting these like really great results in terms of how to meet the user, where to meet the user, how to engage with them across multiple stages of the journey and then having AI just figure that out for them versus them having to go do all that manually.
Okay. You also decided to acquire tvScientific. Talk to us a little bit about how you're thinking about that asset now that it's inside your portfolio, amplifying some of the commercial proposition of the advertising offering, how we can improve signal, how we can drive more performance outcomes.
Yes. So the basic premise with this, so tvScientific is a performance advertising platform for connected TV. And one of the things that we've talked about is that as we made Pinterest a shopping destination that job one is certainly make Pinterest itself a destination, which it clearly is. More than 85% of our usage comes to our mobile app directly. Pinterest is a destination.
And there's a lot more to go on that. But the audience that we have, like I would say, we believe we've got more direct knowledge of user commercial intent probably than any other platforms aside from Google or Amazon. And what you've seen in those platforms is that you can take the value of that audience to build great ad products beyond one surface.
And we've taken our highly commercial audience and our knowledge of taste and preference and what users are looking for, and we're using that to show much more personalized ads on connected TV, and we're proving that in the same way that on our platform, we said doing multiple objectives leads to 3x the conversion rate when you do sort of upper and lower together.
We're now showing it on connected TV. The historical world was like you and I would watch the same football game on Sunday, and we see the same ads. Well, we may have some similar interest, I'm sure we do. We get along great. But I'm sure that at any given moment, you are shopping for different things. We should see different ads, and that's not just better for the advertiser, better return the advertisers is better for the user.
And so with tvScientific, it's letting us to show those much more personalized ads. But then the thing that we've talked about is as we do that, we're able to show that adding our audience on top of what tvScientific was doing with performance advertising an CTV, there is a more than 60% lift in purchases from doing that.
So how valuable is that audience tremendously. So there's a lot more that we'll do in connected TV, but we think the value of that audience is quite noteworthy and lets us think about how we monetize across multiple other surfaces. We're at the very beginning of that. We think that's a big forward opportunity.
And maybe just a place I'd say in terms of where we are in this moment, AI is moving very quickly and sort of where people think the value is going to accrue keeps shifting. And there was a stage of this where people were saying like, oh, all the value goes to the model creators, right? And there will only be 2 or 3 companies in the future because all of the value goes there.
And then, oh, well, wait a minute, hyperscale is going to be pretty important in this and like chips and memory are going to be pretty important in this. And then now you see with open-source and open-weight, you have a lot of commoditization of model capabilities.
And in the same way that open-source software didn't lead to zero proprietary software. In fact, most proprietary software, much proprietary software leverages open-source, you're going to have a mix of both closed models and open models. But that says like, oh, with the advent of open-source and open-weight models, that's going to allow for much broader value creation.
And so a lot of people have been focused rightly on, there's a lot of infrastructure build-out and those kind of things. I think the next part of this that people haven't paid enough attention to is how much value there is in distribution, how much value there is in unique data.
And this is a place where at 640 million users, we are clearly one of the largest practitioners of applied AI, bringing AI-driven experiences to a huge mass of users in a very unique way. Search has been, search is in this expansionary moment, right, where it's clearly the case that chatbots are a new form of search for most consumers, that's expanding the search market overall.
But search has also been fragmenting for years and that there were a few general purpose winners with many vertical-specific winners. We are driving that sort of vertical-specific around shopping and visual. But we think there's a lot more of that, that we can do across multiple surfaces.
And we're in a moment where I think that people are seeing that, okay, yes, there'll be a lot of value in the closed models, but open models make it so that a lot more value can accrue to those who have distribution, who have consumer relationships and those who have unique data. And tvScientific is sort of the first step in us proving out the value of that audience across multiple surfaces.
Okay. I think in the interest of time, we're going to have to leave it there. I always love getting the opportunity to chat, Bill. Please join me in thanking Pinterest for being a part...
Thank you.
Pinterest — Goldman Sachs Communacopia + Technology Conference 2026
Bill Ready frames Pinterest as an AI-first shopping assistant for Gen Z, emphasizing open-source AI efficiency, Performance+, CTV expansion, and international monetization work.
🎯 Key Message
- Message: Pinterest is positioning itself as an AI-driven shopping destination where recommendations drive discovery→decision→purchase. Management stresses human-curated data plus compact/open-source models to deliver personalized, monetizable experiences and deepen Gen Z engagement rather than relying solely on frontier models.
⚡ Strategic Highlights
- Product: The assistant is now foregrounded and available to virtually all U.S. users; assistant queries skew ~80% commercial vs platform-wide ~50%, boosting high-value use cases.
- AI & Costs: Strategy blends compact fit-for-purpose models with post-trained open-source/open-weight models; management claims cost of open-weight approach can be <8% of closed alternatives, with better data security and effectiveness.
- Monetization: U.S. monetization and Performance+ adoption are strong; international (80% of users, ~20% of revenue) is a priority but faces near-term EU regulation and go-to-market restructuring headwinds.
🔭 New Information
- CFO: CFO Julia departed; company seeking an operational, scale-experienced CFO to manage multi-product, multi-geo complexity.
- Gen Z ARPU: U.S. Gen Z average revenue per user now roughly equals millennials on Pinterest, indicating stronger monetization than previously assumed.
- tvScientific: Early integration into connected TV (CTV) shows that adding Pinterest audience targeting drove >60% lift in purchases for CTV performance campaigns.
❓ Analyst Q&A
- AI strategy: Analysts pressed on model choices and costs; management reiterated "right tool for the job," favoring open-weight post-training for cost, safety, and better performance on proprietary data.
- Ad market & Intl: Discussion covered H1 UCAN reacceleration, EU restrictions on Asia cross-border sellers, and short-term pain from international GTM restructuring versus long-term upside.
- Ad products: Performance+ adoption pace, multi-objective (upper→lower funnel) benefits, and the role of agentic commerce/assistant were probed; management cited higher conversions and easier campaign creation.
⚡ Bottom Line
- Bottom Line: Pinterest presents clear product and monetization momentum—AI-powered personalization, strong Gen Z engagement, Performance+ traction, and CTV synergies—tempered by near-term international/regulatory headwinds and a CFO transition; long-term upside depends on executing international monetization and preserving AI cost advantages.
Pinterest — Q2 2026 Earnings Call
1. Management Discussion
Hello, everyone. Thank you for joining us, and welcome to Pinterest's Second Quarter 2026 Earnings Conference Call. [Operator Instructions]
I will now hand the conference over to Andrew Somberg, Vice President of Investor Relations and Treasury. Andrew, please go ahead.
Good afternoon, and thank you for joining us. Welcome to Pinterest's earnings call for the second quarter ended June 30, 2026. Joining me on today's call are Bill Ready, Pinterest's CEO; and Julia Donnelly, our CFO.
The statements we make on this call reflect management's view as of today and will include forward-looking statements. Such statements involve a number of assumptions, risks and uncertainties, and actual results may differ materially. We disclaim any obligation to update these statements. For information about assumptions, risks, uncertainties and other factors that could affect our results, please refer to our earnings press releases and the periodic reports we file with the SEC and are available on our Investor Relations website at investor.pinterest.com.
During this call, we will present both GAAP and non-GAAP financial measures. A reconciliation of non-GAAP to GAAP measures is included in today's earnings press release and presentation, which are distributed and available to the public through our Investor Relations website. Lastly, all growth rates discussed today are on a year-over-year basis unless otherwise specified.
And now I'll turn the call over to Bill.
Thanks, Andrew. Good afternoon, and thank you for joining our second quarter 2026 earnings call. Our strong Q2 results reflect the progress we're making against our strategic priorities. We ended the quarter with 640 million monthly active users and delivered revenue growth of 18% globally and in UCAN, a 5-point acceleration in our largest market.
We continue to build momentum across our 3 strategic priorities: first, continuing to build a differentiated visual search, discovery and shopping experience for users; second, keeping AI at the core of everything we do, from powering the user experience, to our ads platform and our internal operations; and third, accelerating monetization through improved go-to-market and measurement capabilities. At the center of our strategy is a simple idea: Pinterest helps people discover what they want and then go do it in the real world.
That idea comes through clearly in our new brand campaign built around the line, the best thing you can find online is a reason to go offline. It reflects what makes Pinterest different. People come here with intent. They find inspiration that is personalized for them, refine their style and taste, and they can take action directly from our platform. The human curation that is so unique to Pinterest is the highly differentiated signal that trains our AI to make such exceptionally relevant recommendations to users.
Today, I will focus my remarks on two topics that cut across those priorities: how AI is powering our user momentum and how we're turning that strong engagement into more durable monetization. With that, let me start with the user side of the story. Q2 marked our 12th consecutive quarter of record users and our 11th straight quarter of double-digit user growth. In our core UCAN market, users grew 4%. We're also winning significantly with the next generation of users, as Gen Z continues to be our largest and fastest-growing cohort, representing over half of our user base.
AI has been at the heart of this momentum. We've transformed Pinterest into an AI-powered shopping assistant. Effectively, every pin a user sees is personalized and served by AI. We were early to move on AI and its enabling technologies, having completed our full transition to GPU serving more than 2 years ago, which materially improved relevance and personalization using larger models and more data.
Our scale and the unique human curation that occurs on our platform have fueled our proprietary Taste Graph. With more than 80 billion monthly searches on Pinterest, the vast majority of visual and over half commercial, and over 16 billion boards created on our platform, we have a uniquely valuable signal: human taste and curation at scale. This enables us to train our AI with a deep understanding of taste, context and intent that gets more personalized every time a user comes back.
This powerful feedback loop is what helps users discover what they want before they have the exact words, brand or product in mind. That's why so many commercial journeys begin on Pinterest. Today, over 96% of text-based searches on our platform are unbranded, for instance, cool running shoes or new fall wardrobe ideas. This is a great moment for marketers to meet prospective customers when they have clear commercial intent, but haven't yet decided what to buy.
As users move from inspiration to a more specific decision, their needs evolve from discovery to research with questions like, "Do these shoes run true to size?" Or, "Can you compare these two brands." To handle this part of the commercial journey, we're bringing AI further into the foreground of the user experience with our AI conversational layer, Pinterest Assistant. This intelligence layer, which we made available to the vast majority of U.S. users as of the end of July, helps our users answer those later-stage research questions, enabling them to move from an idea to a finished plan or purchase entirely on Pinterest.
Pinterest Assistant is now woven throughout the user experience. Users can engage with it where they already explore and plan with contextual entry points and prompt suggestions across the experience, and will be able to generate product comparisons, step-by-step instructions and visual forward guidance. For example, someone planning a living room refresh can ask what styles work in their space, get help finding the right rug and explore ways to pull it all together within their budget, all without leaving Pinterest.
What makes Pinterest intelligence differentiated is it is built on our Taste Graph, years of visual curation signals from user searches, saves and boards, giving you a deep understanding of products and style that is highly relevant to how people shop and to each individual's taste and interest. Notably, it's also visual-first, consistent with the experience users expect from Pinterest. We are also beginning to introduce memory and conversational history, creating an even more personalized experience.
Importantly, we are building this capability in a highly differentiated, effective and cost-efficient way. Our approach to model deployment includes our own compact fit-for-purpose models built for Pinterest-specific use cases and suitable open source models post trained in our own environment within our secure cloud infrastructure. When we leverage open source models, such as with Pinterest Assistant, we are seeing superior performance for our use cases when compared to closed third-party models because we are able to post train open models on our highly unique data. With open models, we are achieving cost per transaction at less than 8% of the cost of comparable closed proprietary models. This gives us substantial headroom to deepen and extend these capabilities over time in a way that is differentiated, highly effective and cost efficient.
Stepping back, this is the next iteration of work we've been doing for years, taking the discovery and intent that already exists on Pinterest and making it even more actionable for users, helping them move seamlessly from dreaming to deciding, doing and buying. With the launch of our AI conversational layer, we are taking the next step to enhance that actionability even further and making it even more seamless for our users to move through their entire commercial journey on Pinterest. This is what sets up the monetization story I'll turn to next.
On the monetization side, AI is helping us improve advertiser performance across the funnel, from better targeting and bidding to more automated creative and stronger measurement. As we shared last quarter, advertisers using Pinterest Performance+ campaigns see meaningfully better ROAS and grow spend faster than those who haven't adopted it yet. That uplift comes from automating more of the campaign setup, bidding, budgeting, targeting and creative optimization that advertisers historically had to manage manually, while still giving them clear controls.
As part of our efforts to serve a broader group of advertisers with Pinterest Performance+ campaigns, this quarter, we launched a Smart Assembly to help more advertisers benefit from creative optimization tools. This is a new Pinterest Performance+ creative capability for advertisers promoting brands, services or content who do not have existing shopping product catalogs. Advertisers can upload multiple images, and Pinterest automatically builds and serves the best performing ad for each impression.
In early alpha testing, Smart Assembly delivered a 6% improvement in click-through rate on average, demonstrating that creative testing and diversification can meaningfully improve performance. Over time, our goal is for nearly every lower funnel campaign on Pinterest to start in an AI-powered best practice setup, with added controls for more complex buyers who need them. Our near-term road map, including a simpler campaign creation flow, more sophisticated bidding and more automated creative, is designed to drive the next leg of Pinterest Performance+ adoption, including among advertisers that require both performance and increased control.
We're also investing in Business Assistant, our conversational AI collaborator for advertisers, which is currently in beta. Business Assistant combines an advertiser's business context with Pinterest platform insights to surface actionable recommendations, including relevant trends, top-performing pins and optimization opportunities. The goal is to help advertisers understand what is resonating on Pinterest, decide where to put the next dollar and make Pinterest easier to use and scale, especially for advertisers that do not have large dedicated teams.
At the same time, we are upgrading our bidding and measurement systems so we can do two things better: help advertisers find the highest value impressions on Pinterest and prove that value through the metrics and measurement systems advertisers already use. With a small initial group of some of our largest and most sophisticated advertisers, we are continuing to pilot integration between their in-house measurement systems and our AI bidding systems, allowing us to optimize bidding towards their unique set of desired outcomes. That initial group is seeing strong performance, partially contributing to our strong Q2 results.
We are now expanding testing to a small number of additional advertisers over the course of the third quarter. The learnings are also informing broader bidding enhancements across the platform that can scale to many more advertisers. We are always working on making our core ad delivery engine better through adapting new and better signals and driving enhancements in our AI modeling work.
This quarter, we have made our shopping ad delivery systems better at deciding which products to show, when to show them and how to allocate budgets against the highest-value advertiser opportunities. That includes improving product selection for advertisers with large catalogs and increasing the variety of relevant products users see. This package of changes are designed to improve lower funnel performance across both large enterprises and smaller advertisers. The early results are encouraging, helping drive stronger, more consistent ROAS.
Finally, we are continuing to extend Pinterest's unique consumer intent signal and audience to connected TV through tvScientific, and early advertiser reception continues to be strong. In 2027, we expect to fully integrate tvScientific capabilities directly into Pinterest Performance+, turning Pinterest into a full funnel search, social and CTV platform performance solution and opening access to larger and incremental budget pools. We're pairing this progress across our ad platform with a more disciplined, performance-oriented sales and go-to-market motion, helping us better monetize the strong engagement in commercial intent on Pinterest.
Early progress on sales and go-to-market transformation was reflected in our strong Q2 results, particularly in UCAN. Our focus on clear seller accountability, better packaging of commercial moments and a tighter connection between product performance and advertiser conversations are supporting strong UCAN demand. We're also making progress on our mid-market and managed SMB go-to-market efforts, including restructuring account coverage teams and realigning incentives to better serve this cohort over time.
We're now applying our UCAN playbook internationally, where we see significant opportunity to close the gap between engagement and revenue. We're earlier in this work, but our progress in UCAN gives us confidence in the opportunity. With new international leadership, we're sharpening our global go-to-market approach and bringing more global discipline to how we drive performance selling internationally. We're also testing the expansion of third-party demand into Europe. Taken together, the product-led improvements across our ad platform and a more disciplined go-to-market engine are strengthening monetization and helping revenue better reflect the value of the engagement we're seeing on Pinterest.
In closing, Q2 shows that we are making progress on the priorities that matter most. We are building an even more differentiated visual search, discovery and shopping experience. AI is improving both the user experience and advertiser performance, and stronger go-to-market and measurement capabilities are helping revenue better reflect the engagement we see on Pinterest. We are still early on many of these initiatives, but the initial results indicate we are on the right path.
As we build for the long term, we remain focused on making Pinterest a positive platform centered on time well spent. As a global conversation around online safety and youth well-being continues to grow, we believe that foundation matters more than ever. We will keep making deliberate choices to put user trust and well-being at the center of the experience, and we remain confident that building a positive platform and building a strong business reinforce each other.
With that, I'll turn it over to Julia to walk through the Q2 financials and our outlook in more detail.
Thanks, Bill, and good afternoon, everyone. Today, I'll be discussing our second quarter 2026 financial results and provide an update on our third quarter 2026 outlook. All financial metrics, except for revenue, will be discussed in non-GAAP terms unless otherwise specified, and all comparisons will be discussed on a year-over-year basis unless otherwise noted.
Q2 was a strong quarter. We've transformed Pinterest into a scaled AI-powered shopping destination for 106 million users in the U.S. and Canada and 640 million users globally. Importantly, we have a direct relationship with our users. 100% of our reported users are logged in, and 85% come to Pinterest directly through our mobile app, meaning we are not heavily reliant on third parties for traffic.
Revenue exceeded $1 billion for the fourth consecutive quarter, growing 18% year-over-year. This growth was led by strength in UCAN, our core market, where revenue growth accelerated to 18% year-over-year. This performance reflects a number of our initiatives coming together. First, our ongoing ad platform enhancements to improve return on ad spend and to advance our bidding and measurement capabilities are driving advertiser performance and spend. In addition, we are seeing the early results of our sales and go-to-market transformation take hold in UCAN, where increased rigor and discipline and how we go to market are beginning to show up in our results.
As we discussed entering 2026, we have more work to do, so our revenue consistently reflects the strength of our user activity. While this will take some time to fully take hold, particularly internationally, our results in UCAN give us confidence that we are moving in the right direction.
Now I'll move to the details of our second quarter results. We ended the quarter with 640 million global monthly active users, or MAUs, growing 11% and reaching another record high. We continue to demonstrate user growth across all of our geographic regions. In Q2, our U.S. and Canada region had 106 million MAUs, growing 4%. Our Europe region had 157 million MAUs, growing 8%. And in the Rest of World markets, we had 377 million MAUs, growing 15%.
Shifting to revenue. In Q2, our global revenue was $1.180 billion, up 18% or up 17% on a constant currency basis, with strength led by our conversion and consideration objectives. Across verticals, we continue to see strength in retail, as well as smaller but faster-growing emerging verticals on our platform, including financial services, travel and health.
Turning to our geographical breakout for Q2. Revenue in the U.S. and Canada was $880 million, growing 18%. Growth came from retail and emerging verticals, including financial services, travel and health. In Europe, revenue was $213 million, growing 12% on a reported basis or 7% on a constant currency basis. Growth in Europe was driven by retail. Revenue from Rest of World was $87 million, growing 38% on a reported basis or 32% on a constant currency basis.
In Q2, overall ad impressions grew 16%. The deceleration from prior quarters was partly driven by lapping the ramp in ad impressions from previously undermonetized international markets. Ad pricing in Q2 increased 1% year-over-year. This was driven in part by stronger demand in our UCAN region as well as the higher relative mix of UCAN ad impressions, which carry higher average pricing overall.
Moving to expenses. In Q2, cost of revenue was $245 million, up 25% year-over-year and up 6% versus Q1, driven by the full quarter impact from tvScientific and our investment in additional GPU capacity. Our non-GAAP operating expense was $629 million, up 13%. The increase was primarily driven by sales and marketing due to our brand campaign and sales headcount investments, as well as R&D to support our AI and product initiatives.
In Q2, we delivered $311 million in adjusted EBITDA with an adjusted EBITDA margin of 26%, up 130 basis points versus Q2 last year. The higher-than-expected adjusted EBITDA was driven by flow-through from higher revenue. We also delivered Q2 free cash flow of $270 million. On a trailing 12-month basis, we've generated nearly $1.3 billion of free cash flow, representing 94% free cash flow conversion.
In Q2, we allocated $58 million towards share repurchases. Separately, we entered into a capped call transaction for a total consideration of $99 million, which protects against dilution from our previously issued convertible notes up to a price of $30.59 per share. As a reminder, year-to-date, we've repurchased over $2 billion of stock, retiring nearly 111 million shares. We ended the quarter with cash, cash equivalents and marketable securities of $1.3 billion.
Now I'll discuss our guidance for the third quarter. We expect Q3 revenue to be in the range of $1.190 billion to $1.210 billion, representing 13% to 15% growth year-over-year. As we move from Q2 to Q3, there are a few sequential factors to keep in mind. First, based on current spot rates, we expect foreign exchange to be a modest headwind in Q3 after providing a 1 point tailwind in Q2.
Second, the shift of Prime Day from Q3 last year into Q2 this year resulted in an approximately 0.5 point benefit to Q2 and will represent a roughly 0.5 point headwind to Q3 as multiple brands and retailers increased their advertising spend around that moment. Lastly, in Q2, we saw a nearly 1 point benefit from World Cup-related spend that will not repeat in Q3.
Moving down the P&L. We expect Q3 adjusted EBITDA to be in the range of $335 million to $355 million. We anticipate Q3 non-GAAP cost of revenue expense to be roughly flat versus Q2 2026 due to the accelerated recognition of certain contractual benefits in Q3 associated with our recently executed multiyear infrastructure agreement. In Q3, within non-GAAP operating expense, our primary area of year-over-year investment will be sales and marketing and R&D to support our AI and product initiatives.
As we saw in the first half of 2026, we continue to expect modest headwinds from cost of revenue as a percentage of revenue in the second half as a result of the investments in areas such as additional GPU capacity as well as the impact from the inclusion of tvScientific. Given our first half revenue outperformance, we now expect full year 2026 adjusted EBITDA margins of approximately 30% versus our prior expectation of approximately 29%.
In closing, I'm proud of our teams for yet another strong quarter of results as we execute against our strategic priorities. I'm encouraged by our performance in the first half of the year as we continue to deliver for our users and advertisers.
With that, I'll hand it over to Bill for some final words.
Thanks, Julia. I want to thank our teams at Pinterest, our advertising partners and all the people that come to Pinterest to find inspiration and take action.
And with that, we can open up the call for questions.
[Operator Instructions] Your first question comes from the line of Mark Shmulik with Bernstein.
2. Question Answer
Julia, you get a little bit of color on that kind of revenue guide, puts and takes, but hoping to get a little bit more color on perhaps some of the regional differences you might be seeing? Noticed a little bit of a slowdown in Europe. Is that just kind of tougher compares?
Sure. Thanks, Mark. So yes, overall, we're really pleased with a very strong Q2. And on a global basis for Q3, the high end of our Q3 guidance range is consistent with what we just delivered in Q2 when you adjust for the 3-point sequential impact I called out in my prepared remarks from foreign currency, Prime Day and World Cup spend.
At the core of our Q2 outperformance is our ongoing strength in users and engagement. We continue to win shopping demand from consumers globally and in UCAN, and that multiyear trend gives us the most conviction in the trajectory of our business. We're now making it easier for advertisers to tap into that consumer behavior through our AI-driven ad platform improvements and the early dividends from our go-to-market transformation. And that's really what's translating into the strong revenue performance that you saw in Q2, particularly in UCAN.
So let's start with UCAN since that was the biggest revenue driver in Q2. We drove a 5-point acceleration sequentially to 18% year-over-year in UCAN. And this reflects a few different things coming together. So first, as a result of our ad platform improvements, we began to see pockets of large retailer spend accelerate with certain retailers leaning in as a result of our ongoing ROAS enhancement and AI-driven bidding optimizations as well as Asia-based cross-border retailer spend into UCAN.
Second, in UCAN in Q2, the strong year-over-year growth outside of our largest retailers continued across mid-market, managed SMB and emerging verticals as many of these advertisers are benefiting from our ad platform improvements, including Pinterest Performance+ campaigns specifically. Lastly, UCAN in Q2 also benefited from Prime Day shifting from Q3 to Q2, World Cup spend and a full quarter contribution from tvScientific. So overall, as we look to Q3, we expect strong growth in UCAN to continue.
For Europe and Rest of World, we noted on the last earnings call that we expected growth to moderate in Q2 as a result of the deliberate leadership and structural changes we're making to our go-to-market organization and more difficult last year comparisons in certain markets. So in Q2, we were lapping the ramp of resellers in Rest of World last year and lapping a significant influx of cross-border spend into Europe last year following changes in the U.S. tariff environment. That moderation was generally consistent with our expectations.
In addition, we faced incremental pressure mid-quarter from Asia-based cross-border retailers impacted by regulatory actions, particularly in Europe, and that pressure is continuing in the third quarter. We have more work to do to fully realize the benefits of our go-to-market transformation in Europe and Rest of World, and we expect some level of disruption to continue in Q3. As we look to the third quarter, it's also worth noting that Q3 represents the most difficult comparison of the year for our Europe region in particular.
So stepping back, the underlying trends in our business remain healthy. We're pleased with the strong Q2 overall, led by growth in our core UCAN market in particular, which continues to be underpinned by our durable user and engagement strength that we can continue to see.
Your next question comes from the line of Colin Sebastian with Baird.
Bill, you talked about the evolution of the Pinterest Assistant and updates there as usage takes hold. And I guess as the competitive landscape continues to evolve, what are you seeing in terms of early engagement signals there? And then how are you innovating on the broader Pinterest user experience side?
Thanks for the question, Colin. Over the last 3 years, we've effectively turned Pinterest into an AI-driven shopping assistant. So even today, every pin you see on Pinterest is personalized and served by our AI. And that's been really at the core of the significant acceleration in our user growth over that 3-ish year time period.
And what we're doing now is we're bringing more of those AI capabilities in the foreground of the experience for users to interact with directly. So I'll give you a little bit more detail about how we're doing that. We're leveraging AI to make Pinterest more personalized, more actionable and more [ valuable to ] users. And that advantage continues to compound, particularly the human curation on the platform.
So we've been applying AI at scale for years. We completed our migration to GPU serving over 2 years ago. And as I mentioned, every pin you see on Pinterest is effectively served by AI. But it's really that human curation that 640 million plus users on our platform that are creating hundreds of billions of unique connections across our Taste Graph. It really gives us proprietary signal that we can use to train our AI and personalize the experience with every interaction.
And that feedback loop has accelerated over the past 3 years. As consumers are responding, that's what's led to the 12 consecutive quarters of record users, 11 straight quarters of double-digit user growth. And on the competitive landscape, we've long believed search will continue to fragment with a small number of horizontal general purpose platforms, but more vertical-specific experiences that solve distinct consumer needs. And that trend of the search market fragmenting has actually been happening for more than 2 decades. Think of how many product searches start on large retailers or travel searches at online travel companies versus a general-purpose search engine.
So as AI becomes more widely available and open source models continue to improve, we believe there can be many winners, particularly in vertical-specific search. The user growth in our platform alongside the growth in AI over these last few years is very clear evidence of that. You're also seeing that the general purpose AI applications, they're discovering what those of us that have built much larger platforms have known for a long time, that it's very hard to be all things to all people, and you've seen them pull back from many of their vertical specific experiences.
So at Pinterest, we're very focused on visual search, particularly around shopping, and we're using AI to make the experience more actionable across the shopping journey. People already come to Pinterest to discover products, ideas and aesthetics they love. And research shows that shoppers find AI chatbots most valuable when researching and comparing products and narrowing their choices.
The Pinterest Assistant, our AI conversational layer that we've now made available for the vast majority of U.S. users, it brings those LLM capabilities into our visual, personalized and proactive experience. So it helps users move from inspiration through consideration and decision-making and allows them to complete more of their shopping journey on Pinterest. By combining our proprietary signals with cost-efficient open source models, that really allows us to run those securely in our own environment. So we're able to keep improving the experience, scale of innovations with strong ROI. And the result is a better product today and compounding advantage as more people use Pinterest.
And lastly, I'll just say, it has been really, really exciting to see just how much the open source ecosystem is expanding. We've been very early on that. It's been woven into our experience. It's core to what we're doing, part of how we're doing that very effectively. But it's great to see that momentum building, and this is one good example of how we're using that, but I think you're going to see more of that across the ecosystem as well.
Your next question comes from the line of Brian Nowak with Morgan Stanley.
Maybe I want to ask about the UCAN. It seems like you've made a lot of progress on the improvement in attribution and the entire go-to-market on the UCAN. But let me ask you, as you sort of look ahead the next 12 months, what are the next sort of sources of innovation or unlock that you're looking for to even drive faster and more durable growth out of the UCAN business?
Yes. Thanks for the question, Brian. The first thing I'd say is just -- we've talked about this previously. We're still a long way from having fully monetized all the commercial intent that already exists on our platform. So while user growth and engagement continues to be one of the highlights of our platform, especially as you look across sort of the social media landscape where you're seeing platforms that are generally having a harder time growing, 11 straight quarters of double-digit user growth, that user growth and the fact that more than half of them are here to shop continues to be the strongest part of that.
But as we've shared before, we shared on the last call, we 5xed the number of clicks to advertisers over that last 3-year period, but we certainly didn't 5x the revenue. So the things that we've talked about in terms of aligning our AI bidding systems with measurement systems, which I talked about in my remarks, getting more integrated into a broader set of measurement systems so that the advertisers can measure those things. And then our AI-driven ad platform where we just keep making it easier and easier and easier for advertisers to tap into that very high commercial intent on the platform.
But I think the -- we see that flywheel continuing to spin both in the user engagement and the fact that users and the engagement there is coming in the way that we want it with high intent, with search, with actionability in that advertisers are leaning in more and more as we give them better ability to go access that commercial intent.
Your next question comes from the line of Ross Sandler with Barclays.
Bill, you mentioned the integrations with first-party measurement and the like AI optimized bidding as a growth driver at some of these larger accounts. Could you just elaborate on where we are on that progression and what you're seeing thus far?
Definitely. Thanks for the question, Ross. So we're still early in the work, but the initial results from the pilot are very encouraging and contributed to our outperformance in Q2. The small number of advertisers that were participating in the pilot, they're seeing meaningful performance improvements, which is giving them greater confidence to increase their spend on Pinterest.
And so we're expanding this work to a limited number of additional advertisers in Q3. And by integrating with advertisers [ measurment source ] of truth, we're able to align our AI bidding systems to optimize for the hyper-specific outcomes each advertiser values most, whether that's customer lifetime value, incremental ROAS or another metric they use internally to evaluate performance. So the more we're able to line up precisely with what they're looking for, the more we can make sure the AI is delivering their exact outcome. And then so they see more value captured from Pinterest, and they're seeing that across the funnel, upper, mid and lower.
And while we started this work with some of our most sophisticated advertisers because they have the data and the measurement infrastructure and the technical resources required to deploy that, our most customized solutions will remain focused on that relatively smaller number with that level of sophistication. But as we move beyond that initial group of advertisers, it's reasonable to expect the full adoption curve will take place across the rest of our advertisers, but it will take some time to play out.
You're seeing a few things here, like the industry shifting beyond last click attribution to recognize value earlier in the funnel where more than just the last click matters, great marketers have always known that. The ability to take action on that is the most sophisticated to do these things first. But we're seeing that take hold through a broader swath of other advertisers through third-party measurement platforms. And so as those capabilities become easier to deploy through third-party measurement systems, we're making sure that we tie in closely to those things.
So again, those -- that adoption cycle takes time. Advertisers always have sort of cycles they go through in terms of how they adjust their measurement, and they're cautious and very methodical about that. But we absolutely see that happening across the industry, not just with us but with other platforms. And we think that general trend bodes quite well for us.
So as I mentioned already, the pay [ clicks ] average has on Pinterest are up well over 5x over the last 3 years. So all of these things help us to capture more of that value that we're already creating, and the feedback that we're getting is encouraging. Simply stated, when advertisers can see the full picture and we can tune our bidding to what matters most of them, they have more confidence, and they increase their investment in Pinterest.
Your next question comes from the line of John Blackledge with TD Cowen.
As you expand your AI product offerings, how are you managing token spend usage and AI compute costs? And what KPIs are you tracking to make sure those choices translate into real productivity gains for your teams?
Thanks, John. I can take that one. So in 2026, we've expanded our AI capabilities across our product, both for users and advertisers and also for internal productivity-related use cases. We also just raised our margin outlook for the year. So I think that demonstrates our ability to invest in these capabilities while continuing to improve profitability by managing AI and compute costs efficiently.
We've discussed our incremental investment in GPU capacity throughout 2026, which is reflected in our cost of revenue line item. We're already seeing returns through ROAS gains for advertisers in improvements to our user-facing experiences, as Bill just noted. In general, GPU investments have a relatively short payback period because increased compute capacity can be deployed quickly to enable rapid improvements to our AI models, which translate quickly into business outcomes.
As we said, we use a blended model approach that includes our own compact, fit-for-purpose proprietary models, open source models, and in very limited cases, select closed third-party models. We evaluate models across the ecosystem constantly and leverage our centralized model routing layer to optimize production traffic for the right balance of quality, cost, latency and reliability. And this allows us to reserve more capable higher cost models for complex work while using lighter lower-cost options for routine tasks.
In the second half, we're expanding this model routing infrastructure to even more internal use cases, including tools to increase productivity across engineering, sales and other functions. These costs appear in our OpEx line item. And here, we're tracking adoption, developer throughput, cycle time incident rates and service uptime to ensure that greater speed does not come at the expense of reliability.
For example, in July, weekly pull requests per engineer increased 45% versus last year, while incident rates and service uptime remained relatively consistent. So that gives us confidence that we're improving velocity without compromising reliability. As AI adoption continues to grow, we expect both AI-related compute and token spend to grow over time. We see that these investments are ROI positive and that investment growth is planned and included in our outlook that we provided. So we're scaling AI deliberately, expanding user capabilities, driving advertiser outcomes and improving employee productivity, all while maintaining a disciplined approach to profitability as well.
Your next question comes from the line of Justin Patterson with KeyBanc.
Great. You've talked about broadening your revenue base beyond your largest retailers. Can you update us on that progress, particularly with the SMBs and discuss how Performance+ adoption and the product road map supporting this effort?
Certainly, thanks for the question. So we're really pleased with our continued progress in broadening the revenue base. As Julia noted in Q2 in UCAN, we saw strong growth outside our largest retailers across mid-market, managed SMB and emerging verticals. And we've got ongoing ad platform improvements, notably, Pinterest Performance+ has been a key driver of this strength across those. So Performance+ gives advertisers an automated best practice setup across bidding, budgeting, targeting and creative. And so that's especially valuable for smaller advertisers that don't have large teams.
So we're also adding the controls that more sophisticated advertisers need so they can take advantage of these things as well. As we shared last quarter, approximately 30% of our lower funnel revenue was running through Performance+ campaigns as of Q1. Adopters also grew their lower funnel spend more than twice as fast as nonadopters, so we're really seeing that be effective for our advertisers.
And then I'd say more recently, the [ past our ad ] delivery models drove a 28% improvement in ROAS during testing for SMB advertisers using Performance+ with ROAS bidding. So these improvements continue to help smaller advertisers achieve better outcomes with less manual work. And as we look ahead, we continue to make our best performing automation the default for lower funnel campaigns, doing more and more of that while also improving bidding, creative and measurement and adding controls for more complex buyers.
So simpler campaign flow targeted for early next year, we'll put best practice set up in place from the very start. So we want to continue to move towards that kind of experience where we're giving really, really simple setup with best practices baked in. So as we've consistently said, this is a multiyear product and customer adoption cycle. And part of that is managing customers through not only their adoption, but how they think about leveraging these tools. But we continue to release new functionality every quarter, and we see good adoption happening across our user base.
And other platforms that have deployed AI-driven automation suites saw adoption play out over several years. In fact, even some of the earliest to have done this are still working through their adoption cycle. And we expect a similar dynamic for ours as well, where we've created a lot of capability, but there's a lot more in front of us than behind us.
And then lastly, just on the go-to-market aspect of this, we're also evolving how we go to market for mid-market and SMB advertisers. We talked about how we're restructuring account coverage, realigning incentives so we can provide direct support where can unlock growth and scale support where that is a better fit. And so broadening our revenue base, including internationally, it's a multiyear journey, and we're still relatively early. But we're building the product foundation, coverage model and go-to-market discipline required to serve a much broader range of advertisers. And again, we believe there's significantly more opportunity ahead of us.
Your next question comes from the line of Nitin Bansal with Bank of America.
Julia, can you provide some color on the increase in SBC expense this quarter? And as we continue -- as you continue to invest in EA talent, how should we think about the trajectory of SBC for the second half and next year?
Sure. So we don't guide stock-based compensation expense specifically, but it's certainly an area we're focused on. Q2 had some unique factors, and as a result, should be the highest quarter for stock-based comp expense in 2026. The increase in Q2 stock-based compensation expense was driven by the annual equity grant cycle for our employees and the lower stock price at the time of grant, which meant we needed to issue more RSUs to remain competitive on compensation. Equity is an important part of how we attract and retain our strong talent while also aligning employees with long-term shareholder value.
We also saw some timing impact in Q2 as a greater portion of our annual grant expense was recognized this quarter. While stock-based comp will remain elevated in 2026, starting in Q3, we do expect both stock-based compensation expense dollars and the year-over-year growth in stock-based compensation to step down versus Q2. As in recent years, we also expect to be profitable on a full year GAAP net income basis.
I'll also note that we've leaned in opportunistically to manage dilution, particularly this year at a moment of dislocation in our stock price. We've repurchased over $2 billion of stock at an average price of $18 per share. As a result, net dilution for Q2 was down 12% year-over-year, leading to growth in Q2 non-GAAP EPS of 30%. And we have a growing, highly profitable and cash-generative business, and we'll continue to be thoughtful in balancing employee retention and incentive alignment with opportunistic capital return and ongoing dilution management going forward, just as we've done in the past.
Your next question comes from the line of Jason Helfstein with Oppenheimer.
So first question for Bill. You touched on the capabilities of open source AI models. Maybe, how does PINS leverage that today? And how does that fit into your broader AI strategy?
And then second, just Julia, a quick one. Is MAU really the best KPI for UCAN? Or is there another metric that you could share with us over time to help us better understand what's going on in the business around engagement banks?
Thanks for the question, Jason. So on open source, it's -- open source AI, it's an area that we're really, really excited about. I've been talking with you all about this since right after the DeepSeek moment, about 1.5 years or so ago. And as we've discussed before, we take a model-agnostic approach. We use the right model for the task, whether that's one of our in-house compact fit-for-purpose models, an open source model that's post-trained on our own data, or in some very limited cases, a selected closed third-party model.
But we're one of the largest practitioners of applied AI at scale at over 640 million users. And we've been at the forefront of leveraging open source. It's become an increasingly important part of our strategy because it gives us 3 important advantages: cost, customization and control.
So starting with costs. For our use cases with open models, we're achieving cost per transaction at less than 8% of the cost of comparable closed proprietary models. And that's a substantial advantage. And it becomes even more compelling as open source models, including those from U.S.-based labs, continue to improve.
Our early adoption of open source has enabled us to scale AI efficiently to serve our 640 million users while also expanding margins and generating significant free cash flow. But it's the combination of those, our in-house compact models and leveraging open source really effectively. And I would also just say with the open source, not only at much lower cost, the fact that we can post train on our own data makes it more effective.
So as you're looking at what's happening in the open source ecosystem, those models continue to get better and better. It's not just how they do on the benchmarks. It's how are they going to work in your own environment. And when you can post train on your own data, that makes them much more effective. So then you're looking at something that is more effective than what you get from the closed models and at less than 1/10 of the cost. That really makes it so that at this point, any CEO that's not taking advantage of open source model is almost certainly wasting a lot of their shareholders' money.
And especially, that's true now that you have hyperscalers making it really easy to take advantage of that open source in their secure environment so that you can leverage the open source in your own cloud environment, so that it's safe, it's secure. You don't have to worry that it's phoning home. And as others have called out, you don't have to worry that you're giving your company's most important data over to somebody that's going to potentially use it against you.
So again, we're very, very excited about the progress in open source. That pairs with our own work on our own compact models that serve our use cases. But we're quite encouraged by what we're seeing in the advancement of the ecosystem there. And I think there's going to be a lot more of that to come. And it's, I think, a great democratizing agent. Most of Silicon Valley, most of the web, most of the mobile was built on top of open source software. U.S. [ tech ] needs a thriving open source ecosystem. And I think with the hyperscaler showing up, with U.S. lab showing up, we're getting exactly that. And again, we've been one of the largest practitioners of it, but we think it's a really great thing for the industry.
And then maybe just to take the second part of the question on UCAN and MAUs and engagement. I'd say we always internally look at sort of various baskets of metrics to measure engagement across the platform. We continue to see -- we're adding new users, and we're continuing to maintain strong engagement with those users that we're adding.
So for example, in UCAN, for instance, searches and boards created continued to grow faster than users in Q2. But I'd say just sort of across the platform as we're looking at strength overall, where we're seeing across a number of those basket of metrics, strength that gives us confidence that we're really resonating with users in UCAN, and in particular with Gen Z.
Your next question comes from the line of Eric Sheridan with Goldman Sachs.
Julia, maybe building on some of the commentary you've given so far with respect to EBITDA margins and given the performance of EBITDA in the quarter. Maybe just put a finer point on two questions. One, how are you thinking about what the highest return areas are for incremental growth investments when you look out over the next couple of years?
And when you think about flexing the EBITDA margin beyond 2026, how do you think about the scope for both headcount reductions, productivity gains and/or increased growth investments in the ad platform as different variables that could play into how margin evolves going forward?
Sure. Thanks, Eric. I'd say, in general, we're internally just becoming ever more AI native company over time, and we're continuing to move further in that direction. AI is embedded now in how we build every single product, operate the business and allocate resources internally.
So the restructuring actions we took in Q1 were really about aligning the organization with our highest priority opportunities and creating capacity to invest in the areas where we see the greatest potential returns, including AI. And so you're seeing that reflected in how we're rebalancing our cost structure a bit in 2026, where we're directing more investment capacity towards GPUs and internal AI tools while being thoughtful and disciplined about where we add headcount.
Reported headcount was up 3% year-over-year in Q2, which includes employees who joined Pinterest through the tvScientific acquisition. So if you exclude that acquisition, headcount was down year-over-year in Q2 and is down 6% since the end of 2025. So to be clear, we'll continue to invest in specialized talent where we see a clear and compelling ROI, but an ongoing focus for us is finding the right mix of talent, infrastructure and AI-enabled productivity to produce durable growth and expand margins over time.
So for 2026, as I noted in my prepared remarks, we are increasing our full year 2026 [indiscernible] for EBITDA margin to 30%, given the strong performance, [ pick in ] revenue that we saw in the first half that's up from 29% that we had noted previously. And as we look forward to 2027 and beyond, I think it's still too early to talk through specifics, but I will reiterate sort of my prior commentary on the appropriate sort of near- to medium-term margins for the business that's sort of consistent with the long-term range we gave at Investor Day a few years ago, 30% to 34%. We still feel like those are the right ones to be tracking, but no specific commentary yet on '27.
Your next question comes from the line of Michael Morris with Guggenheim Securities.
I wanted to follow up on the Pinterest Assistant comments and hoping you can expand a bit more on the path to monetization of the product. I understand how it further strengthens the user experience. It's very clear, but are all the pieces in place from advertisers to be on that monetization journey? Or do you need more there?
And if I could ask one more on the -- just a follow-up on the comments on the deceleration in non-U.S. international growth that's driven by decisions that have been made by the new leadership team. Can you expand a little bit on what's changing in that go-to-market and when we will see the sort of fruit of that labor?
Yes. So on the monetization for our Assistant, one of the things I talked about on the call is that we've actually woven it throughout our existing app. And so that means it has monetization built in right from start. So we don't think of this as a build it now and then layer monetize type of thing with our Assistant capabilities that are woven throughout the app. It's woven throughout the app right alongside of the monetization that is already baked in there.
And I would just say, as you look at our journey over the last few years as we made Pinterest, an AI-driven shopping assistant, you've seen us do that while having a pretty consistent margin expansion through that time, which has been twofold, has been one, about us using AI for highly commercial moments where monetization again is sort of baked in right from the start, as well as all the cost efficiency that we've talked about with compact models and using open source or open [ weight ] models. So those are the things that we've been doing to make sure that we've got not only the monetization, but the margin profile that we want from leveraging AI. And so that's exactly what we've been doing for the last several years in the background, now to bring to the foreground the same type of approach that is sort of woven right in right with the monetization there.
And of course, there's always things that we'll do to keep adding to that. We've talked about like our Business Assistant for advertisers, things like that, where we're bringing more assisted capabilities to advertisers, all those things that will continue to enhance that. But we think about monetization from the beginning of our product design.
And then on the second point, in terms of the go-to-market changes the monetization there. So these -- we expect -- we talked about these last quarter. It tends to take -- going to be a multi-quarter journey on these things. But the thing I'd point you to is we had work to do in UCAN as well. And when you look at the reacceleration of UCAN, the things that we did to reaccelerate in UCAN particularly around our go-to-market and sales approach, you saw those reflected in Q2. And that's what we're deploying, those similar strategies we're deploying internationally.
So while it can take a little bit of time to take hold, you're already seeing that happen for us in UCAN, and that's what gives us really good confidence on that for Europe. And while there's still a little bit more of that for us to do and it can be a multi-quarter journey, we feel quite confident in the approach. I don't know, Julia, is there anything you want to add to that?
Yes. I think that's spot on. I think just to add a little more color, our new Head of International Sales is in place now, focused on improving kind of market prioritization and coverage, deepening senior relationships with advertisers and agencies in the region and bringing just greater consistency overall to measurement and cross-functional support across regions. We're also testing the expansion of third-party demand into Europe as we work to broaden demand. So just a little bit more color there. And again, as Bill said, I think seeing nice results here from the UCAN playbook and looking to extend those to international over time.
Our last question comes from the line of Shweta Khajuria with Wolfe Research.
I have one on engagement. What is -- specifically what is driving engagement strength? It's continued to remain strong, particularly among Gen Z. And I guess, what gives you confidence in these trends being durable?
Yes. Thanks for the question. On the durability of these trends is 12 straight quarters of record high users. And through all 12 of those quarters, it's been the same things that we've been talking about in terms of really making Pinterest a highly shoppable platform with great personalization and with AI powering great recommendations. But not the AI alone, it's the AI powered on human taste and curation, that unique signal that we get.
Stated very simply, the AI by itself doesn't have style or taste. People have style and taste. The 640 million people come to our platform really create a flywheel effect that we get really unique signal that we can train our AI or post train open models on that then let us give better and better results to users. And as I mentioned in my prepared remarks, we see that flywheel continuing to accelerate. And when we think about how differentiated that is, I shared this on prior calls, that when we look at our latest multimodal models and the relevancy of the shopping recommendations we make. We talked about how we saw those outperforming closed models by 30 full percentage points on the relevancy of shopping recommendations. Not anything that it could do on the relevancy of shopping recommendations.
So those are things that give us confidence in the durability, but I'd also just point to what's been happening over the last 3 years, where we're several years into AI chatbots. Gen Z is more than half our platform, our largest, fastest-growing demographic. They have all almost certainly used chatbots, and they see something different from Pinterest.
And with Pinterest, it's not only the visual-first nature. It's how we are bringing that human taste and curation and which is completely unique to our platform and that we don't see happening any place else in the Western world. So there's a lot more for us to do to make that better and better. But we see that with Gen Z. They absolutely are thinking of it that way.
And you see that not just in our user growth and engagement. You see it in third-party research as well. We've previously cited, Adobe did a study, independent of us, that 39% of Gen Z now thinks that Pinterest as a first place to go search. And the reason for that is more than 70% of Gen Z sees Pinterest as more personalized. So I think those are places where you can look and see that flywheel really taking effect. And as models commoditize, which they clearly are with open source, we're able to take those capabilities, train on our total unique signal and give really great recommendations to users.
We've got great distribution to those users and have become really a beloved platform for those users, which is why, as Julia noted in some of her earlier comments, 85% plus of our users come to our mobile app directly. We're not dependent on others for that traffic. Pinterest is a destination that's beloved by its users. And I think that has proven out to be quite durable as well.
We have reached the end of the Q&A session. I will now turn the call back to Bill Ready for closing remarks.
Thanks again to all of you for joining the call and for your questions. We look forward to keeping this dialogue going, and we hope you all enjoy the rest of your day.
This concludes today's call. Thank you for attending. You may now disconnect.
Pinterest — Q2 2026 Earnings Call
Pinterest — Q2 2026 Earnings Call
Strong Q2: 640M users, revenue $1.18B (+18% YoY), improved margins as AI boosts personalization and ad performance.
📊 Quarter at a Glance
- Revenue: $1.180B (+18% YoY; +17% constant currency)
- Users: 640M MAUs (+11% YoY); U.S. & Canada 106M (+4%)
- UCAN: $880M revenue (+18% YoY), led by retail and conversion objectives
- Profitability: Adjusted EBITDA $311M (26% margin, +130 bps YoY)
- Cash/FCF: $270M free cash flow in Q2; $1.3B cash and equivalents; $58M repurchases in Q2; YTD >$2B repurchased
🎯 What Management Says
- AI-first product: Pinterest positioned as an AI-powered visual shopping assistant; "Taste Graph" (human curation signal) plus GPU-backed models drive personalization and the Pinterest Assistant conversational layer.
- Ad platform: Monetization via Pinterest Performance+ automation, Smart Assembly creative tool, and improved bidding/measurement to raise ROAS and scale advertiser spend.
- Go-to-market: UCAN playbook reaccelerated revenue; management is applying similar sales and structure changes internationally but expects a multi-quarter rollout.
🔭 Outlook & Guidance
- Q3 revenue: $1.190B–$1.210B (13%–15% YoY)
- Q3 EBITDA: $335M–$355M
- Full year: Now targeting ~30% adjusted EBITDA margin (vs ~29% prior)
- Headwinds: FX a modest ~1-point drag on Q3, Prime Day timing ~‑0.5 pt, Q2 World Cup benefit (~1 pt) not repeating; cost pressures from GPU capacity and tvScientific inclusion noted.
❓ Analyst Q&A
- Regional mix: Europe and Rest of World moderated due to tougher comps, go-to-market restructuring and some Asia cross-border/regulatory impacts; UCAN strength driven by retailer spend and platform improvements.
- AI & costs: Assistant is embedded in-app (monetization built in); open-source models plus compact in-house models cut per-transaction cost to <8% of closed models; GPU investments tracked for quick ROI.
- Measurement pilots: Early pilots integrating advertisers' first-party measurement with AI bidding improved performance and are expanding to more advertisers in Q3.
⚡ Bottom Line
Pinterest delivered strong user and revenue momentum with improving margins as AI enhances relevance and ad performance; near-term upside hinges on wider Performance+ adoption, successful scaling of measurement-integrated bidding, and international go-to-market execution while managing AI compute and stock‑based comp dynamics.
Pinterest — Q1 2026 Earnings Call
1. Management Discussion
Hello, everyone. Thank you for joining us, and welcome to Pinterest First Quarter 2026 Earnings Conference Call. [Operator Instructions] I will now hand the conference over to Andrew Somberg, Vice President of Investor Relations and Treasury. Please go ahead.
Thanks, Andrew. Good afternoon, and thank you for joining our first quarter 2026 earnings call.
Welcome to Pinterest's earnings call for the first quarter ended March 31, 2026. Joining me on today's call are Bill Ready, Pinterest's CEO; and Julia Donnelly, our CFO. The statement we make on this call reflect management's view as of today and will include forward-looking statements. Such statements involve a number of assumptions, risks and uncertainties, and actual results may differ materially.
We disclaim any obligation to update these statements. For information about assumptions, risks, uncertainties and other factors that could affect our results, please refer to our earnings press releases and the periodic reports we file with the SEC and available on our Investor Relations website at investor.pinterest.com.
During this call, we will present both GAAP and non-GAAP financial measures. A reconciliation of non-GAAP to GAAP measures is included in today's earnings press release and presentation, which are distributed and available to the public through our Investor Relations website. Lastly, all growth rates discussed today are on a year-over-year basis unless otherwise specified.
And now I'll turn the call over to Bill.
Thanks, Andrew. Good afternoon, and thank you for joining our first quarter 2026 earnings call. We entered 2026 focused on delivering the next phase of growth at Pinterest, and our stronger-than-expected first quarter results reflect our early progress. We delivered more than $1 billion in revenue, up 18% year-over-year and grew adjusted EBITDA to more than $207 million.
Pinterest is a destination where our 631 million monthly active users, all of whom are logged in, come to discover what they want and go do it in the real world. That experience is powered by one of the largest image corpuses in the Western world and a powerful proprietary data set. Together, they allow us to solve a problem that text-based general-purpose search was never built for. It's the classic, I'll know it when I see a problem. When a user knows what they want, but cannot quite describe it, an image can do what text cannot. That is where our AI and proprietary taste graph come in.
By understanding not just what a user is searching for today, but who they are and how their interests are evolving, we have made Pinterest a highly personalized AI-powered shopping assistant. The result is more than 80 billion monthly searches on our platform, approximately half of which are commercial in nature and a platform that continues to distinguish itself as both a destination for users and a vital partner for advertisers. That said, we remain clear-eyed about where we are in this journey.
Users are growing and engagement continues to deepen globally and in UCAN, our highest engagement region. Improvements to shopping and actionability are at the heart of those trends. We have also built an ads platform that is delivering performance for advertisers, but we still have more work to do to ensure monetization more fully reflects the strength of that user activity. Our priorities remain clear.
First, continue building a differentiated visual search, discovery and shopping experience to drive sustained momentum with users. Second, keep AI at the core of everything we do from powering our user experiences and ad platform to optimizing our internal operations. And third, accelerate monetization through improved go-to-market and measurement capabilities.
So, our revenue more fully reflects the strength of our engagement. With that context, let me turn to how AI is driving user growth and engagement. 10 straight quarters of double-digit user growth are the direct result of multiyear investments in AI, improving personalization and curation within visual search and discovery. At the center of this is our taste graph, which captures visual intent and curation signal built on hundreds of billions of user interactions over a decade.
Every search, click and save gives our AI more signal about who a user is and what they care about, which allows us to deliver more relevant and personalized experiences across the platform. Higher relevance drives deeper engagement, deeper engagement increases retention and stronger retention brings users back with higher intent.
Powering this flywheel is our deliberate approach to AI at Pinterest. We pair a world-class engineering team with the unique signal from our taste graph to build the models that deliver the best results for our specific use cases. In some cases, that means fit-for-purpose proprietary models that outperform leading third-party alternatives. In others, it means post-training suitable open source models in our own environment within our cloud infrastructure that deliver comparable outcomes to third-party models, but at a fraction of the cost.
Deploying these and other models across our platform have led to meaningful gains in user experience and advertiser performance over the last several years. And with ongoing model improvements, we see significant opportunity ahead to extend these models to more surfaces over time. An example of this is PinRec, our proprietary generative retrieval system, which is trained on user activity and our taste graph.
Rather than building separate models optimized for each surface, PinRec is now a single model that generates personalized results for each user across all surfaces simultaneously, informed by the full depth of what we know about their taste and interest. We initially launched this model on search and related surfaces in 2025 and subsequently extended it in Q1 to serve content globally sitewide.
This launch improved search fulfillment by approximately 180 basis points. It also drove a roughly 180 basis point reduction in CPA and CPC for advertisers. On our search surfaces, where over 72% of our impressions occur today across both visual and text-based searches, we continue to see searches grow as we improve the experience.
In Q1, we updated our proprietary search ranking model, extending user context windows within search by 30-fold, similar to the expansion we previously made to our home feed ranking model. We now use up to 16,000 user actions over a 2-year period to inform the search results shown to each user. This launch improved search fulfillment by approximately 70 basis points and saves by approximately 390 basis points.
Our AI capabilities also extend into creative generation with Canvas, our in-house AI image generation model trained exclusively on Pinterest data. Canvas allows us to build experiences that reflect the high bar for visual quality and aesthetics that users and advertisers expect from Pinterest, while operating at an order of magnitude lower cost than leading third-party models.
It already supports Pinterest Performance+ creative optimization, enabling advertisers to dynamically edit backgrounds and transform basic catalog images into high-performing lifestyle images. With the newest version of the model now supporting real-time high-fidelity image editing, particularly in key verticals, we expect to expand Canvas to enable more creative experiences for users and advertisers in the months ahead.
Our AI investments are also translating into better advertiser performance as Pinterest Performance+, our AI-powered performance ad suite, continues to drive strong results for advertisers. In particular, we are focused on driving adoption of Pinterest Performance+, our automated bundle of bidding, budgeting, targeting and creative features that reduces CPAs and CPCs while requiring half as many inputs to set up as a standard campaign.
As we have said in the past, Pinterest Performance+ will be a multiyear customer adoption and product cycle. Just over a year-end, approximately 30% of lower funnel revenue is now running through Pinterest Performance+ campaigns, but we are still early in capturing the full opportunity as adoption continues to expand and we continue to build out functionality of the suite.
Advertisers using Pinterest Performance+ campaigns continue to see higher ROAS and improvements in CPA and CPC compared with business-as-usual campaigns. And importantly, in Q1, adopters of Pinterest Performance+ campaigns grew their lower funnel spend nearly twice the rate of non-adopters. We are now making it easier for advertisers to validate that performance using the metrics they value most.
In Q1, we launched a native A/B testing tool in beta directly in Ads Manager, allowing advertisers to run structured KPI-driven tests comparing Pinterest Performance+ campaigns to their existing ones. And we are starting to see strong early results. For example, Mejuri a leading fine jewelry brand, ran a 4-week A/B test comparing a dedicated Pinterest Performance+ campaign to its business-as-usual approach.
The Pinterest Performance+ campaign delivered a 46% increase in ROAS and a 62% increase in conversions, which led Mejuri to adopt Pinterest Performance+ campaigns more broadly. We are also continuously upgrading our core ads models. In Q1, we unified and retrained our shopping ROAS models to better predict and optimize for advertiser return on ad spend across multiple stages of our ad stack.
In experimentation, these improvements drove ROAS gains of up to 11% and are an indication of what continued investment in our ads platform can unlock. As our ads platform gets better at driving outcomes, the next priority is ensuring advertisers can fully see and attribute the value we are generating for them. That means capturing more of the actions Pinterest drives and connecting that data more directly to the measurement tools and bidding systems advertisers use to evaluate and optimize their spend.
For our largest and most sophisticated advertisers, we are continuing to pilot integrations with their proprietary in-house measurement systems, which enables our bidding systems to respond dynamically to their specific definition of a successful outcome, whether that is customer lifetime value, profit per order or something else entirely.
In early testing with one advertiser that prioritizes lifetime value, the advertiser cited a 15% to 20% improvement in lifetime value ROAS. These and other bidding optimizations helped drive stronger performance in Q1, and we were encouraged to see some advertisers lean in further over the course of the quarter. We plan to expand this pilot to additional large sophisticated advertisers later this year.
We also expect to deepen integrations with key third-party measurement partners later this year, giving a broader set of advertisers both the attribution clarity to see what Pinterest is driving and the bidding tools to act on those insights at scale. Whether an advertiser uses a first-party measurement system or a third-party partner, our goal is the same, to help them better understand the full value Pinterest is driving while also helping us optimize our AI bidding systems toward the outcomes that matter most to them.
And as we deepen our performance and measurement capabilities on Pinterest, we are also extending that performance to the biggest screen in the home through our acquisition of tvScientific, which closed in Q1. With tvScientific, we're unlocking the ability to extend Pinterest's unique consumer intent signal and audiences beyond our owned and operated properties to power high-performing CTV campaigns. We have already begun integrating Pinterest audiences and signals with tvScientific's algorithms via tvScientific's buying platform.
The early results are encouraging. One early partner, a leading home furnishings omnichannel retailer, saw a nearly 190% increase in incremental audience reach and a 159% increase in incremental sales after leveraging Pinterest audience data in its CTV campaigns. These are early days, but they demonstrate what becomes possible when Pinterest's deep understanding of consumer intent meets the scale and reach of connected TV.
Over time, we expect to integrate TV scientific capabilities directly into Pinterest Performance+, turning Pinterest into a full funnel search, social and CTV performance solution that should open larger and incremental budget pools. As part of our efforts to accelerate the monetization of our platform, I will now turn to how we are strengthening our global sales and go-to-market organization.
Since joining as our Chief Business Officer earlier this year, Lee Brown has been focused on making our monetization motion more durable and scalable, so we are better positioned to capture the opportunity ahead. He is moving with urgency and has already begun making key changes, particularly in leadership across parts of our international and go-to-market organizations and how we drive accountability across the sales force and an accelerating adoption of internal AI tooling.
For example, we have sharpened our coverage model to position sellers closer to the clients they serve with higher expectations for how they engage, and we are evolving our sales incentive structures to drive more accountability and give a sharper insight into execution across the organization. We are also incorporating internal AI adoption and advertiser conversion signal quality into how we measure performance.
Our performance and measurement sales specialists, the technical sales teams supporting performance and measurement solutions will soon have product activation and customer engagement targets. And we have rolled out a globally consistent merchant playbook, giving our teams a standardized, scalable way to bring Pinterest best practices to market across every region.
Looking forward, our ongoing go-to-market work is organized around 3 broader themes. First, broadening our revenue base. During our last earnings call, I noted that we were seeing pressure from our largest retail advertisers. While it was encouraging to see that dynamic improve in Q1 relative to our expectations, as Julia will describe a bit later, our conviction around broadening our revenue base has not changed. We continue to see meaningful upside over time by expanding our footprint across mid-market, enterprise, managed SMB and international advertisers.
Second, increasing the consistency of our global go-to-market execution. We have evolved from a primarily upper funnel sales force into a more full funnel and performance organization. The changes I just described are designed to translate that more reliably into advertiser outcomes and revenue at scale.
Third, strengthening our measurement foundation. As measurement becomes an increasingly important part of performance selling, we are leveling up our technical expertise to ensure advertisers adopt our measurement solutions and can better understand the full value we are driving. As we said last quarter, some of these changes will take a couple of quarters to fully play through and progress may not be perfectly linear, but we believe these changes are critical to broaden our revenue base and position us to execute more consistently against the large opportunity ahead.
Ultimately, the reason we have conviction in this work is because Pinterest is doing something different, and that difference matters. What sets Pinterest apart is not just that we help people discover ideas. We help them act on those ideas in the real world. Consider a homeowner renovating their garage who knows they want their space to feel more functional, but may not know where to start.
On Pinterest, they can start with garage organization ideas, visually explore different layouts and styles, identify solutions like peg boards or modular storage and ultimately find and shop the products that bring that vision to life. The same is true for a parent planning a child's first birthday party or a Gen Z user designing a manifestation board.
In each case, Pinterest helps turn inspiration into action. That reflects the kind of experience we have been building for years. We have long focused on creating a more positive platform, one centered on time well spent, not just time spent. That foundation is becoming even more relevant as the broader online ecosystem faces increasing scrutiny around youth mental health, well-being and online safety.
We were the first major online platform to make accounts for users under 16 private only. We have also supported efforts like phone-free schools and App Store age verification while applying AI in ways that prioritize positivity. Our new brand campaign brings that differentiation to life for consumers. Launched earlier this month in the U.S. and U.K., the campaign marks a meaningful step up in how we are showing up in the market. It reaches Gen Z and millennial audiences across television, streaming, cinema, out-of-home and digital channels through the end of the year. The message is simple and true to Pinterest. The best thing you can find online is a reason to live your life offline.
In closing, as AI reshapes how people discover, plan and shop, Pinterest is in a differentiated position. Our taste graph and rich curation signal give us a data foundation that is hard to replicate. We are pairing that foundation with product, measurement and go-to-market improvements to better translate that deep engagement into more durable growth over time.
And importantly, we're doing that in a way that stays true to what makes Pinterest distinct, helping people discover what they want and then go do it in the real world. I'm proud of our team's execution this quarter and excited about the work ahead.
With that, I'll turn the call over to Julia to share more details about our financial performance.
Thanks, Bill, and good afternoon, everyone. Today, I'll be discussing our first quarter 2026 financial results and provide an update on our second quarter 2026 outlook. All financial metrics, except for revenue, will be discussed in non-GAAP terms unless otherwise specified, and all comparisons will be discussed on a year-over-year basis unless otherwise noted.
Q1 was a strong quarter. We delivered over $1 billion in revenue for the third consecutive quarter, growing 18% year-over-year and above the high end of our guidance range. Stepping back, we remain in the early stages of fully monetizing the engagement and commercial intent on our platform. As Bill discussed, improving the consistency of our go-to-market execution and strengthening our measurement foundation are central to that opportunity.
While these changes will take time to fully play out, we believe the progress we are making across the business and the outcomes from our AI investments will lead to durable growth over time. Year-to-date through today, we repurchased roughly $2 billion of stock or 109 million shares at a weighted average price of approximately $18, reflecting our confidence in the long-term value of the business.
Funded with $1 billion convertible note and cash on hand, this $2 billion stock repurchase has resulted in an approximately 16% reduction in our shares outstanding versus a quarter ago. We now have $2 billion remaining on our new Board-authorized $3.5 billion share repurchase program. We believe these actions reflect both the strength of our business as well as our significant opportunity ahead.
Now I'll turn to more specifics about our first quarter results. We ended the quarter with 631 million global monthly active users, or MAUs, growing 11% and reaching another record high. We continue to demonstrate user growth across all of our geographic regions. In Q1, our U.S. and Canada region had 106 million MAUs growing 4%. Our Europe region had 159 million MAUs, growing 7%.
And in the Rest of World markets, we had 367 million MAUs growing 15%. Shifting to revenue. In Q1, our global revenue was $1.008 billion, up 18% or 15% on a constant currency basis. We saw strength from our conversion and to a lesser extent, our consideration objective. Across verticals, growth was driven by retail, though with puts and takes as well as smaller but faster-growing categories on our platform, including financial services.
As we previewed on the last earnings call, we saw a continued headwind from our largest retailers in Q1. However, AI-driven ad platform improvements, including bidding optimizations for this group, partially offset some of this headwind later in the quarter. Revenue growth, excluding these large retailers, accelerated in Q1 relative to Q4, underscoring the progress we're making to diversify our revenue base.
Turning to our geographical breakouts for Q1. In the U.S. and Canada, we generated $750 million in revenue, growing 13%. Strength came from retail and emerging verticals, including financial services. In Europe, revenue was $186 million, growing 27% on a reported basis or 16% on a constant currency basis. Growth in Europe was driven by retail. Revenue from Rest of World was $72 million, growing 59% on a reported basis or 50% on a constant currency basis.
In Q1, overall ad impressions grew 24%, while ad pricing declined 5% year-over-year. The deceleration in ad impression growth versus recent quarters was primarily driven by lapping the initial ramp of monetization in previously undermonetized markets, including from resellers in Rest of World, which had contributed to outsized impression growth the prior year.
On pricing, the sequential improvement versus recent quarters was driven primarily by a higher relative mix of UCAN ad impressions, which carry higher average pricing overall due to the lower growth of international ad impressions I just mentioned as well as stronger UCAN ad demand.
Moving to expenses. In Q1, cost of revenue was $232 million, up 20% year-over-year and up 5% versus Q4, driven by increased infrastructure spend related to our user and engagement growth. Our non-GAAP operating expense was $574 million, up 16%. The increase was primarily driven by sales and marketing due to headcount investments and marketing expenses as well as R&D to support our AI and product initiatives.
In Q1, we delivered $207 million in adjusted EBITDA above our guidance range with an adjusted EBITDA margin of 20%, up 40 basis points versus Q1 last year. The higher-than-expected adjusted EBITDA was driven by flow-through from higher revenue as well as a reversal from Canada digital services tax following its repeal. We also delivered Q1 free cash flow of $312 million. Consistent with prior years, Q1 is seasonally our strongest quarter of free cash flow conversion due to higher Q1 collections following Q4 peak revenue. We ended the quarter with cash, cash equivalents and marketable securities of $1.3 billion.
Now I'll discuss our guidance for the second quarter. We expect Q2 revenue to be in the range of $1.133 billion to $1.153 billion, representing 14% to 16% growth year-over-year. Based on current spot rates, our guidance assumes the impact of foreign exchange will be approximately 1 point of tailwind. For Q2, we expect adjusted EBITDA to be in the range of $256 million to $276 million. We anticipate Q2 2026 non-GAAP cost of revenue to grow sequentially from Q1 2026 by mid-single digits percent, partially driven by the full quarter impact from tvScientific and our investment in GPU capacity.
In Q2, our primary area of year-over-year investment within non-GAAP operating expense will continue to be investing in sales and marketing, including in our brand campaign as well as sales headcount. As a reminder, sales and marketing trends tend to be seasonally higher in Q2 than in Q1 due to the timing of certain marketing expenses within the year.
Within R&D, we are continuing to invest in headcount to support our AI and product initiatives. As we're still early in the year, our full year margin outlook is largely unchanged from what we shared last quarter, so I will keep these reminders brief. Starting with cost of revenue. As with Q2, we continue to expect modest headwinds from cost of revenue as a percentage of revenue in 2026 as a result of the investments in areas such as additional GPU capacity as well as the impact from the inclusion of tvScientific.
Importantly, we are already starting to see strong yield from our GPU capacity investments, including the engagement and performance improvements that Bill mentioned earlier. For adjusted EBITDA, we continue to expect full year 2026 margins to come in around 29%, including the approximately 100 basis point drag from tvScientific that we called out previously. We expect adjusted EBITDA margin pressure to moderate in the second half compared to the Q2 adjusted EBITDA margin implied by our guidance range.
In closing, our Q1 results reflect a strong start to the year and the underlying health and relevance of our platform. Our user base is growing. Our AI investments are producing measurable results for users and advertisers and the changes we're making to our go-to-market organization are the right ones for the business long term. Progress may not always be linear, but our direction is clear, and our conviction in our ability to return to our long-term targets and capture the large and growing opportunity ahead remains unchanged.
With that, I'll hand it over to Bill for some final words.
Thanks, Julia. I want to thank our teams at Pinterest, our advertising partners and all the people that come to Pinterest to find inspiration and take action. And with that, we can open up the call for questions.
[Operator Instructions] Your first question comes from the line of Doug Anmuth from JPMorgan Chase.
2. Question Answer
Can you talk more about the drivers of upside in 1Q across the core business, tvScientific and FX and also how you're thinking about 2Q? And do you expect to maintain revenue growth in the mid-teens on an FX-neutral basis in the back half?
Sure. Thanks, Doug. So on Q1, the story of the strong Q1 is really 2 things. First is the continued broadening of our revenue base. And then second, better-than-expected performance from our largest retail advertisers as we continue to drive improvements to the ad platform. In Q1, revenue growth, excluding these large advertisers accelerated relative to Q4 as we continue to make progress diversifying our business across mid-market enterprise, managed SMB and international.
Overall, large retailers remained a headwind to growth, but AI-driven platform improvements, including bidding optimizations we delivered for these advertisers began to offset some of this headwind later in the quarter. We're seeing strong early results there, including our efforts to link our AI bidding systems directly to advertisers' measurement sources of truth, and we plan to scale that pilot to additional large advertisers later this year.
We don't intend to break out tvScientific's revenue contribution specifically going forward. But I will say for Q1, the tvScientific contribution was broadly in line with the updated guidance we gave in mid-February. And looking ahead to Q2, given the change in FX impact in Q2, our guidance for Q2 revenue growth is roughly consistent with Q1 on a constant currency basis. Maybe just to dive in a little bit into some of the color by region.
Starting with UCAN, where we generate roughly 75% of our revenue, we achieved double-digit growth in Q1 in UCAN, and we expect to repeat that in Q2. We're really encouraged by the stability we're seeing in that core market. We believe we're on the right trajectory there. International revenue is a smaller portion of our business, but there are a few factors which we expect to moderate international growth in Q2. We're making deliberate leadership and structural changes to our international go-to-market organization to best position for the long-term opportunity, including a new Head of International joining soon.
As we said last quarter, progress as we rebuild and retool the organization will not always be linear, but that modest disruption is playing out here in our international regions in Q2. And then as a reminder, in Q2, we're also lapping more difficult comparisons in Rest of World and Europe due to the ramping of resellers last year and elevated cross-border spend following the introduction of U.S. tariffs. We're still significantly undermonetized internationally relative to the strength of engagement and commercial intent we see on the platform.
So our long-term conviction in the opportunity in international is unchanged. And we think the changes that we're making now best position us to fully capture that opportunity over time. I think, to your last question on sort of outlook for the rest of the year, we don't guide beyond 1 quarter, of course. But stepping back, I think the plans that we laid out last quarter to return to our mid- to high teens long-term growth targets, they're proceeding well, and we're encouraged by the early progress here in the first half of the year. And the work that we're doing across the business is focused on returning us to consistent delivery of those targets over time.
Your next question comes from the line of Eric Sheridan from Goldman Sachs.
Maybe coming back, Bill, to some of your comments about the hiring of Lee into the role in the organization. Just want to go a little bit deeper in terms of his areas of focus. What signal investors should be taking in terms of what that means for your go-to-market strategy, not only in 2026, but longer term? And how should we be monitoring that in terms of what we'll see showing up in the business in the years ahead?
Thanks for the question, Eric. So first of all, at the platform level, it's really important to remember that today, our user engagement and commercial activity continues to outpace our monetization. So while we've made real progress building a full funnel performance ads platform, the significant opportunity to broaden our revenue base across performance, mid-market, SMB and international is still largely in front of us.
Over the last 3 years, we've gone from primarily selling upper funnel ads to large U.S. CPG and retailers a few years ago to selling full funnel performance solutions across more verticals, more advertiser segments and more geographies than ever before. And as those channels have expanded, they've also introduced a higher level of scale and complexity, and that's exactly what Lee is laser-focused on addressing.
So that scale and complexity, it's a great thing for our business, but clearly a different operating approach for us to go fully pursue that opportunity. So what he's focused on first is bringing more accountability, more consistency, more operational rigor and AI tooling to how we go to market. The through line across everything he's doing is making performance more visible and measurable and making sure we're executing with greater consistency across regions and teams.
Some of the near-term changes I mentioned in my prepared remarks are already underway, including leadership changes across parts of the international and go-to-market organization, accelerating adoption of internal AI tools and sharpening accountability across the sales force. We're also restructuring and reallocating resources so we can move faster in the parts of the market where we see the biggest opportunity, including mid-market, enterprise, SMB and international.
At the same time, we're doubling down on measurement and technical selling capabilities across the organization, and that includes increasing accountability for our technical sales teams by adding product activation and customer engagement targets to how we measure performance. As the industry has advanced on attribution, we know that we need to move faster, and that's an area we're very focused on improving.
So stepping back, I have high confidence in Lee and in the team, and we're already seeing good early progress. The focus now is on building a go-to-market organization that matches the strength of the product foundation that we've spent the last several years putting in place.
Your next question comes from the line of Ross Sandler from Barclays.
Great. Julia, you mentioned that the small and midsized accounts accelerated in the March quarter. Just curious what you're seeing both in that area and with the large accounts since kind of the conflict started and what the early read is on 2Q? And in particular, when do we expect the larger accounts to start to maybe pick up the pace a bit? Any thoughts there?
Yes. Happy to take that one. As we said, in Q1, the large retailers remained a headwind, but we did see some strength there later in the quarter, largely driven to ad platform and product improvements. And then outside of those large retailers, the rest of the business, right, which is all the areas we've been talking about in terms of driving growth in, that accelerated. The rest of the business accelerated in Q1 relative to Q4.
To your question sort of on macro and Middle East, I'd say broadly, the environment that we're seeing in the ad market is relatively consistent from last quarter. Those large retailers do continue to navigate some tariff-related margin pressure, though we're seeing some stability there. And we're continuing to focus on how we grow outside of that business, driven by a lot of the product and go-to-market changes that Bill was just talking about and that Lee is really focused on driving.
We are tracking the conflict in the Middle East, but I'd say the impact we are seeing so far from that conflict is small on a dollar basis based on what we now know. So we see it most directly in our Rest of World region and to a lesser extent, in Europe as well, where it's really isolated to certain verticals impacted by higher oil prices. But this has all been factored in as we thought about our Q2 guidance range.
Your next question comes from the line of Rich Greenfield from LightShed Partners. Rich Greenfield, if you could double check that your line is unmuted. Let's move on to our next question, which comes from the line of Colin Sebastian from Baird.
Maybe as a follow-up to Ross's question regarding the efforts to diversify the advertiser base, Performance+, now running at approximately 30% of lower funnel revenue. I guess what adoption trends are you seeing within the mid-market and SMB segments? And related to that, given that Performance+ adopters are growing their spend at, I think, twice the rate of nonadopters, how are you leveraging tools like Canvas and PinRec to lower those barriers for smaller advertisers?
Thanks for the question, Colin. So as I noted, we're really encouraged by the progress in Q1. Our business accelerated in the quarter, and that acceleration was driven by growth outside of our largest retailers. So the diversification we've talked about, we feel really good about the progress we're making there. On SMB, to be very clear, we're referring to advertisers with tens of millions to $100 million of GMV, not really the long tail of mom-and-pop advertisers.
It's also important to remember that Pinterest Performance+ only reached general availability approximately a year ago. For the first time, we have a product built to serve smaller advertisers that don't have the time, resources or expertise to manage campaigns across multiple platforms. And we're only about a year into that journey, which we expect to be a multiyear cycle, just as it was for the larger platforms when they deployed their AI-driven automation suites.
So early adoption is encouraging. The 30% of our lower funnel revenue that's now running through Performance+ campaigns, we feel good about that. But obviously, that's still early in the journey of capturing the full opportunity, both in terms of driving continued adoption because there's significant room to grow the adoption, but also because we continue to roll out meaningful performance improvements, a few of which I noted in the call, but we see much more opportunity for that to continue. And we're adding more functionality across bidding, targeting, creative and measurement over time.
And a lot of that on our in-house capabilities, our taste graph, things that we think we're really uniquely positioned to do and demonstrating that. I'd also mention that mid-market enterprise and international are also still relatively early opportunities for us. So we made a good start in both areas last year. And now we're focused on building the teams, processes and the go-to-market motions required to serve a much broader set of advertisers at scale. As I commented on a bit before, that takes a different level of operational rigor than serving a smaller group of large retailers, and that's exactly what Lee is focused on building there.
So we feel good about the early progress there. But we still have a lot more to go there, a lot more of that opportunity is in front of us. So we still very much believe that SMB, along with mid-market and international can become a meaningfully larger part of our business over time. And we have the product and tooling able to do that. We're building out the go-to-market to do that, but much more build still in front of us to fully capture that opportunity, but we're encouraged by the early progress. Hopefully, that helps.
Your next question comes from the line of Jason Helfstein from Oppenheimer.
I'll ask a high level then a quick margin question. How are you viewing the impact from AI chatbots with respect to the competitive landscape and emerging visual discovery? And just second, I know you're not guiding for next year, but is there any way to think about how we should be thinking about expenses for next year relative to what may be a higher level of investments this year after the headcount reduction?
Thanks for the question. So obviously, nobody can perfectly predict the future, but we're actually several years into a massive AI adoption cycle. And that means that we can really learn a lot from what people are already doing given we're several years into the AI adoption cycle. So I would start first -- in answering your question, I would start with what we can see and what our users are telling us through their actions already.
And it's important to note that at the same time, chatbots have grown in popularity over the last few years, we've put up 10 straight quarters of double-digit user growth and deepening engagement per user. Users, including Gen Z, they're engaging with chatbots and Pinterest at the same time, but for very different things. So of Pinterest's more than 80 billion monthly searches, half are commercial in nature, whereas ChatGPT's own data says that only 2% of their prompts are commercial.
You're seeing specialization versus generalization play out among the AI models on enterprise versus consumer. But consumer search has historically had significant generalization versus specialization split as well. And we believe we have clearly carved out a unique and specialized use case on visual search and shopping, again, as evidenced by the fact that many, if not most of our users have interacted with AI chatbots, but yet are deepening their engagement with Pinterest.
And that's really because the users come to Pinterest leaned in with intent. And Pinterest offers something that the other platforms aren't built to solve, which is visual search and discovery. We surface relevant personalized recommendations before the user even knows how to ask what they want. And we connect that to real products that they can act on. So we're solving the -- I'll know it when I see a problem, which is such a significant component of so many consumer shopping journeys.
And again, we're seeing this dynamic play out right now even amongst the largest players where it's clear that focus has been more successful than others who try to be all things to all people all at once. So Pinterest is a specialized platform, and that's a position of strength. It's very hard to be a text-based general-purpose search platform and simultaneously deliver the depth of visual discovery and taste-based personalization that Pinterest offers and specialization is where we believe we can win.
And in comparison, general purpose chatbot platforms start with a blank screen and a command line interface and the user has to know what the type, which is a meaningful barrier for discovery and planning use cases because often the user doesn't yet have the words for what they're looking for. And when these platforms generate an image, there's often no path to a real product, brand or purchase versus Pinterest on that -- on Pinterest, that same journey centers on shoppable content, product comparisons and real purchase paths, particularly in a primarily visual nature.
And on Agentic commerce more broadly, you've also seen meaningful strategic pivots from some of the platforms that were most aggressively pursuing that space. That validates our view that the barriers of progress in Agentic were likely not technical, but around user behavior and ecosystem incentives, and we've been clear about partnering with advertisers and not disintermediating their relationship with customers. So I hope that helps to give a little more color, and I'll give it to Julia on the second part of your question.
Yes. So I think it's obviously too early to talk about sort of 2027 margins specifically. However, I will reiterate what we said on the last call about the long-term targets of 30% to 34% adjusted EBITDA margin still being the right ones and still be the ones we're shooting for here in the medium term. Obviously, we laid out those targets at the very end of 2023. We made very quick and rapid progress towards those targets.
This year, we're aiming for 29%, partially because we're including tvScientific. But if you exclude that, we're basically flat year-over-year. But I still think those 30% to 34% targets are the right ones to be focused on, and we'll have more to say specifically on the exact trajectory for 2027 as we get later into this year.
Your next question comes from the line of Justin Patterson from KeyBanc.
Great. Bill, I wanted to touch on your deepening engagement points a little bit more. What do you see as the core levers to continue doing that? And given UCAN is a more established market, how much more runway do you have to drive further engagement growth here?
Thanks, Justin. While we don't comment on or validate third-party data, our user and engagement strength continues to be one of the real highlights of the transformation we've driven over the last few years. It's 11 straight quarters of record high users. And it's important to note that 100% of our reported users are logged in and 85% come directly to our mobile app, making Pinterest a clear destination app.
We've also had 10 straight quarters of double-digit user growth. As I mentioned before, we see it as having effectively turned Pinterest into an AI-powered shopping assistant that operates in a primarily visual manner, which is consistent with large portions of how people actually shop. In terms of how we're deepening the engagement, we're deepening engagement in the areas that matter most globally and in UCAN, searches and outbound clicks are both growing. And of our more than 80 billion monthly searches, half are commercial in nature, which is a much more significant skew toward commerciality than you'd see in general search elsewhere or in chatbots.
We've also talked about how we're winning with Gen Z, over 50% of our platform and our fastest-growing cohort with Gen Z. And not only are they coming to Pinterest to shop, but they also value our platform as a more private positive space committed to their well-being. Our intentional choices to prioritize safety and positivity are really resonating with Gen Z specifically as well as other generations that we track.
And we continue to see growth across generations, including with millennials. And I'd just say longer term, at the heart of our engagement strength is how we continue to leverage AI to drive better personalization and relevance. Our ongoing improvements to the platform, including the launches we highlighted this quarter across search ranking, content recommendations and creative generation are all pointing in the same direction, which is a more relevant and personalized experience that gives users more reasons to come back and anticipates what they're looking for next.
And all of that built off of our proprietary signals and that unique curation behavior, which I've talked about consistently since joining Pinterest, that curation behavior that occurs on Pinterest which we see as completely unique in the Western world, gives us a highly differentiated signal that we can use to train AI in ways that others without that signal can't. And that's why Gen Z who are obviously very familiar with chatbots are coming to Pinterest in larger and larger numbers and with increasing depth of engagement per user as they clearly get something very different from Pinterest than they get from chatbots.
One other thing I'd just add on user and engagement trends. I think it's just worth a quick reminder that Q2 is typically our seasonally softer period for quarter-to-quarter sequential user growth, particularly in Europe. We measure monthly active users on a 30-day look back from the last day of the quarter. So as we get into the summer months, users tend to travel and spend more time outside. So we often see a seasonal pattern there in Q2. But overall, as Bill said, we feel really great about where the user engagement trends for the business are heading right now.
Your next question comes from the line of Rich Greenfield from LightShed Partners. Your next question comes from the line of Ron Josey from Citibank.
Two, please. Bill, as part of your -- the sales reorg that we talked about, I believe you talked about having ad sales closer to clients. So I just wanted to talk to us a little bit more about how the sales force is now structured going forward. Are we talking more regional versus vertical? Any insights about go-to-market would be helpful.
And then teeing off on your latest comments there around Personal Assistant and shopping assistance gaining greater adoption. We're seeing consumers do that. But talk to us about how retailers are preparing for this going forward. And as you look out maybe 1 to 3 years and we hear about the personal assistance on Pin, how do you envision that future going forward?
All right. Thanks for the questions, Ron. So on the first one, on the sales reorg, we've had regional focus previously, really around like the segments that report versus UCAN, Europe, rest of world. And so we've had regional focus before. The most notable thing over the last few years, as I mentioned in my prepared remarks, is that a few years ago, we were primarily an upper funnel ads platform that really went to market with a smaller number of large CPG and retailers, both in the U.S. and in Europe and international.
And as we've built a broader set of user engagement that allows us to now engage with a much broader set of advertisers, there are different things required for a very large enterprise versus a mid-market advertiser versus an SMB. And we really just got the ad product that would let us start to go beyond those largest retailers into mid-market and SMB that really went GA approximately a year or so ago.
And so over 2025, we saw good early progress in that, but we also saw that we need to have more specific efforts around those different segments of advertisers. And we need to target our sales and go-to-market approaches differently for a mid-market or SMB than, say, the largest retailers, which is where more of the approach has been focused in the past as well as you can do more and more performance selling, you have more to do around that.
So it's not just about organizing around those customer segments within the regions, but also about more technical selling. We talked about measurement and the things we're doing around measurement and getting more technical sales capabilities around getting the right measurement implementation. As I mentioned, we've more than 5x the number of clicks we send to advertisers over roughly the last 3 years. But obviously, our monetization hasn't increased nearly at that rate, which means there's a lot more monetization or there's a lot more shopping activity that we're driving than what our monetization currently reflects.
And part of that is driving deeper measurement integrations to get credit for that. So that is part of the go-to-market motion and the technical selling capability is a really important addition. So those are some of the things in terms of just going a little bit deeper on the go-to-market there. And then the second part of your question on shopping assistance, and AI, like a few things I'd say, just we launched Pinterest Assistant in beta in Q4 of last year.
And as we continue to have strong user engagement trends, we're really being intentional in taking our time on getting the product market fit right with Pinterest Assistant and incorporating important learnings into our core user experience. I think you've seen some false starts from others in the space that they had to then sort of pare back. And we have such really great commerciality and great traffic that we're driving to advertisers.
We want to make sure we're doing this in a way that deepens the relationship between the user and the advertiser. So as we've been testing over the past couple of months, we've been able to really materially advance the capabilities of the underlying model, powering the Pinterest Assistant due to both advancements in the underlying open source model as well as our ability to post-train that model with our unique data and integrate it into our suite of in-house models that power that Assistant, and so as we bring that to market, we're actually growing our excitement about being able to solve more of the shopping journey, but in a way that more deeply connects the user to the advertiser.
Basically, for our brands and retailers, we want them to gain a customer, not just a transaction. And we've been really successful in doing that over the past few years. And we want to make sure we continue to do that with our assistant, and we're seeing good ability to do that, but more to come in terms of how we'll continue to ramp that over the coming months and quarters.
And then last thing I'd say on this point around the models that it's worth really just commenting a bit on what's happening with these models across the industry. The industry is converging on a conclusion that we reached here at Pinterest relatively early on. The unit economics are relying on large proprietary third-party LLMs does not make sense or may not make sense for many use cases as companies end up paying a significant premium for what might be an overengineered generalized capability that's not necessarily optimized for company-specific problems.
So it's becoming increasingly clear that the narrative that you have to rely on only one of the largest proprietary models to get significant benefits from AI isn't really holding up. Our approach has been deliberate from the start. We build compact fit-for-purpose models trained on our proprietary data for our most unique and core use cases such as visual understanding. And we've seen these consistently produce better results at far lower cost for the majority of what our product does.
And for the more generalized LLM capabilities, we use suitable open source models running in our own cloud environment within our cloud infrastructure, when they're the right tool, and then we post train them on our own proprietary data, and that has multiple advantages. Since it runs in our environment, it's more secure. It has much lower latency. Since it's been able to be trained on our unique data, it delivers better performance than off-the-shelf proprietary models, and it's a fraction of the cost.
And that's all enabled by the unique feedback loop that we get from the curation on our platform. So Pinterest data set is fundamentally different from what these other third-party models have been trained on.
And so as we think about advancing our assistant, taking that combination of our fit-for-purpose in-house models have been so great at visual understanding and driving commerciality and driving great recommendations pairing that with some basic LLM capabilities, but then post-training that in the places that can be helpful to the user, we think that unique combination can really help a lot there, and we can do some differentiated things there.
And the last thing I'll mention is just in terms of the incredibly valuable assets that we have with our data and our taste graph and how much that lets us do unique things with AI, I'd point you to what we're doing with tvScientific. It's a very tangible example of what we can do with that data beyond our Pinterest app where we've been able to achieve a 27% increase in the outcomes and a 65% increase in purchases by leveraging our taste graph on top of tvScientific's algorithms.
So that's one tangible example that we talked about on the call of how we can use our data on top of algorithms to get even better outcomes and part of what we're doing with AI models, generally both what we build in-house and those where we retrain open source models. So I know I expanded on quite a bit there, but hopefully it gives you a sense of how we're thinking about the Assistant and just the advancement of the AI landscape overall.
Your next question comes from the line of Shweta Khajuria from Wolfe Research.
Could you please talk to your view on the evolving regulatory environment and the focus on online safety for younger folks and perhaps the opportunities or risks from the pending and/or proposed regulations?
Thanks for the question. We're seeing a clear trend where parents, policymakers and governments are raising the bar on online safety for young people. And this is a conversation we have long pushed for. We believe social media companies should compete on their safety record, the same way car manufacturers compete on their safety ratings. And we've proven that prioritizing safety and well-being can lead to better business outcomes.
As a specific example, when we made accounts private by default for under 16 in 2023, many people thought it would hurt our relationship with Gen Z. Instead, Gen Z is now our largest and fastest-growing demographic, representing more than 50% of our user base.
And we see that even beyond what's happening from a regulatory perspective, we see that young users are becoming much more keenly aware of the negative effects of traditional social media and are looking to create a healthier social media diet and spend time in places that they know are positive for their well-being.
So in addition to making accounts private by default for users under 16 and private only for users under 16, we've supported phone-free schools and app store age verification, and we apply AI in ways that prioritizes and tunes for positivity. And the response from users reflects that there's a genuine consumer demand for a more positive and safer space online.
And Pinterest has earned that trust by making the right choices over many years. So while neither we nor anybody else can perfectly predict what happens in the regulatory environment, we welcome that conversation. And we've been an active voice in those discussions. And we've seen the policymakers recognize and appreciate the proactive stance that we've taken on these issues. And for the sake of all our young people, we're hoping to see more advancement of that dialogue.
Your final question comes from the line of Brian Nowak from Morgan Stanley.
Maybe just 2. One, on the upside in the first quarter, it sounds like it was driven by some of the attribution improvements from the large advertisers toward the end of the quarter. So the question is as you look into 2Q, are you sort of assuming you see further benefits from that attribution modeling across even more advertisers? Or is that -- would that be a source of upside to even what your base case expectation?
And then secondly, Bill, you have quite a few innovation irons in the fire, I guess. Are there any 1 or 2 that you would point to and say this could be a driver of substantially faster growth in revenue even this year, like this attribution modeling was?
So on the first part of your question on the attribution, like this is not a guidance commentary to be very clear. But as I mentioned in the prepared remarks, it was some of the things that we -- when we talked about these even in Q4 of linking our AI bidding systems to the measurement sources of truth of the advertiser. And by doing that, the AI is able to deliver more and more outcomes that are aligned with the way the advertiser sees value from those outcomes.
And we were in beta with that in Q4. As I mentioned, as we rolled it out in Q1, we're seeing that work well. We have more of that deployment to go. And so we're excited about that. We also think that, as I mentioned a few times, like continuing to deepen our measurement integrations with our partners should allow us to capture much more of the value that we're creating. Again, 5x the number of clicks to advertisers over the last 3 years, but the revenue hasn't increased nearly as much as that.
As you look at what's happening with other platforms, you hear them talking about model conversions. You see them growing revenue faster than the rate of their supply growth and those model conversion, those kinds of things, like some of that means that those platforms are doing a better job of taking credit for clicks and conversions that they may not have driven directly or they were a more tangential part of that.
So we think as we get more deeply integrated into measurement platforms, that gives us an opportunity to get more of our rightful credit for those things. Simultaneously, I would say another positive trend is that as advertisers start to really give more credit to actions beyond just the last click. We have a lot of upper and mid-funnel activity as well. And so as we see that playing out, we think that is generally in the long term, a good thing for our platform, but there's a lot of work to do in terms of getting the measurement integrations not only from the -- getting people to leverage our products, but the sales and go-to-market efforts, which is why we've had the meaningful retooling of our sales and go-to-market.
So hopefully, that helps give a little bit more color as to some of what we're seeing from the products there. And in terms of innovation, one of the things I'd point you to on innovation, I touched on this a little bit, we see and are driving much more commerciality than what we believe we're getting credit for today. And we also think that commerciality can let us that very unique audience and high commercial audience that we have, we think we can drive outcomes well beyond just our O&O property.
So tvScientific, you can think of as the first move in that direction, and we shared some of the stats. We're really excited about how we're moving there. That 27% increase in outcomes and 65% increase in purchases when you brought the Pinterest audience on top of the tvScientific algorithms, we have a lot more to do in CTV.
We're very excited about that. But we also think how can we leverage our audience beyond surfaces beyond just the Pinterest app, we think is a really interesting area of opportunity. And again, connected TV, we're off to a good start, lots more to do, but we think there's more that we can do in terms of the value of that audience more broadly.
Yes. And then maybe just to wrap up, obviously, our plans here are all factored into our Q2 guidance numbers. I think way too early to talk about what's happening in the second half of the year. But certainly, we're feeling really good here about the first half progress against the plans and our goal is to kind of continue hitting consistently our mid- to high teens revenue growth targets, which are our long-term targets.
This concludes our question-and-answer session. I will now turn the call back to Bill Ready for closing remarks.
Thanks again to all of you for joining the call and for your questions. We look forward to keeping this dialogue going, and we hope you enjoy the rest of your day.
This concludes today's call. Thank you for attending. You may now disconnect.
Pinterest — Q1 2026 Earnings Call
Pinterest — Q1 2026 Earnings Call
AI-driven growth and monetization lift Pinterest with solid Q1 results and strategic AI initiatives.
📊 Quarter at a Glance
- Revenue: $1.008B (+18% YoY; above guidance)
- Adjusted EBITDA: $207M (20% margin; +40 bps YoY)
- MAUs: 631M (+11% YoY)
- Free cash flow: $312M
- Buyback: $2.0B repurchased (109M shares; ~16% fewer shares); $2.0B remaining on a $3.5B program
🎯 What Management Says
- AI-first flywheel: Artificial intelligence powers Pinterest’s personalized discovery; PinRec improves search fulfillment and lowers costs; Canvas enables real-time, high-quality image editing at lower cost.
- Monetization focus: Broaden revenue base across mid-market, enterprise, SMB and international; strengthen measurement and go-to-market with more accountability and AI tooling.
- TV/CTV expansion: tvScientific acquisition extends Pinterest to connected TV, with early wins and plans to integrate capabilities into Pinterest Performance+ for broader reach.
🔭 Outlook & Guidance
- Q2 revenue: $1.133B–$1.153B (+14% to +16% YoY; FX ~1 pt tailwind)
- Q2 adj. EBITDA: $256M–$276M
- Full-year note: 2026 margin around 29% ( ~100 bps drag from tvScientific); continued investment in S&M and R&D; long-term target remains 30%–34% EBITDA margin.
❓ Analyst Q&A
- Upside drivers & attribution: Deepening advertiser attribution, integration with measurement partners, and tvScientific contributions could lift results into Q2 and beyond.
- Go-to-market changes: Reorganization under Lee Brown aims for more accountability, regional focus, and increased use of AI tools to improve execution and measurement.
- Performance+ adoption: ~30% of lower-funnel revenue; growth opportunities in mid-market, SMB and international; ongoing enhancements to bidding, targeting, creative and measurement.
⚡ Bottom Line
Pinterest posted solid Q1 results with revenue and EBITDA ahead of guidance, driven by AI-enabled engagement and a broader advertiser base. The company reiterates its mid- to high-teens long-term revenue target and 30%–34% EBITDA target, while expanding into TV advertising and strengthening its go-to-market and measurement capabilities.
Pinterest — Q4 2025 Earnings Call
1. Management Discussion
Good evening. Thank you for attending today's Pinterest Fourth Quarter and Full Year 2025 Earnings Call. My name is and I'll be your moderator for today. [Operator Instructions]
I would now like to pass the conference over to Pinterest VP of Investor Relations and Treasurer, Andrew Somberg. Andrew, you may proceed.
Good afternoon, and thank you for joining us. Welcome to Pinterest's Earnings Call for the Fourth Quarter and Full Year ended December 31, 2025. Joining me on today's call are Bill Ready, Pinterest's CEO; and Julia Donnelly, our CFO.
The statements we make on this call reflect management's view as of today and will include forward-looking statements. Such statements involve a number of assumptions, risks and uncertainties, and actual results may differ materially. For information about assumptions, risks, uncertainties and other factors that could affect our results, please refer to our Forms 10-K and 10-Q, each filed with the SEC and available on our Investor Relations website at investor.pinterestinc.com.
During this call, we will present both GAAP and non-GAAP financial measures. A reconciliation of non-GAAP to GAAP measures is included in today's earnings press release and presentation, which are distributed and available to the public through our Investor Relations website. Lastly, all growth rates discussed today are on a year-over-year basis unless otherwise specified.
And now I'll turn the call over to Bill.
Thanks, Andrew. Good afternoon, and thank you for joining our fourth quarter and full year 2025 earnings call. Before I get into the quarter, I want to address the moment we're in. AI is changing how people discover, how they form intent, narrow choices and move from inspiration to action. Pinterest is designed for this shift. When users have intent but don't have the exact words, brand or product in mind, that's where we win. I'm proud of how we've transformed the company over the past 3.5 years. We've taken Pinterest from a platform with declining users into a growing AI-powered visual first shopping assistant and search destination that has now put up 10 straight quarters of record high users. Today, we see over 80 billion monthly searches on our platform, most of which are visual and generate 1.7 billion monthly outbound clicks.
Over that same time period, we've launched numerous performance ads products to build a unique full funnel ads platform, moving from single-digit revenue growth to consistent mid-teens or better revenue growth, all while significantly expanding margins. All of this combines to make Pinterest a stronger, more profitable business than ever before. We [Audio Gap] 2025 with 619 million global MAUs, up 12% year-over-year in Q4. User growth accelerated in the second half as we continue to introduce AI-led features for both users and advertisers. However, we are not satisfied with our Q4 revenue performance, and believe it does not reflect what Pinterest can deliver over time.
While we absorbed an exogenous shock this year related to tariffs, which are disproportionately affecting ad spend from our top retail advertisers, this quarter also underscored where we need to move faster. Most importantly, we need to further broaden our revenue mix and accelerate the next phase of our sales and go-to-market transformation. These efforts will be led by Lee Brown, who joined in late January as our first Chief Business Officer.
We are moving with urgency to return over time to the mid- to high teens growth or better than we have been consistently delivering. The path forward is clear and we're laser-focused on delivering the next phase of Pinterest. Our priorities, which I will walk you through today are to: First, continue building a differentiated visual search, discovery and shopping experience. We have made Pinterest into a highly personalized visual first shopping destination, and we need to continue to build on our strong momentum with users.
Second, keep AI at the core of everything we do. from highly personalized user experiences and new features like Pinterest Assistant to the advertiser experience through Pinterest Performance+ and to optimizing our own internal operations. And third, accelerate monetization through improved go-to-market and sales execution, so our revenue consistently reflects the strength of our user activity.
With that context, I want to begin where every platform starts, with users and engagement. It's clear that we are in a period of rapid innovation in our industry with new AI chatbots quickly scaling to hundreds of millions of users. However, competing for user engagement is not new to us, and we have been able to thrive because we are doing something separate and distinct. During that same period when AI chatbots were scaling, we reported 10 consecutive quarters of record high MAUs, 100% of which are logged in and reached 105 million UCAN MAUs.
The Gen Z population, who are often the earliest adopters of this new technology like AI chatbots are also flocking to Pinterest. Gen Z represents over 50% of the users on Pinterest today, and they remain the fastest-growing user cohort on our platform. Our ratio of weekly active users to monthly active users or WAU-to-MAU ratio, has held steady year-over-year even as we achieved record highs in users. Importantly, we're also deepening engagement per user in the areas that matter most. As queries, boards created and clicks to advertisers continue to grow faster than users overall, both globally and also in our highest engagement UCAN region, specifically.
To understand how we've been able to carve out this distinct position and grow users and engagement, even as chatbot scale, I'd like to expand upon how we positioned our platform for visual search and discovery. Stepping back, e-commerce spent the first 2 decades focused on perfecting buying online, cheap and fast fulfillment, often at the expense of shopping, the joy of discovering what you actually want. Today, there are countless places to buy, but a few great places to shop, and that's where visual discovery matters most. As AI adoption accelerates, general purpose search is increasingly up for grabs as the largest players pour capital into general-purpose LLMs. But fit for purpose search still wins in key verticals like travel and consumer products.
Our differentiation is clear. We're using AI to power visual search, discovery and shopping, not general-purpose tech-based search. Pinterest sees over 80 billion searches a month and the vast majority are visual, while our newest visual search features are growing fastest. Engagement is growing because our unique curation signal and taste graph combined with cutting-edge AI has improved relevance significantly and made our services much more actionable. Users open Pinterest to a personalized visual feed that starts their shopping journey without having to enter a prompt, bringing the promise of agent a commerce to life. And they can buy seamlessly by linking to an advertiser's mobile app or site or increasingly via one-click checkout from the advertiser within our app.
As I've said before, in many ways, AI is following the same pattern cloud computing did over a decade ago. It's rapidly becoming a set of foundational capabilities available to everyone. The winners will be the companies that combine those capabilities with truly differentiated data and solve problems in unique ways for users and customers. That's exactly what we do at Pinterest. We have created one of the largest search destinations in the world by pairing those building blocks with our unique feedback loop and data set. One of the largest image corpuses in the world and the rich curation signal from hundreds of millions of users that forms our taste graph.
In 2025, our taste graph grew by nearly 40%, as users make more associations across pens, products, boards, retailers and brands. A larger taste graph means we can surface more relevant content and make truly differentiated recommendations. Not only do we have differentiated signals, we're also leveraging AI in a highly capital-efficient manner. We are model agnostic and focus on what delivers the best results for our specific use case, giving us the flexibility to test multiple approaches. As a result, we use a combination of AI models, including our own proprietary fit-for-purpose foundation models, leading third-party proprietary models and increasingly open source models that we fine-tune on our unique signal.
In 2025, we introduced Omni Sage. Our core AI model trained on our taste graph to turn those associations into a single high-value recommendation signal used to retrieve and rank content. The application of Omni Sage drove a 450 basis point lift in site-wide saves. Additionally, in a continuation of our work to increase contact windows and bring a user's full history across all major surfaces on Pinterest, we developed a proprietary foundation ranking model called PFM. This model distills lifetime user actions into the recommendations on the home feed and related pens, driving personalization in nearly every impression our users see. This launch brought meaningful site-wide engagement gains, including a 240 basis point increase in saves across the platform.
Finally, as open source models have made tremendous strides in performance, we developed a model framework called Navigator ONE, which allows us to leverage visual embeddings built on our taste graph and fine-tune open source models to power our newest AI-driven experiences. This framework reduces latency and delivers approximately 90% reduction in costs versus utilizing a leading third-party proprietary model. These models form the foundation for the next generation of AI-driven discovery experiences on Pinterest.
A great example of this is Pinterest Assistant, which we launched in beta in Q4. Pinterest Assistant is a voice-activated visual first conversational assistant that will leverage Navigator One to expand our multimodal discovery capabilities and seamlessly flow between images, voice and text. While we're still iterating, we're encouraged by how people are using the product. Compared with traditional text-based search users are asking a significant higher share of commercially oriented questions, about 25 percentage points more, when using Pinterest Assistant. Pinterest Assistant also helps users learn the names and terms for whatever they're looking for, making it easier to find similar items in the future. That's exactly the kind of high intent, high-value engagement we want to enable. We expect to meaningfully broaden access to U.S. users over the coming months.
Lastly, AI is at the core of how we are improving efficiencies internally as roughly 50% of our new code is AI generated. Taken together, these advances give us confidence that we can keep improving relevance, engagement and advertiser performance while remaining disciplined on AI spend by leveraging Pinterest's unique first-party data.
With that, now I'll turn to the fourth quarter and our priorities for the year ahead. As I stated upfront, we are not satisfied with our Q4 revenue growth, and we are moving with urgency to close the gap. Many of the largest retailers have been disproportionately impacted by tariffs and have been pulling back on advertising spend across the industry as they seek to protect their margins. Our higher mix of large retailers relative to some of our peers has resulted in us feeling more of an impact. This highlights the need for us to further accelerate our growth with a broader set of mid-market, SMB and international advertisers with less than $30 billion of GMV. This is the next phase of our sales and go-to-market transformation.
Stepping back, as we were building our performance ads platform, we deliberately started by serving the largest retailers, given that is where consumers do the most shopping and was the fastest way to provide comprehensive inventory and selection to shoppers. This strategy has been effective. as reflected in our user and engagement trends and in our ad supply with paid clicks to advertisers up roughly fivefold over the last 3 years. However, this strategy is also what has led to higher exposure to large retailers compared to some other platforms. We saw continued softness from this cohort of large retailers in Q4. While we see opportunity over the long term, the near-term outlook for this cohort on our platform remains pressured given these headwinds.
At the same time, the scale of the monetization opportunity we're pursuing has grown significantly. We're now competing for full funnel and performance marketing budgets across a broader range of advertisers in global markets than ever before. We made significant progress growing with a broader set of mid-market SMB and international advertisers in 2025. And but not enough to offset the headwinds that the largest retailers faced.
So we've proven we can serve mid-market SMBs and international advertisers, but we need to accelerate our growth within these segments. Also, while we've made progress evolving our sales organization from primarily selling upper funnel brand advertising a few years ago to full funnel and performance marketing, our monetization still doesn't fully reflect the value of the clicks and conversions we're driving. This quarter made it clear that capturing this opportunity requires a higher level of sales and go-to-market sophistication with globally scaled selling motions as well as deeper technical expertise, particularly around measurement and attribution.
To lead this next phase, we're pleased to welcome Lee Brown as our new Chief Business Officer, with responsibility for scaling Pinterest's global monetization efforts. Lee is a proven business and sales leader with deep experience building and growing advertising businesses at the intersection of technology, media and commerce.
Cloudian also joined us in February as our new Chief Marketing Officer, bringing extensive background with the world's largest online retailer. With this leadership in place, we believe we have the right team to pursue the significant long-term opportunity ahead.
Now let me turn to the key levers we'll be executing against as we move through 2026. First, as I've shared, we're prioritizing broadening our revenue mix, with a primary focus on deepening our footprint with both mid-market enterprises and SMB advertisers. These advertisers who, on our platform range from roughly $30 billion down to tens of millions in annual GMV and continue to represent a significant opportunity for us to scale advertiser demand. Relative to the largest advertisers I was describing earlier, we believe this group has exhibited stronger advertising spending trends in the current environment and has been a strong growth driver for competing ad platforms. By further unlocking this opportunity, we create a powerful flywheel more diverse advertiser demand allows our models to serve more relevant, highly personalized ads to users. This relevancy not only improves the user experience but drive superior performance for our advertisers and higher yield for Pinterest.
While we're seeing healthy revenue growth from this group today, we believe we can accelerate that momentum over time with new leadership and a more sophisticated go-to-market approach, along with the enhancements we're making to Pinterest Performance+ that I will talk about in a moment.
As part of our multiple ways to win, we've also been on a multiyear journey to bring in new sources of demand via multiple third parties to complement our first-party demand. We previously announced the agreement to acquire TV Scientific, a leading connected TV performance advertising platform. This acquisition is an important step toward leveraging our valuable high-intent audience beyond Pinterest's owned surfaces and starting to monetize off-platform supply. Acquiring TV Scientific, which comes after a partnership and several years of exploration in this space supports our road map to make Pinterest a full funnel and performance solution across search, social and over time, connected TV. It opens up larger and incremental budget pools. We're excited to welcome this outstanding team and to begin helping advertisers reach our high intent audience on Connected TV.
Second, we're continuing to advance Pinterest's Performance+ by investing in the next wave of bidding and performance enhancements. Since the end of 2023, we have increased the number of shopping SKUs with a paid ad impression by roughly 5x. Over the past year, we accelerated this trend with the launch of Pinterest Performance+ ROAs bidding in Q1 2025, which adds more granular bidding functionality and allows advertisers to optimize for conversion value, not just the number of conversions. We still see significant opportunity to deepen catalog penetration as we remain a long way from having bids and budgets against advertisers' full product catalogs.
As advertisers increasingly adopt AI-driven automation platforms. The next step is optimizing our bidding system to become more tightly aligned with the advertisers measurement source of truth. Late last year, we began to pilot integrations with a few of our most sophisticated advertisers proprietary in-house measurement systems to help us optimize bids to drive more of the outcomes of those advertisers value. So far, this pilot has delivered promising results, with one advertiser increasing its bids on Pinterest by more than 30%, reflecting the higher value it was seeing from the platform under this new value-based optimization approach. We expect to expand this pilot to additional large sophisticated advertisers in the first half of 2026.
To serve an even broader set of advertisers who rely on third-party measurement partners, later this year, we will enable deeper direct integrations between Pinterest and a number of measurement partners. These integrations will allow automated 2-way data transfer, so we can continuously train and optimize our bidding models to reflect advertisers highest valued outcomes and thus show up more favorably in their measurement systems. Additionally, these measurement systems are increasingly assigning more credit to events leading up to a conversion, such as view-through attribution.
For example, Omnilox, a leader in medical-grade LED light therapy partner with Pinterest and its measurement partner, North Beam. After leveraging North Beam's clicks plus deterministic views model, Omnilex saw a 7x increase in attributed transactions to Pinterest through view-based attribution. For a full funnel platform like Pinterest, this shift should support increased budget allocations over time. As part of our broader effort to give advertisers more control over expressing what matters most to them and building upon campaign customer groups, which we introduced 2 quarters ago. We recently entered beta for Pinterest Performance+ new customer acquisition. Available exclusively through Pinterest Performance+ campaigns, this feature helps advertisers efficiently acquire new customers by allowing them to assign their own customized values to different audiences, so we can optimize towards that outcome.
In initial testing, advertisers saw new customer conversions increased by an average of 64% in campaigns where new customer acquisition was enabled compared to control campaigns without it.
In closing, this is a moment of extraordinary innovation at Pinterest and across our industry and one that we've been building towards for the last several years. Our user and engagement trends reinforce that our product direction is working, and we know where we need to execute better to drive faster and more durable growth to ensure monetization follows that engagement. Importantly, I'm proud not only of what we're building, but how we're building it. We've made deliberate choices that put user trust and well-being, especially for young users at the center of the experience, and we're seeing those choices rewarded as more users than ever come to Pinterest each month. It's clear the parents and regulators around the world are raising the bar for online safety, particularly for teens and kids. We're proud to lead the way by tuning our AI for positivity and giving our users more agency and choice over their experience.
This positions us well as these standards evolve. We are creating a positive place on the Internet where people can invest in themselves and proving that you can build a strong business based on positivity. With that, I'll turn the call over to Julia to share more details about our financial performance.
Thanks, Bill, and good afternoon, everyone. Today, I'll be discussing our full year and fourth quarter 2025 financial results and provide an update on our first quarter 2026 outlook. All financial metrics, except for revenue will be discussed in non-GAAP terms unless otherwise specified, and all comparisons will be discussed on a year-over-year basis unless otherwise noted.
I'll start with our fourth quarter results. We ended the quarter with 619 million global monthly active users, or MAUs, growing 12%, our tenth consecutive quarter of record high users. We continue to demonstrate user growth across all of our geographic regions. In Q4, our U.S. and Canada region had 105 million MAUs growing 4%; our Europe region had 158 million MAUs growing 9%; and in the Rest of World markets, we had 356 million MAUs growing 16%.
Moving to revenue. In Q4, our global revenue was $1.319 billion, up 14% year-over-year or 13% on a constant currency basis. We saw strength from our conversion objective. Across verticals, growth was driven by retail, though with puts and takes within that, as we've described, and driven by smaller but faster-growing categories on our platform, including financial services and telecom.
Turning to our geographical breakouts for Q4. Revenue in the U.S. and Canada was $979 million, growing 9%. Growth came from retail, financial services and telecom. In Europe, revenue was $245 million, growing 25% on a reported basis or 18% on a constant currency basis. Growth in Europe was driven by retail, but was lower than our expectations. We saw a second order effect on cross-border spend from certain large global retailers who pulled back ad spend in Europe as well as you can as they recalibrated across our global portfolio due to the same tariff and margin pressure as Bill described earlier.
Revenue from Rest of World was $96 million, growing 64% on a reported and constant currency basis. In Q4, overall ad impressions grew 41% while ad pricing declined 19% year-over-year driven primarily by the continue mix shift [Audio Gap]
In Q4, cost of revenue was $221 million, up 15% year-over-year and up 7% versus Q3, due to increased infrastructure spend related to our user and engagement growth. Our non-GAAP operating expenses were $562 million, up 13%. The increase was driven by headcount investments in sales and marketing and R&D as we continue to invest in AI initiatives and grow our sales force. Within G&A, expenses grew at a higher than typical rate year-over-year, primarily due to certain legal costs not expected to repeat as well as lapping certain insurance proceeds received in the prior year.
In Q4, we delivered adjusted EBITDA of $542 million with an adjusted EBITDA margin of 41%, up 20 basis points versus Q4 last year. For the full year 2025, free cash flow increased 33% to $1.25 billion. This compares to 2025 adjusted EBITDA of $1.27 billion, representing free cash flow conversion of 99%. Our ability to generate significant free cash flow speaks to the inherent profitability of our business and asset-light nature of our model. Investors should continue to analyze our free cash flow annually as quarterly free cash flow can fluctuate due to the typical seasonality of our business.
We ended the year with cash, cash equivalents and marketable securities of $2.5 billion. We made further progress mitigating dilution in Q4 as we allocated $500 million towards share repurchases, bringing our full year 2025 share repurchases to $927 million for a total of 30 million shares. In addition, we utilized $399 million of cash in the year on net share settlement of equity awards. Combined for full year 2025, these actions have driven an approximately 1.6% decline in year-over-year fully diluted share count, which compares favorably to our stated positive 2% to 3% average annual target.
Now I'll discuss our guidance for the first quarter, which does not include any impact from TV Scientific as we await regulatory approval for the closing of that transaction. We expect Q1 revenue to be in the range of $951 million to $971 million, representing 11% to 14% growth year-over-year. Based on current spot rates, our guidance assumes the impact of foreign exchange to be approximately 3 points of tailwind in Q1. For the first quarter, we expect adjusted EBITDA to be in the range of $166 million to $186 million. We anticipate Q1 2026 non-GAAP cost of revenue to grow sequentially from Q4 2025 by low single digits percent. In Q1, within non-GAAP operating expense, we will focus our investments on our sales transformation and additional R&D hiring to support our AI efforts.
Next, I want to share some color about the trajectory of margins throughout the year. Starting with cost of revenue. In 2026, we're making deliberate investments in high ROI areas such as GPU capacity to enable key AI initiatives. These investments will allow us to train and serve visual foundation models and our conversation models that advance our capabilities in multimodal search, discovery as well as Pinterest Assistant. In addition, we will continue to build more powerful AI models that are enhancing full-funnel ROAS for our advertisers and ad relevance for our users.
We also have been signaling for some time that we have captured much of the benefit from our multiyear infrastructure cost optimization efforts and are now reaching diminishing returns. As a result, we expect modest headwinds from cost of revenue as a percentage of revenue in 2026. That said, we are actively -- acting decisively to free up investment capacity elsewhere within the company. In January, we announced a restructuring, including a series of organizational actions to simplify how we operate, reduce layers and increase efficiency so that we can invest more intentionally in the areas that matter most, especially AI and our go-to-market transformation.
The result of these offsetting dynamics is that we expect adjusted EBITDA margins to be roughly in line with 2025. So while we anticipate year-over-year adjusted EBITDA margin pressure in the first half, based on our current outlook, we expect full year 2026 adjusted EBITDA margin to be roughly in line with 2025 at approximately 30%.
While the acquisition of TV Scientific has not yet closed, we do expect closing to happen in Q1 or Q2, which we anticipate would cause a roughly 100 basis point drag to adjusted EBITDA margin in 2026, leading to 29% for 2026 overall on a combined basis. To illustrate the potential revenue impact of the acquisition, I will also share that we estimate TV Scientific's Q4 2025 revenue would have contributed less than 2 points of growth to Pinterest revenue in Q4 2020.
Stepping back, over the last 2 years, we've made meaningful progress toward our long-term margin goals. Adjusted EBITDA margins expanded by nearly 700 basis points from 2023, reaching 30% in 2025, reflecting both operating discipline as well as the inherent profitability of our model as we've scaled. Our margin outlook for 2026 reflects our decision to lean into the high ROI investment opportunities we see for ourselves in this crucial moment and to capture the full opportunity ahead. However, our fundamental view of the profit potential of the business is unchanged. and we, therefore, still expect to achieve our adjusted EBITDA margin target of 30% to 34% over the medium term.
Given the strength of our user and supply dynamics, and the organizational actions we are taking to strengthen our sales and go-to-market efforts, we believe our revenue growth should be higher over time, and we continue to have conviction in our ability to reach our long-term targets. We are making the right decisions today to emerge from this period better positioned to compete for the large and growing opportunity ahead.
With that, I'll hand it over to Bill for some final words.
Thanks, Julia. I want to thank our teams at Pinterest, our advertising partners and all the people that come to Pinterest to find inspiration and take action.
And with that, we can open the call up for questions.
[Operator Instructions] The first question will go to the line of Doug Anmuth with JPMorgan.
2. Question Answer
Can you just talk more about the drivers of 4Q revenue, including the home impact that you saw? And then also how you're thinking about the 1Q guidance?
Sure, Doug, I'll take that one. So in Q4, our largest retail advertisers created a more meaningful headwind than we expected as they sought to protect their margins in this dynamic environment and pulled back on ad spend. We believe this pullback on ad spend from larger advertisers was felt across the industry but impacted our platform to a higher degree, given our current revenue mix. We also saw a second order effect of the same dynamic into Europe as well with some of these same large global retailers pulling back on spend in Europe as they rebalance across their global portfolio.
On the home category, where there was a new furniture tariff enacted last October. The home category remains challenged overall, but the performance there was generally in line with our expectations at the time of guidance. Looking ahead to Q1, we expect these headwinds will continue and may become slightly more pronounced in Q1, including in U.K. and Europe. It's also worth noting that we recently implemented a restructuring in January and are going through a sales and go-to-market transformation, and that may cause some near-term disruption, which we factored into our guidance to be prudent. So all that to say, we're in a moment in time where both of these near-term factors are impacting us. And we know we have a lot of execution to do on the monetization side, and we've started that process.
Looking kind of even beyond Q1, visibility isn't perfect. And obviously, we don't guide beyond one quarter. And we can't predict the macro working anyone perfectly. But we're not seeing any new factors today beyond what we've described that would create more headwinds to our current trajectory.
A few things to think about as we go forward to 2026. In terms of external factors, we've talked about the larger retailer headwinds, which we will start to anniversary in the second half of 2026. For internal factors, we talked about our measurement product releases and sales and go-to-market transformation, which may take a couple of quarters to play out, but we're encouraged by the new leadership we have in place with Lee and the quick actions he's taken there. So all of this will take time, but we're moving quickly to ensure our revenue matches the strength of the users and engagement we're seeing on the platform today.
Our next question will go to the line of Ross Sandler with Barclays.
Great. Bill, can you elaborate on how you and we are changing the go-to-market team. And basically, how is this new organization or a reorganized team likely to drive wallet share and digital advertising for Pinterest? And then Julia just mentioned this, what's the lag period between when the new team kind of comes together and when it might be generating positive results in the form of share gain?
Thanks, Ross. So only been here for a few weeks, but he's already moving quickly and taking decisive action. As with any sales transformation, there can be some modest disruption in the near term as we rebuild and retool the organization to best position the company for the long term. But we're doubling down on broadening our revenue and consistent with the areas that we've been talking about with you all of last year, particularly across mid-market enterprise and SMB advertisers and closing the monetization gap in international markets, including rethinking how we cover some of these areas.
Over the past year, we've made good progress on this. We've doubled the growth rate of our managed SMB business. We expanded with mid-market enterprise advertisers in the $1 billion to $30 billion range and international revenue growth accelerated to 38% versus 25% in 2024. But we believe growth in these areas should be higher, which is why we need to move faster and be bolder. And to do this, we need to restructure and reallocate resources across those opportunities. We need to adapt more quickly to grow within the fastest-growing parts of the market that we see contributing more significantly to the overall growth of competing platforms.
So we're also doubling down on measurement and technical capabilities within our sales team. We've made significant progress from where Pinterest was just a few years ago as an upper funnel only platform and sales team to one that can compete for performance budgets with the largest most sophisticated advertisers. But we know there is significant opportunity in driving greater performance selling capability across our sales organization and across the segments of the business beyond large advertisers. This is actually really important as the industry has advanced measurement and attribution with large platforms becoming more aggressive in claiming credit for outcomes, even when they don't own the clicker conversion. You'd see this reflected in others talking about "model conversions." This is an area where we know we haven't moved fast enough but we're laser-focused on addressing this and have -- we talked about some of the successful pilots that we've already put in place and that we have underway. So while we expect this to play out over a couple of quarters, we're planning prudently around it as we think these changes are essential for us to capture. What we continue to see as a much larger long-term opportunity more consistent with the long-term targets that we've talked about previously.
Our next question will go to the line of Ken Gawrelski with Wells Fargo.
I wanted to just follow up a little bit on this last point about broadening the advertiser base. And I know, Bill, you talked about this in the prepared remarks, around broadening beyond the large retailers. But can you talk a little bit more about how much tech investment beyond just kind of sales and go-to-market, but more tech investment might be necessary to broaden that advertiser base to broaden and deepen that advertiser base? And that's question one. And just to follow on, on the engagement side, you've seen -- it's kind of rare that we see in this industry where you see really strong engagement trends at least the third-party data that we follow suggests you've had very healthy time spend increases, both domestically and internationally. And I think that syncs up pretty well with was your commentary on these calls, but yet to see the ad revenues kind of decelerate here? And I understand there are specific pressures. But maybe you could just talk a little bit about the dynamics around impression growth and click outs relative to what you might -- the pressure you might be seeing on pricing and maybe even conversion if the consumer is less healthy?
Thanks, Ken. So like the rest of the market, we're seeing strong performance amongst our managed SMB business. We actually get is one of the fastest growing parts of the market and a part of the market that we've been under-indexed to these advertisers represent approximately 15% of our revenue today. So we are very active there, but it's a lower percentage on other platforms. And I mentioned the revenue growth rate of this group nearly doubled in 2025 versus 2024. And so we see opportunity over a multiyear period to make us a larger part of the business. And again, we think that's where we see competing platforms having significant growth. And so that growth we have had there demonstrates that we've got product that can compete there. SMBs who are adopting Performance+ campaigns to automate and simplify campaign set up with AI are seeing stronger performance and are spending more on our platform. So as we noted last quarter, we see a 12% higher monthly revenue growth rate with these managed SMB advertisers versus non-adopters. So the ongoing improvements we're making to Performance+ around measurement and attribution will be particularly important for this group as they have leaner teams and often rely on third-party measurement platforms to validate performance. So looking forward, we will continue to focus on driving Pinterest Performance+ campaign adoption as well as simplifying the advertiser onboarding experience. So whether there's more for us to build on product, but the product that we have today, we know can work and is driving good progress there. And it will take time. But Lee and the team are focused on bringing a new level of sophistication to our go-to-market efforts, including how we sell to a broader range of advertisers, particularly with SMBs. And then I'll give to Julia to hit some of the other part of your question there.
So I would just to add on to that, and we'll -- Ken, I think you had a second question on sort of engagement, which I'll go back to. But I just want to add on that SMB, Bill talking about SMB is obviously a large opportunity for us. But it is sort of one of multiple ways that we have to win, as we've talked about in previous quarter, right? Other growth drivers include deepening our share of wallet with mid-market enterprises, growing internationally, growing with agencies and UCAN and internationally and using third-party demand to complement our first-party business. We're also continuing to drive growth in emerging verticals, including financial services, telecom, technology and entertainment, all of which we think can help us build a broader base of revenue and more resilient platform over time. I think we had a second part to Ken's question as well. So I'll turn it back to Bill for that.
Yes. On the engagement side, a couple of things I'd note. We've talked about this, to transform the platform, we need to start with users first, get the shopping behavior and the search behavior. And on that on that engagement, we talked about the 10 straight quarters of record high users. I actually think one of the things. We shared this for the first time last quarter. And I don't think it got as much discussion on the call. But as we talk to folks across the industry, it has really raised some eyebrows in terms of the 80 billion monthly searches that we're doing. To put that in context, you can go look at third-party data as what other platforms are doing. If you ask ChatGPT, how many prompts per month ChatGPT does, it will tell you about 75 billion monthly prompts. We're doing 80 billion monthly searches and generating 1.7 billion monthly clicks. That makes us one of the largest search destinations in the world. And importantly, more than half of those searches are commercial in nature compared to, I think, open out share that they have approximately 2% that will be commercial there. So not only have we created one of the largest search destinations in the world and doing approximately as many searches per month as ChatGPT doing prompts in a month, more than half of that is commercial. And so we have talked about how we needed to go from winning that engagement to then getting the advertisers behind that and then getting measurements so they could see that and lean more into their budgets.
If you step back from it, we're still relatively early on in that journey, we only became fully committed to being a performance ad platform just a few years ago. And you have the largest ad platforms in the world that have been at this for 20-plus years, they were competing against. But the growth that we have delivered is really indicative of how much unique user engagement we have there. But obviously, we have a lot more of that to do. And I would say our users and engagement are out in front of where our ad platform is. The ad platform has been growing significantly. And the ad platform is out in front of where our sales and go-to-market capabilities are.
And as we have proven out that we can sell not only to those largest retailers, but also to those midsized retailers that we've been talking about and SMBs and international and now moving beyond our O&O, just the complexity of that sales organization has increased significantly, and the need to have technical performance selling ability, measurement ability within the sales organization, that has changed significantly as well. So these are the things that are embedded in that sales transformation that we're talking about. And we're not only do we think there's a gap to cover between our monetization and our user engagement, we think that gap is quite significant and why we feel really encouraged about the long-term initial of our business. I've shared in my remarks, search is more up for grabs than it ever has been, at least in the last 25 years. And I'm not aware of another company in the western world that could claim anywhere close to the search volume that we're talking about other than us ChatGPT, OpenAI and Google. Obviously, we have a lot more to do to monetize that, but we have a clear line of sight as to what we need to do to get there.
Our next question will go to the line of Eric Sheridan with Goldman Sachs.
Maybe building on the answers to so far in the call, Bill, when you think about ChatGPT and they're launching their own ad product and you have a lot of ambition for growth across the industry at the same time that the industry is moving towards more automation and more AI and machine learning. Can you bring together your vision for how you see Pinterest broadly fitting into this increasingly competitive landscape for digital advertising budget dollars? I'll just ask the one and leave it there.
Thank you, Eric. Over time, we believe ad dollars will ultimately flow towards clicks and conversions and we have that engagement. And that has continued to grow, including in UCAN, our largest, most mature market. So while this has always been a competitive market, we have a unique curation signal. We have a differentiated full funnel platform. And we've created one of the largest source destinations in the world now with 619 million global users and shopping as a primary use case. We have one of the highest commercial intent audiences of any platform. Again, we're very early on in that monetization journey. But the others that would claim large search volumes are also very early. And so I think that the ad market is still quite large. There are a lot of dollars still flowing to places that aren't necessarily highly performant. We think there's a lot of dollars still up for grabs as we deliver high commercial intent, strong performance, there are a lot more dollars available. And so I talked about, for example, the TV Scientific acquisition as one of us now starting to monetize our audience beyond our owned and operated. We think there's a real opportunity in that commerciality beyond just our O&O surface. And this has happened before. You've seen this play out before where those that have high commercial intent are able to monetize that across multiple surfaces, including beyond their O&O.
So we think that again, we acknowledge that the revenue performance we put up in Q4, while pressured by the tariffs and our greater mix towards large retailers. While that has presented some near-term headwind, the long-term commerciality of the platform, the very significant volume of search activity that we're getting, the high commercial intent and our ability to -- that we've now proven that we can drive performance advertising budgets, gives us confidence that really, this is about how we get that performance to a broader set of advertisers through greater sophistication. And we think what we have is quite unique. I shared those stats. Again, 80 billion searches per month. Similar to what ChatGPT would say that it provides in prompts per month, but with a much greater mix of commerciality, 50% of our search is being with commercial intent, 1.7 billion monthly outbound clicks. There's a lot of that, that we still have to monetize, but we have a clear line of sight to do. We just have to do that across a broader set of advertisers. And we think that is quite unique in the ecosystem and there's room for multiple winners. So even as another new search player comes in, I think there's room for multiple to succeed. And what we're doing with the completely visual forward nature of our platform, those 80 billion monthly searches, the vast majority of those are visual in nature. It's just completely different than what anybody else is doing. We think that's a distinct space that not only are we winning there now, we see the very unique data that we have, giving us a sustaining advantage of that. Even as AI advances, we talked about how we're able to use low-cost open source AI and our own internal proprietary models, train that against that data and then get very different results. I shared on prior calls that our latest multimodal visual search models, outperform leading proprietary off-the-shelf models by 34 percentage points on the relevancy of shopping recommendations. That's really about that flywheel effect of the unique signal on our platform in AI trained on that unique signal. So those are all the things I'd point to that give us confidence that -- and I think, again, it's best demonstrated by what we've done over the last 10 quarters or 10 straight quarters of record high users, but also despite the sort of near-term bumps here, where we see that there is a lot more monetization opportunity ahead even just for the engagement that already is on platform today. Hopefully, that helps.
Our next question will go to the line of Colin Sebastian with Baird.
Great. I guess -- maybe for Julia, but obviously, a lot of moving parts here. But given some of the top line headwinds, the sales force transition and the opportunities you have to unlock with some of the reallocation of investments. Could you maybe walk through in a little more detail the puts and takes on the adjusted EBITDA outlook for the year just as we move through the year and then you balance some of those -- the impacts from some of those various factors.
Colin, so we anticipate adjusted EBITDA margins, as I said on the call, to be kind of roughly in line with 2025, excluding the approximately 100 basis point drag from the TV Scientific acquisition, which results in sort of 29% for full year 2026 overall. But to get into some of the puts and takes underneath that, we're intentionally investing in cost of revenue, specifically in GPU capacity to enable key AI initiatives, which I described earlier in my prepared remarks. But we believe this will drive further improvements to advertiser performance and, therefore, advertiser budgets and continued user and engagement growth. So we expect this cost of revenue investment to be approximately 100 basis points in 2026, similar to the gross margin outlook implied in my Q1 commentary earlier.
Moving to OpEx. In January, we took action on a restructuring, which we anticipate will generate approximately $100 million of annualized non-GAAP OpEx savings. Now we expect to reinvest roughly half of those OpEx savings primarily in our sales transformation and in AI talent. So as a result, the net impact between the cost of revenue investment and the OpEx savings I just described, gets you to roughly flat margins for the stand-alone Pinterest business in '26 compared to '25. On top of that, we expect the acquisition of TV Scientific, which is higher growth business, but also earlier-stage business. So we expect the acquisition of TV Scientific to be an approximate 100 basis point headwind to full year adjusted EBITDA margin, including some modest further deleverage on cost of revenue. So we'll continue to be responsive to the overall environment and thoughtful allocators of capital. But based on what we see today, these are the puts and takes that get us to our expected 29% adjusted EBITDA margin for '26, as I said before, we've made significant progress against our long-term targets, reaching 30% in '25. And obviously, this continues to be a very structurally high-margin business, and we continue to have conviction in margins reaching 30% to 34% over the medium and long term.
Our next question will go to the line of Brian Nowak with Morgan Stanley.
Just to go back to the advertising go-to-market change, so we can sort of understand a little bit what you want to really change this year, Bill. Can you give us sort of a couple of examples of your current go-to-market with SMBs and international and some tangible examples of what you would like to change 12 months from now, just so we can understand the KPIs and the go-to-market that you're most focused on to make this right. And then secondly, with the first quarter guide, I think you might have mentioned there's an assumption on some disruption expected in the advertising side. Can you just walk us through sort of like practically what are you expecting to be disrupted with the ore change?
Yes. Thanks for the question. So in terms of like how we're thinking about it, when we could step back and put things in context for a moment, we only started building a true performance ad platform just a few years ago. Our first true CPC product for advertisers wasn't launched until we didn't go GA until Q4 of 2023. So sort of 2 years in the quarter -- 2 years on a partial quarter into even having a platform that do clicks to advertisers. As we talked about before, we started with the very largest advertisers. We've been working our way down. Our SMB -- the main product that we needed to enable that for SMBs was Pinterest Performance+ because SMB advertisers need something that is much more automated, more set and forget it. Pinterest Performance+, we went GA at the start of '25. As we deployed that through '25, we saw that working well. As I mentioned, we doubled the growth rate of our SMB, our managed SMB population that's now 15% of revenue, but we know that can and should be much larger. And so it's a different kind of selling to those kinds of advertisers. .
The things that we need to do to run that the -- also the measurement integrations that we need to do as they rely on a different set of measurement partners than what the very largest advertisers would. So that is part of that go-to-market, which is how do we have those sellers set up to sell performance, understand the measurement, particularly measurement sources of truth that are used by the advertiser and then how to help that advertiser get the most out of our AI-driven tools like Pinterest Performance+ to configure those things for performance. Those are some of the things that we're driving through. And again, leasing a couple of weeks in, but these are things that -- we have made progress on this, again, doubling the growth rate of SMBs over the course of '25, we've made progress. So we have a clear line of sight what to do. We just need to take bigger, bolder steps. And we're confident now with Lee here, we've got the right leadership in place to go do that.
Yes. And the second part of your question in terms of Q1 and what I was referring to there on the near-term disruption, I think we obviously took the difficult decision to go through that restructuring activity in January. Part of that did impact some of frontline sellers and on the measurement side as well. And so as we're kind of getting ahead of that and backfilling those roles, obviously, it will take a little bit of time for those new folks to come in and ramp up productivity. So I do think we're anticipating a little bit of impact here in Q1, but all of that is factored into the guidance.
Our next question will go to the line of Justin Patterson with KeyCorp.
Great. Bill, you mentioned earlier that Pinterest is a brings the promise of agentic commerce to life without having to enter prompts. Could you just spend some more on just what agentic commerce means for Pinterest and the steps to get there?
Yes. Thanks for the question, Justin. The broader promise of agentic has tremendous potential, and we're leaning into the places where we see the most opportunity to solve compelling user problems. So let me start with: First, the way we think about the broader agentic opportunity and what it really means for users. The promise of agentic is one where users trust AI to help them along a commercial journey to remove friction and find products they love all without the user having to do as much of the work. That's exactly where Pinterest has been leaning in. Our visual search, discovery and personalization means that users are instantly met with relevant products that they're interested in when they open up the Pinterest app. We're helping them complete those commercial journeys without having to type in a single prompt. So that is the agentic nature that we are solving for already, which is the users to have to tell us what next step to take, we're meeting them with products that help them along their products recommendations that help them along their commercial journey.
In essence, we're helping our users know what to buy before they know what to ask for, which has historically been one of the biggest problems in search is that people don't have the words to describe what it is they're looking for. So on top of that, we've enabled capabilities that make the purchase in a single tap without ever leaving our site, most notably with Amazon. This has resulted in users, searches, clicks and overall commercial intent, all growing significantly and accelerating over the last 3 years. In Q4, we accelerated our product even further, introducing Pinterest Assistant, which adds voice as a new modality.
So we're seeing very strong traction in real-world application of this type of experience for users, with our AI capabilities at the core of how we're delivering on it. What we see less demand for in the near term is an experience where ages complete the full shopping journey without the user being involved at all. We see users wanting to be in the loop for the foreseeable future. And in the future, when users are -- well, right now, when users are ready to confirm a purchase, we're making it very seamless for them to do so. And whatever point in the future users are ready to actually trust the agent to press the buy button for them -- that will actually be one of the easiest parts of the commercial journey to solve given how many frictionless buy buttons exist in the market today. So again, I think there's been a lot of discussion of the promise of agentic, and a lot of it sort of goes all the way to the agenda just go do everything for you.
We're focused on the AI doing the thing that the users need the most help with today, and not getting in the way of the users for the thing that they want to make sure that they verify, which is the user being in the loop at that last one was saying, yes, that's the thing. Give it to me. I press a button in us all the way. And that's what's happening on the platform today and why we're seeing the very strong user engagement trends that we talked about.
Our last question will go to the line of Ron Josey with Citigroup.
I wanted to ask two really quickly. Just Bill, on TV Scientific. You talked about the new sources of demand and highlighted Pinterest third-party partners in the past. But with TV Scientific expands beyond the platform. Does it talk to us how this acquisition can open up larger budget pools as it just accelerates those TV Scientific as well as Pinterest overall scale? And then on the go-to-market and the revamp that we're planning there in the first half of the year. Would love your thoughts, just where are we on the process there? I know, obviously, Lee just to not too long ago, but any insights on additional impacts on timing and like rebuilding that team?
Thanks, Ron. So on TV Scientific, yes, you're exactly right. We've, over the last couple of years been bringing in third-party demand. This now is our first foray -- first meaningful foray into third-party supply. And this is very consistent with what you would see from other high-intent platforms, where you can take the high intent that you have on your own platform. And then drive more relevant, more performant ads on other surfaces based on knowledge of that intent.
And in terms of -- this is an area we've been sort of studying and experimenting in for a couple of years now. And we started with a partnership with TV Scientific to allow us to sort of understand their technology, their team, and we move from that to acquisition because they're driving today search type performance advertising in TV and connected TV, which is very aligned with our approach. And we think we can -- when we combine that with our very highly commercial audience and the scale of that audience, as I've shared a few times, over 80 billion monthly searches and that being primarily visual, which obviously would align with TV and sort of the visual nature of that. We think there's a lot we can do to together drive more performance connected TV advertising which is one of the fastest-growing areas of the ad market. So I talked about more exposure to SMB into international, given that those are fast growing. Connected TV is also fast growing. And I think there's a lot we can do to bring performance there. So hopefully that helps on the TV Scientific acquisition.
It effectively turns Pinterest into a full-funnel search, social and connected TV performance solution, opening up larger in incremental budget pools. And of course, these things take time, but we're quite excited about the opportunity.
On the other part, on the go-to-market revamp, that I have commented on that a good bit. And so the timing and rebuild, these things do take some time. We are in flight on these things already. Again, the way I would characterize this as looking back at '25, we talked about diversifying the revenue base all through '25. We were talking to all about that on the call then of expanding to those midsized retailers expanding to SMB to expand international, we executed on those things.
I would say that we had good execution, we need great execution. And so all that to say, we're not starting for the first time on these things. It's really about how do we learn from the efforts we've had so far, double down, go faster with greater clarity with those teams and bolder decisions around what are the different levers needed for those different segments of the business. It's just a more complex selling organization. Again, I think we've got the right leadership in place now with Lee to go after that. But time 0 is not at this moment. This is really about sort of us finding the next year in that transformation. We have a really good line of sight to that. And I commented that with any of these kinds of things, you can expect at times a quarter or 2 of disruption as you move through some of those things. But again, we've got clear line of sight to how these have already been faster-growing areas for us, and it's really about us doubling down in those faster-growing areas.
That will conclude the question-and-answer session. I would now like to pass the conference back over to Pinterest's CEO, Bill Ready for closing remarks.
Thanks again to all of you for joining the call and for your questions. We look forward to keeping this dialogue going, and we hope you enjoy the rest of your day.
That concludes today's earnings call. Thank you for your participation, and enjoy the rest of your day.
Pinterest — Q4 2025 Earnings Call
Pinterest — Q3 2025 Earnings Call
1. Management Discussion
Good day, ladies and gentlemen. Thank you for joining today's Pinterest Third Quarter 2025 Earnings Conference Call. My name is Tia, and I will be your moderator for today's call. [Operator Instructions]
I would now like to pass the call over to your host, Andrew Somberg, Vice President of Investor Relations and Treasury. Please proceed.
Good afternoon, and thank you for joining us. Welcome to Pinterest's earnings call for the third quarter ended September 30, 2025. My name is Andrew Somberg, and I'm Vice President of Investor Relations and Treasury for Pinterest.
Joining me on today's call are Bill Ready, Pinterest's CEO; and Julia Donnelly, our CFO. This conference call is being webcast, and we are also providing a slide presentation to accompany our commentary. Please refer to our Investor Relations website at investor.pinterest.com to find today's presentation webcast and earnings press release.
Some of the statements that we make today regarding our performance, operations and outlook, may be considered forward-looking and such statements involve a number of assumptions, risks and uncertainties that could cause actual results to differ materially. In addition, our results, trends and outlook for Q4 2025 and beyond are preliminary and are not an assurance of future performance. We are making these forward-looking statements based on information available to us as of today. and we expressly disclaim any duty or obligation to update them later unless required by law. For more information about assumptions, risks, uncertainties and other factors that could affect our results, please refer to our most recent Form 10-Q and Form 10-K, each filed with the SEC and available on our Investor Relations website.
During this call, we will present both GAAP and non-GAAP financial measures. A reconciliation of non-GAAP measures to the most directly comparable GAAP measures is included in today's earnings press release and presentation, which are distributed and available to the public through our Investor Relations website. Lastly, all growth rates discussed in today's prepared remarks should be considered year-over-year unless otherwise specified.
And I'll now turn the call over to Bill.
Thanks, Andrew. Good afternoon, and thank you for joining our third quarter 2025 earnings call. Q3 marks another quarter of strong execution against our multiyear strategy and long-term financial targets. Over the past few years, we've transformed Pinterest from a platform of window shopping, where users often found that all the stores were closed into an AI-powered visual first shopping assistant. We are digitally replicating the joyful experiences of walking the bazar or working with a great salesperson on your favorite boutique while seamlessly enabling our users to take action.
In an evolving competitive environment, Pinterest continues to distinguish itself as a destination for our users and a vital partner for our advertisers. To illustrate this point, nearly 85% of our users come directly to our mobile app, meaning we're not reliant on search engines or other third parties for traffic. We reached 600 million monthly active users in Q3, marking our ninth straight quarter of record high users with particular strength in Gen Z. Gen Z is our largest, fastest-growing cohort comprising over 50% of our user base and represents the next generation of users and shoppers who are influential tastemakers, content creators and a lucrative audience for advertisers to reach.
This momentum is also evident in key markets with our U.S. and Canada MAUs reaching 103 million, the highest level on our platform in the last 4.5 years. Importantly, 100% of our reported users are logged in giving us valuable first-party intent signals that provide an unparalleled view into consumer taste and preferences, which powers our recommendation engine and creates an even better user shopping experience. This combination of scale and intent continues to fuel our financial performance, with Q3 revenue growing 17% year-over-year to $1.049 billion, proving our role as a trusted partner to brands and agencies across the world.
Not only has our platform become a destination for shopping, we've also increasingly become a destination for search, in particular, visual search. Today, there are approximately 80 billion monthly queries across Pinterest, split across related items and other forms of visual search and traditional text-based searches. In Q3, all of these individual query types grew year-over-year on the platform. Overall, queries per user also grew year-over-year as we deepen engagement per user and user search more often on Pinterest. Related items in other forms of visual search are by far the largest source of queries and on our latest visual search features, in particular, queries grew the fastest at 44% year-over-year in Q3. These trends help to highlight how our AI investments are elevating our visual search capabilities and the relevance of our shopping recommendations. As a result, we are driving more of our engagement towards visual search, an area where we have a distinct right to win and is aligned with the visual search -- with the visual inspiration and discovery that our users have come to expect from Pinterest.
At the same time that we found our best product market fit with users, we've also built a performance ad platform that is harnessing our users' commercial intent and AI-driven automation to improve performance and simplify campaign creation for our advertisers. As a result, we've grown outbound clicks to advertisers by 40% year-over-year in Q3 and by more than 5x over the last 3 years. We have also broken into performance budgets, including achieving 5% to 10% share of total ad spend for some of the world's largest, most sophisticated advertisers.
Through continued product innovation, we see meaningful runway to expand our share of wallet with these large advertisers while also growing with smaller mid-market advertisers through continued improvements to our AI-powered automation suite, Pinterest Performance+.
International markets also remain significantly undermonetized, creating clear opportunities to increase monetization over the next several years across multiple growth levers. With these foundations in place, we see a clear path to sustainably grow our business and expand our market share.
AI is the heart of the Pinterest experience, working continuously in the background to understand our users' evolving tastes and preferences. Unlike chat or search platforms that wait for users to type a prompt, our AI is proactive. It anticipates what users will love next, curating a fresh feet of personalized recommendations that are ready, the moment they return, advancing their commercial journeys without the user having to ask, which is effectively the promise of agentic experiences. This is the magic of Pinterest, delivering a world of inspiration and individualized AI-assisted shopping for each user. In effect, this has made us an AI-powered shopping assistant for our 600 million monthly active users.
Importantly, through this experience, we are acting as a true partner to our advertisers. We don't disintermediate their traffic. We provide our users a seamless journey from visual discovery directly to the advertiser's product checkout page, helping our advertisers gain a customer, not just a transaction. This entire ecosystem is built on our core competitive advantage. A deep understanding of user taste, intent and product associations. Our AI is trained on billions of first-party signals from hundreds of millions of people actively curating and buying, which builds our taste graph. This unique first-party data then trains our AI to recommend deeply personalized and relevant content, often before users even -- can even articulate what they're looking for. This creates a powerful feedback loop. As we provide more value to our users by surfacing what they are looking for, they engage more deeply, further enriching our data and strengthening our ability to recommend relevant content.
This May, we launched a significant enhancement to visual discovery on Pinterest, our first-ever multimodal search experience, starting with women's fashion. This upgraded feature allows users to refine searches with more precision than ever by using both image and text inputs. Powering this experience is a proprietary in-house multimodal model trained on Pinterest's vast and unique data set, which is 30% more effective at identifying and recommending relevant content from our Corpus compared to leading off-the-shelf models.
Now we're testing ways to expand multimodal search and bring AI to the foreground of the user experience with the launch of our new Pinterest Assistant. With Pinterest Assistant, we are fundamentally enhancing the discovery journey on Penterest by transforming pure text-based search into a voice-activated conversational assistant. Now users can move beyond simple keyword text inputs to describing open-ended, complex questions and commands like, "What outfits might match this theme," and make these home decor ideas brighter and with a modern layout. Our AI technology services real-time inspiration that takes these conversational descriptors, runs them through our AI fine-tuned with our first-party signal and surfaces shoppable products from our catalog.
Additionally, by translating natural language queries and to curated visual results, we are also able to capture more nuanced commercial intent, providing us valuable signal to drive further personalized recommendations. We just began a beta rollout of Pinterest Assistant to a small set of test users in the U.S. We're excited about the opportunities that multimodal search can unlock and we'll continue to test this product over the coming quarters seek user feedback and expand access to a broader set of users over time.
AI is also being integrated to help move users through their commercial journeys in ways that are unique to Pinterest. A recent example is with Boards. As I've discussed in past quarters, Boards are at the heart of a user's inspiration to action journey and a superpower of our platform. hundreds of millions of our users actively saved to 15 billion boards organizing every aspect of their lives and creating an intent signal found nowhere else in the Western world. Importantly, users who use boards are more likely to revisit, less likely to turn and more likely to have deep recessions. Now we're using AI to make boards even more inspirational and shoppable, helping users move seamlessly from discovery to decision.
In the coming weeks, we will be introducing new trends and brands to our U-Can users with a new feature called Boards made for you. This feature brings timely curated collections of fresh and personalized content right into the home feed, with the goal of driving more frequent visitation and curation in introducing relevant shopping recommendations. With a blend of AI-driven recommendations and expert human curation, we're delivering personalized boards that help users discover new trends for them, see what others with similar styles and interests are loving each day and shop personalized weekly outfit ideas.
As part of our Q4 holiday go-to-market efforts, we're also launching the holiday edit, consisting of hundreds of new expert curated gift guides spanning 17 categories, including fashion, home, food, beauty, travel, parenting and technology. These shop boards feature gift ideas selected by celebrities in the know and Pinterest experts who understand exactly what to buy for every taste and budget. Through these initiatives, we're driving value for our users that they can only find on Pinterest, which in turn drives better engagement on the platform.
Our commitment to enhancing the user's journey from inspiration to action creates a powerful full funnel opportunity for advertisers. It allows them to connect with consumers at every stage, especially during the critical discovery phase where users have high commercial intent, but don't yet know exactly what they want to purchase. To that end, we recently launched a number of ad formats geared towards connecting users to shoppable products. For example, we recently launched top of search ads, now in beta in all monetized markets. These ads appear directly within the top 10 search results and in related pins ensuring that the brand's products are visible for shopping journeys most often begin and ahead of the competition. Since 45% of clicks occur in the top 10 search results, this placement is highly valuable. Our testing shows an average click-through rate of 29% higher for top of search ads compared to standard campaigns and a 32% higher likelihood of attracting new users who haven't seen or engaged with the brand's ads in the past.
For example, Tractor Supply Company leveraged top of search ads and an A/B test saw a 129% increase in click-through rate versus their catalog benchmarks. Last quarter, I highlighted our significant opportunity to enable new seamless shopping experiences across various categories on our platform. As part of that effort, we announced our new partnership with Instacart. -- which enables Pinterest ads to become directly shoppable via Instacart, allowing users to complete a purchase in just a few clicks. In September, we further expanded this functionality, which brings actionability to CPG advertisers with the launch of where to Buy links. Where to Buy links make standard ads instantly shoppable by surfacing multiple in-stock retailer options for a single product directly from an ad, all while allowing advertisers to receive valuable purchase intent data. With one tap, shoppers can view retailer options and choose their preferred one to complete a purchase.
In September, we also launched local inventory ads, where retailers can display real-time prices for in-stock items within a shopper's local store radius, adding a layer of convenience and actionability for users who want to know what's available nearby. These new ad formats are complemented by our ongoing focus on Pinterest Performance+, where we continue to drive adoption, increase functionality, enhanced bidding capabilities through features like ROAS bidding and subsequently drive increased advertiser spend. We're excited about the performance that Pinterest Performance+ is delivering for advertisers, particularly Pinterest Performance+ campaigns, our AI-powered suite of automated ad products designed to boost campaign performance by simplifying setup and optimizing delivery across objectives.
Pinterest Performance+ campaigns bundle a la carte features like P+ bidding, P+ targeting and Plus budgets into one suite to help advertisers reach the right audience and drive better results with 50% fewer inputs related to set up a campaign. Just one year since launching into general availability, we're extremely pleased with our progress and the performance we're driving for advertisers. For example, retail advertisers that spent on Pinterest Performance Plus campaigns have on average seen a 24% higher conversion lift than those spending only on traditional campaigns.
Additionally, Performance+ campaigns are also helping us deepen performance across a wide range of advertiser segments. Last quarter, we talked about how our Pinterest Performance+ campaigns was seeing a particularly strong product market fit amongst our mid-market enterprise and smaller advertisers as these advertisers value automated and simplified ways to optimize their campaign performance on our platform.
We continue to see highest adoption of this tool amongst our smaller and mid-market managed advertisers, who range from tens of millions to upwards of $100 million in annual gross merchandise value. As these advertisers adopt Performance+ campaigns, we are seeing them spend more on the platform. Among our mid-market and smaller managed advertisers, Performance+ campaign adopters exhibited on average a 12% higher monthly growth rate in spend on Pinterest post adoption when compared to non-adopters. While this cohort of smaller and mid-market advertisers represents approximately 15% of our revenue today, we see significant opportunity to continue to increase our share of wallet with this segment of advertisers.
We also continue to add new features and functionality to the Pinterest Performance+ suite. In Q1 2025, we launched Performance+ ROAs bidding, which provides more granular bidding functionality for advertisers and optimizes for conversion value. not just the volume of conversions. This is particularly impactful for advertisers that have a large catalog of varying price points. And while we are only 2 quarters into general availability of Road bidding, we're seeing promising early adoption. Globally, 22% of our lower funnel retail revenue now flows through ROAs bidding. And notably, as we drive adoption, we're increasingly seeing advertisers place bids against a greater portion of their catalog.
In Q3, the number of unique shopping SKUs with a paid ad impression grew more than 100% year-over-year. And advertisers using road bidding contributed the entirety of that growth.
Lastly, we continue to enhance our Pinterest Performance+ suite and be responsive to advertiser feedback. As an example, advertisers have requested additional transparency regarding the audiences their performance plus campaigns are reaching to supplement the performance metrics they already receive. As a result, we recently launched enhanced new reporting functionality and ads manager, offering detailed audience breakdowns, including age, gender and approximate location.
In short, just over a year since launching Pensions Performance Plus, I am proud of the value we've delivered for advertisers with meaningful opportunities still ahead of us. Now I'll turn to our international opportunity. International monetization represents one of our largest, most durable growth vectors, and we're still in the very early innings. Today, we have roughly 500 million MAUs outside of UCAN or 83% of our global users, evidence of our strong global awareness and product market fit with our users. However, these users represented just 25% of global revenue in Q3 2025, reflecting our historical monetization focus on U-Can.
While we continue to see opportunities to drive growth in UCAN, this imbalance creates the upside we're now beginning to unlock as we scale proven playbooks across our Europe and Rest of World regions and integrate more deeply with the advertising ecosystem in each of these regions. Our go-to-market approach is region-specific. In Europe, we lead primarily with our first-party sales team to serve advertisers directly. We're also focused on strengthening our relationships with agencies who manage and deploy much of the digital advertising spend in this region and who we view as vital partners in the ecosystem as well as integrating with marketing tech partners who help advertisers manage their creative and campaigns.
In the rest of world, we've deployed a hybrid model that blends our direct sales force in select markets, reseller partners in over 40 countries. And incremental third-party ad demand, allowing us to effectively scale growth in longer tail markets that were previously unmonetized or significantly undermonetized. Critically, we're exporting what already works in you can while localizing the implementation. Our lower funnel playbook focuses on increasing uploads of product catalogs and driving adoption of shopping ad formats and privacy-centric measurement. We couple that with Pinterest Performance+ to simplify campaign creation and improve outcomes for our advertisers. The result is a consistent, measurable path for advertisers to see performance and scale their spend on Pinterest. As an example, Pandora, a leading European-based global jewelry retailer leveraged many of Pinterest's best practices, including the adoption of Pinterest Performance+ across 100% of their lower funnel spend in existing markets, which drove ROAS lists across their campaigns. Additionally, Pandora adopted our conversion API, driving nearly a 36% increase in ROAS and after implementing off-line conversions drove a 148% increase in ROAS across priority markets.
International advertisers leaning into our shopping ad formats has been one of the clearest indication that our lower funnel playbook is resonating across the globe. 2 years ago at our Investor Day in September 2023, shopping ads represented just 9% of international revenue. In Q3 2025, it reached 30%. In fact, Q3 shopping ad revenue in both Europe and the Rest of World grew over 2x faster than the overall revenue growth of their respective regions. Despite this progress, we see significantly more opportunity to both activate and grow our share of wallet with international advertisers, particularly with the most sophisticated European and rest of world advertisers where we are currently underpenetrated.
It's still early, but we're making tangible progress narrowing our international monetization gap as measured by international ARPU relative to UCAN. Overall, I'm extremely proud of our team and the progress we are making across a number of initiatives. Pinterest is growing users across all the generations and geographies we track and has become a destination. Importantly, we're also growing queries, board creation and clicks to advertisers faster than users, meaning we're deepening engagement per user across the dimensions we want even as users have more alternatives than ever for search.
With that, I'll turn the call over to Julia to share more details about our financial performance.
Thanks, Bill, and good afternoon, everyone. Today, I'll be discussing our third quarter 2025 financial results and provide an update on our preliminary fourth quarter 2025 outlook. All financial metrics, except for revenue will be discussed in non-GAAP terms unless otherwise specified, and all comparisons will be discussed on a year-over-year basis unless otherwise noted.
Now let's start with our third quarter results. We ended the quarter with 600 million global monthly active users, or MAUs, growing 12%, our ninth consecutive quarter of record high users. We continue to demonstrate user growth across all of our geographic regions. In Q3, our U.S. and Canada region had 103 million MAUs growing 4%, our Europe region had 150 million MAUs growing 8%, and then the rest of world markets, we had 347 million MAUs growing 16%.
Shifting to revenue. In Q3, our global revenue was $1.049 billion, up 17% on a reported basis and 16% on a constant currency basis. We saw strength across our conversion and awareness objectives. Across verticals, we continue to see strength led by retail as well as by smaller, faster-growing categories on our platform, including telecom and entertainment. We also continue to see a normalization within CPG, driven largely by our food and beverage subvertical.
Turning to our geographical breakouts for Q3. In the U.S. and Canada, we generated $786 million in revenue, growing 9%. Strength came from retail, CPG, Telecom and entertainment. In Europe, revenue was $193 million, growing 41% on a reported basis or 34% on a constant currency basis. Strength in Europe was driven by retail. Revenue from Rest of World was $70 million, growing 66% on a reported basis or 65% on a constant currency basis.
We're pleased to deliver the strong 17% third quarter revenue growth which exemplifies our multiple ways to win that I've spoken about for many quarters. We continue to diversify our business across geographies, grow long-standing as well as new advertiser verticals and begin to deepen our share with mid-market and smaller advertisers. We did face pockets of moderating ad spend in UCAN in Q3 as larger U.S. retailers navigate tariff-related margin pressure in the current environment. However, as Bill noted, we also saw accelerating strength across our international geographies in Q3 as we have begun to successfully export our lower funnel playbook around shopping.
In Q3, overall ad impressions grew 54% and while ad pricing declined 24% year-over-year. The primary driver of the continued strong growth in ad impressions and corresponding decline in ad pricing continues to be the growing mix shift from ad impressions in previously unmonetized or undermonetized international markets, which carry lower ad pricing than our more mature markets.
Moving to expenses. In Q3, cost of revenue was $206 million, up 13% year-over-year and up 5% versus Q2 due to increased infrastructure spend related to our user and engagement growth. Our non-GAAP operating expense was $543 million, up 15%. The increase was due to investments in sales and marketing and R&D as we continue to invest in headcount to support our AI and other product initiatives as well as our sales force.
Our revenue growth, combined with our disciplined approach to cost led to another strong quarter of adjusted EBITDA coming in at $306 million, a margin of 29%. Adjusted EBITDA margin expanded 170 basis points versus Q3 last year and helped to deliver Q3 free cash flow of $318 million. This speaks to the inherent profitability of our business and highly cash-generative nature of our model with over 90% of our adjusted EBITDA converting to free cash flow over the trailing 12 months. We ended the quarter with cash, cash equivalents and marketable securities of $2.7 billion. As a reminder, we've previously discussed the 4 pillars of our capital allocation framework, which remain unchanged. First, investing in product and technology innovation; second, balance sheet optimization; third, preserving flexibility for opportunistic and disciplined M&A; and fourth, dilution management. To that end, as part of our ongoing efforts to mitigate dilution from employee stock-based compensation, in Q3, we allocated $199 million towards share repurchases and $115 million toward net share settlement of equity awards, thus bringing fully diluted share count roughly flat year-over-year.
Now I'll discuss our preliminary guidance for the fourth quarter. We expect Q4 revenue to be in the range of $1.313 billion to $1.338 billion, representing 14% to 16% growth year-over-year. Our guidance assumes the impact of foreign exchange to be approximately 1 point of tailwind based on current spot rates.
Moving down the P&L. We expect Q4 2025 adjusted EBITDA to be in the range of $533 million to $558 million. We anticipate Q4 2025 non-GAAP cost of revenue to grow sequentially from Q3 2025 by high single-digits percent. Within Q4 non-GAAP operating expense, our primary area of investment will continue to be headcount growth within R&D to support our efforts in AI and other product initiatives as well as our global sales team. Our Q4 adjusted EBITDA guidance confirms that we will continue to expect adjusted EBITDA margin expansion in the second half of 2025. We Consistent with our commentary on our last earnings call, the level of expansion in the second half will be lower than the more elevated expansion we delivered in the first half of 2025 as we continue to invest in revenue-driving initiatives. Overall, we are pleased with our progress in 2025 towards our long-term adjusted EBITDA margin targets and our ability to continue generating significant free cash flow.
In closing, I'm proud of our team for another strong quarter as we continue to deliver for our users and advertisers. With that, I'll hand it over to Bill for some final words.
Thanks, Julia. I want to thank our teams at Pinterest, our advertising partners and all the people that come to Pinterest to find inspiration and take action.
And with that, we can open the call up for questions.
[Operator Instructions] The first question comes from the line of Ron Josey with Citigroup.
2. Question Answer
Great. Bill, a bigger picture question for you, and then Julia, I had one for you. Bill, on the future of e-commerce, I would love to get your thoughts on agentic Commerce, agenetic search and how everything is evolving here. and specifically interest opportunity and strategy given its evolving landscape and then clearly with the launch of Pinterest Assist? And then, Julia, I think you mentioned some pockets to growth in UCAN given tariffs. Wondering if this continued or if things have normalized since then. .
Thanks for the question, Ron. So one of the things I'm most proud of when I look at our results, particularly over the last 3 years is the strength that we have had with users, 9 straight quarters of record high users, in the fact that shopping has been at the very center of the resurgence of our platform. And the core of that is that we've effectively become an AI-driven shopping assistant, as I discussed in my prepared remarks.
And to go a little further on that related to your question on agentic. Pinterest is proactive. It anticipates what users love without the user having to ask. Effectively, that is the promise of agentic that AI is working for you without you having to tell it what to go do. And that's exactly what users experience on Pinterest every day and what is leading to that deep engagement that we understand their style and taste and preferences so well. that every time they open the app, they're getting great new recommendations from our AI-driven systems, and we're making those more and more helpful as evidenced by the Pinterest Assistant that we just announced. We're clearly not standing still. We're going to continue advancing that, and we're going to continue to be centered on our strength in a visual first experience. But adding voice, bringing more of the AI to the foreground, we think will take us further into that AI-driven journey for the user. And our focus, to be clear, is in guiding the user through the decision-making journey. We believe that is the most impactful part of the promise of Agentic.
From a buying perspective, we deliver great buying experiences for our users. For example, we have push button buying with Amazon linked accounts. That's a great experience. We have millions of users using that today where they can buy right within our platform. And if we see users saying they want the AI to push the button for them, that's not a technically complex thing for us to do, but we think actually the more differentiated thing is how we're guiding the user through that journey helping them go further down the commercial journeys every time they come back to our app.
And it's also worth noting, as you've seen other AI platforms really burst onto the scene AI, open AI at 800 million users, that's branded over the last few years. But even if that has happened, we've delivered 9 consecutive quarters of record users while deepening engagement across the metrics that we want, including on search. And within that, a 44% increase in queries in our latest visual search features. So we think that is really clearly demonstrating that we've carved out a unique space for ourselves there. And where -- when you think about that broader promise of agentic AI working on your behalf to guide you through those earnings, I think we are at 600 million-plus monthly active users, I think we are one of the most popular places for us to go in that and doing something unique and distinct from others. And then on the cost side of that, I think there's -- it's really important to understand that just as we've been talking about, our ability to go align the AI with great monetization continues. The cost implications there it's not only about us aligning the assistant with our ability to monetize and how that is renewing great search results that are highly commercial in nature. We have our own proprietary and compact fit-for-purpose models that perform really well. And every pen we serve today is driven by that, and that's really already in our cost structure. And when there are things that we need to do with broader LLM capabilities, we are constantly doing side-by-side testing between both the leading off-the-shelf proprietary models and open source models.
And one of the really, really interesting things that we're seeing is that we are just getting tremendous performance from open source models, specifically for Pinterest use cases on visual AI given current market rates and per ton costs in early testing, we're seeing orders of magnitude reduction in costs with comparable performance using fine-tuned open-source models versus leading off-the-shelf proprietary models. So going forward, we think open source can be applied to many more of our use cases and at a fraction of the cost of the larger model providers using open source. So again, we feel really good about the value that we're bringing to the user there. our ability to align that with monetization and our ability to control those costs and deliver that effectively.
And then, Ron, the second part of your question, I'd say overall, with respect to Q3, the quarter played out largely as we expected. In addition, we saw some of the pullback from some U.S. retailers spend from Asia-based e-commerce players in the U.S. was down year-over-year again in Q3. So relative to Q2, we did see a partial recovery there. As we think about guidance for Q4, our Q4 guidance range is 1 point lower than our guidance range was for Q3 as we see these broader trends and market uncertainty continuing with the addition of a new tariff in Q4 impacting the home furnishings category. So I think overall, we still feel really good about our mid- to high teens kind of revenue growth targets over the medium and long term and the durability of our revenue growth.
There are several areas of momentum in our U-Can business that continue that you've seen over the last several quarters. So One of those has been momentum in emerging verticals, also momentum in smaller and mid-market advertisers and then some of the international opportunity that Bill touched on in his prepared remarks. To put this into perspective, some of these emerging verticals in the U.S. like financial services is nearly a $40 billion digital ad category in the U.S. we estimate that we have less than 0.5 point of market share there, and that category has been growing really nicely for us for some time. We expect this to translate into further share gains in this and other emerging verticals like travel, entertainment and telecom Likewise, smaller and mid-market advertisers today represent only 15% of our revenue as our priority has been to solve the needs of larger enterprise advertisers first. But we're seeing nice tailwinds as these smaller and mid-market advertisers adopt Performance+ campaigns, and we plan to continue to invest more into growing this segment. So while all these initiatives continue to play out over time and that's going to take time to play out. We're confident we have the right playbook to drive further growth, including an UCAN moving forward.
The next question comes from the line of Eric Sheridan with Goldman Sachs.
Maybe building on that answer, just Bill, can you characterize more broadly the digital ad environment that you find yourself operating in, representing Q3 what you just reported and sort of the building back of Q4? And Julia gave some really good color there with respect to UCAN. Can you characterize what you're seeing in UCAN relative to the rest of your operations globally against that broader ad environment?
Thanks, Eric. We're pleased with another strong quarter in Q3 at 17% revenue growth. And as I'm sure you've noted, we've been quite consistent in our growth and in line with the long-term targets for revenue and margin that we laid out at our Investor Day 2 years ago. So we continue to feel good about that mid- to high teens revenue growth target over the long term that we laid out at Investor Day and our ability to consistently deliver. It's also really important to know this gets to your sort of question on sort of the broader environment. It's also important to note that we grew 17% despite operating in an environment where some of our largest retailers in UCAN pull back spend across the industry, not specific to us, a pullback across the industry as a navigated tariff-related margin pressure. And we think that's disproportionately impacting large retailers, but that is a segment that we have more exposure to than other platforms given our focus on shopping though we continue to grow in other verticals and segments of the market in addition to those.
Additionally, as advertisers are adopting AI-driven platforms, there's a next level of optimization in the AI ad platforms that's taking place right now, where bidding is getting further aligned to advertisers measurement sources of truth and more events that lead up to a conversion or being incorporated. We think that presents an upside opportunity moving forward. We began that journey earlier this year with road-based bidding, and we've seen good results there. For example, after launching ROAS bidding in Q1, we saw a 100% increase in shopping SKUs with paid ad impressions across the platform in Q3. And has driven entirely by ROAS bidding adopters, as I noted in my remarks, and more of those advertisers are uploading greater portions of their product catalog. We've talked about that opportunity to get deeper into the catalog even of our largest advertisers. We think this will continue to help us do more of that. Going forward, we see meaningful potential to expand further into AI-based optimization of other events that are valued in advertisers' measurement sources of truth. And while many advertisers have adopted these solutions first with the larger platforms as typical of the adoption cycle, we are testing this with some of our largest partners, and we're seeing really good early results. Certainly, more of that is in front of us than behind us. But the good news is that the alignment of AI bidding with the advertisers measurement source of truth is market expanding. I think we've already seen that reflected in some of the larger platforms and what they have been out in the market with. And that tended to give more credit to events leading up to a conversion, such as view through attribution, which should be good for a full funnel platform like Pinterest. So this should accrue to our advantage in future quarters as we continue to roll out those features are very early on our platform now, but we are seeing good early results. And through our broader deployment of these additional Performance+ solutions in 2026, we think there's continued opportunity there. So we know we're driving performance for advertisers. Clicks to advertisers increased 40% in Q3 and clicks to advertisers outpaced revenue in all of our reported geographies. In fact, Clicks to advertisers were up over 5x over the last 3 years. But clearly, we have more to do to get proper credit for that performance.
The next question comes from the line of Rich Greenfield with LightShed Partners.
Question -- seen that's allowing users to actually remove AI content. I guess the big question is, how do you know what's AI generated? What's not? And why did you make that decision? It seems like a lot of your peers are actually encouraging and want AI content because they want more content to keep people even more engaged, to sell more ads or to build the business. And so it seems like you're sort of doing the opposite, and I'm curious or maybe allowing the opposite versus doing the opposite. Why and help us understand how this all works and why you're doing it?
Yes. Thanks for the question, Rich. So it's a really great clarification. And overall, we see Gen AI created content as a big tailwind for our platform, and we are very much embracing it. Part of embracing it is addressing content quality. And we address content quality primarily through our recommender systems, but then also by giving users choice and saying what they want to see. And so I think you've heard this across pretty much every platform out there, that there are some users and some use cases that would like to see less AI-driven content. And so we're simply giving the user choice, but we're also leveraging all the really great AI-generated content that is available out there. And I think this is not dissimilar to what's happened in prior expansionary moments with content, whether you think about what happened with online video or short form video or the ability for everyone to take a photo with their phone, initially, people react to changes in the volume of quality leading to some examples of lower content quality. But if you have recommender systems that can really parse what's great quality versus not great quality, then you can give users the best of that expanding content corpus. And when you look at the engagement on our platform, I think that we -- I think that demonstrates that we're doing a pretty good job of parsing all that great influx of AI-generated content that's out there and figuring out what's going to be relevant for which user at which moment in time. And then what we're doing is augmenting what our recommender systems can do with the user's ability to give us direct feedback if they want to see less AI-driven content. You do have some use cases where someone might say, well, hey, I'm looking for a specific thing to provide architecture on my home. And so I need to know it's a real picture of something that could actually be built versus something that is AI generated. I think over time, users will accept more and more of that as the quality filters get better and better. But again, overall, we see gene content as a significant tail on the platform already. And it's really about getting the content quality right, which primarily we do behind the scenes on our users' behalf, but we're giving them tools to say when they want to see more or less.
And then specifically to your question of how do you tell. I would say there's not a precise ability for any platform to catch 100% of what is AI generated. There are some industry-level tags that we would act on. There are also things where we're looking at metadata and other indicators that give us indication of that. But that's why we say see less, not see none of because the ability to precisely spot that is not perfect for any platform. And I would just say, over time, I think it will get to a place where almost every piece of content you see will have been at a minimum edited by AI in some form or other -- and there are analogs is if you think back to -- it used to be that people would get really sort of intense or some people get in a sense if photos had been photoshopped. Well it has long since been the case that nearly everything you would see out there would have been not just Photoshop, but you have filters and all these things that even the average person can do. We think that over time, almost every piece of content you see will have been AI modified in some way, and it really will come down to content recommendation and content quality. But in the near term, we're giving users choice and allowing them to express what they want to see in honoring that choice.
The next question comes from the line of Shweta Khajuria with Wolf Research.
I was wondering if you could please talk about your relationship with Magnite and more broadly about your efforts to add new sources of demand and perhaps time line around that?
Thanks for the question, Shweta. We've been very consistent from the beginning as we think about our programmatic and third-party strategy. Our first-party ad demand continues to be the primary driver of our growth. with third-party demand really complementing and rounding out our auction when there may be gaps in the auction.
With respect to Magnite, when we announced that, we said it would take time to integrate test and doing more fulsome go-to-market. We're still working through that testing now, and we're in the early days. Today, most of our efforts have been with respect to 3P have been focused on bringing on new sources of demand on the platform as many of these programmatic budget pools are large and new to Pinterest today. So we continue to see that consistently with how we have before. But I would also call out that there's a next potentially meaningful opportunity that we're also starting to look at that we think that we think we bring a unique audience to these budget pools given the high intent nature of our audience and the visual discovery that uniquely occurs on Pinterest. So as a result, we're also starting to explore very early testing how valuable our audience could be even beyond our own platform. When you think about the very strong commercial intent that we see with our users, obviously, we satisfy a lot of that commercial intent on our platform, but we think that could be helpful beyond our platform. So we're in very early days of testing that.
The next question comes from the line of Mark Kelley with Stifel.
Bill, I appreciate the extra color on Performance+ tonight. I was hoping maybe we could drill into the SMB and kind of mid-market opportunity, just a little bit more. I know you threw out that -- that's that, the 24% higher conversion rate. Is that pretty like standard, whether you're a smaller advertiser versus a more sophisticated and larger brand? And then second, maybe just to clarify, the 10% to 15% of revenue running through P+, was that just an SMB and mid-market stat? And where might that go over time?
Thanks for the question, Mark. So first of all, we feel really great about Performance+ and how well that's working. we're not even a year end to the deployment of that. And as a reminder, the larger platforms are many years into their rollout of this. So we're at year-end, and we feel great about the progress that we've made. People's campaigns or bundled suite of AI-enabled automated features. It's really driving much better performance and reducing the inputs, 50% fewer inputs. So I called a little bit of this out, but for example, retail advertisers using performance plus campaigns are seeing a 24% higher conversion lift versus traditional campaigns. It is also helping significantly as we have bent the smaller and mid-sized advertisers, those tens of millions or hundreds of million -- $20 million to $100 million of GMV, who really value that automation. And for that segment, we see a 12% higher monthly revenue growth rate of adopters of Ps campaigns versus non-adopters and approximately 15% of our current revenue the segment is growing nicely. So there's a lot more to do to deepen share of wallet there. And again, as a reminder, this is a segment of the market that larger platforms have had much more exposure to. We are earlier on this segment of the market. But P+, we see as a significant unlock there and it's having exactly the effect of intended, but we still have a lot more of that opportunity in front of us than behind us. So we're quite excited about what we're seeing from Performance+ there.
And then on the larger segment of this, ROAS bidding, as we've talked about, is really helping us get much deeper into the catalog of our -- of the largest retailers out there. So I've shared 22% of retail lower funnel revenue, both enterprise and SMB. So -- and that's just launched in 2 quarters on ROAS bidding. So road bidding is really having quite an effect. And I shared how much is getting us into many more SKUs. So when we think about ads as relevant content, we want to make sure that we have ads that line what you are actually looking for, getting a much larger portion of large retailers catalog on our platform is super helpful to that and ROAS bidding as a subset of Performance+ we rolled out over the last couple of quarters, effectively has doubled the number of SKUs with a -- that are delivering a paid impression on our platform. And it's because that ROAS bidding allows advertisers to more precisely tune really the AI tunes for them across catalogs with high variation in price points and margin points and those kinds of things. And so we see really great progress everybody I think there's a lot more of that to go. So when we think about, I would just say our opportunity globally, but specifically UCAN, even as we think about growth in UCAN it's really 3 things: the expansion into the full catalog with the largest retailers, driven by more granular bidding like ROAS bidding from Performance+. And so -- we've got good results of that. We're just a couple of quarters and a lot more to do there. They can get us deeper into the catalog to the largest retailers. And then secondly, it's mid-market and SMB driven by Performance+ where we're just getting started in that segment of the market, but seeing really good promising early results. And then the third point that I alluded to in one of my prior answers, the AI-driven alignment of bidding and bidding systems to the advertiser measurement sources of truth. That's giving a clear view of full-funnel attribution and events across the funnel. And other larger platforms have fully roll that out. We are just getting started testing on some of our legist advertisers. We're seeing really promising early results there. So we think that will -- that's having an expansionary effect that you're seeing with some of the largest platforms out there. We think that's a real opportunity for us as we look into next year. So hopefully that helps give a little more color on the broader sort of things we're thinking about with Performance+ there.
The next question comes from the line of Ross Sandler with Barclays.
Great. Just want to bring Julia in on key investment priorities for next year. And how do we think about the pace of EBITDA margin expansion in '26 compared to the pace we're seeing in second half '25? And then, Bill, just a follow-up on the agentic question. So Walmart's integrating its catalog into ChatGPT for this checkout service. I know it's early days, but for something like that, do you view that as neutral, positive, negative in terms of where that kind of a marketer might move their Pinterest ad budget in the future? Is this going to help you guys or potentially create a new headwind? Any thoughts there?
Thanks, Ross. I'll take the first question. So it's still a bit too early to talk specifically about 2026 as we're still reviewing those plans internally. But stepping back, we still feel confident in the long-term margin targets that we provided in 2023. And at that time, just as a reminder, we said we would target a 30% to 34% adjusted EBITDA margin over a 3- to 5-year time horizon. So now here in 2025, we're already approaching 30% for the full year. So we've made a lot of progress already by growing the top line while investing thoughtfully primarily in R&D and to a lesser extent, the sales area as well. So looking forward, we continue to see many investment opportunities with high ROI, particularly across AI. Power user experiences, including our new Pinterest Assistant, which we believe will help keep us on the leading edge in visual search and discovery as well as ongoing investment in our performance ads platform.
On the gross margin line, in aggregate, we expect cost of revenue next year to grow more in line with the business going forward, so there can be some variations quarter-to-quarter, and there are a few factors at play there that I'll call out. Cost of revenue, which is mostly our infrastructure costs will naturally rise, of course, due to kind of ongoing user and engagement growth. Additionally, we've previewed for multiple quarters now on several calls that we expect to see diminishing returns from the infrastructure cost optimization work that we've undertaken for the last 2-plus years. Now partially offsetting this kind of natural upward pressure on cost of revenue is the fact that we're able to apply AI use cases sort of directly in service to monetization, where we see immediate revenue lift, right? So we're not rolling out new features and then planning to monetize them years later. They monetize right away. So part of our general philosophy. We're also being cost efficient with our model usage, including, as Bill alluded to, utilizing open source models where applicable that come at a meaningful reduction in costs. So -- in summary, we continue to stand by our long-term adjusted EBITDA margin targets that we've always said, though, that the rate of adjusted EBITDA margin expansion would vary year-to-year. We've made a lot of progress towards these goals, and we'll continue to be thoughtful about how we invest moving forward as well.
And then following up on your agentic commerce part of the question, Ross. A couple of things I'd say. One is that for the largest retailers, we have catalog integrations. I shared how we're getting deeper into their catalog with our Performance+ capabilities and root level bidding and things like us getting a much broader part of the catalog available for ads, but we have those catalogs for organic shopping for push button type buying and linked accounts. We have that with Amazon. We've had that for some time in millions of users on Pinterest to take advantage of that and have a great experience. So we feel really great about the shopping experience that we're providing. And I think overall, I would just say it's worth noting that there's an expansionary moment happening with search generally. And I think users just as I did in an app-driven world, are thinking about different places to go for different types of experiences. Traditional search was always great for things like product research. And I think broad-based chat bots are sort of the next evolution of that sort of research type of shopping behavior if you're trying to figure out like every attribute of the latest 4K Ultra TV or things like that. Search was -- traditional search was always great for that, and then chatbots are even better for that. But we're solving a different type of shopping journey on Pinterest, really the more the -- I'll know when I see it a tight problem. And the best evidence I can share of users think about these things as distinct and separate is that over the last couple of years as you've had an explosion of usage in AI chat bots, we've put up 9 straight quarters of record high user growth, shopping being at the very center of that. And it's because we're taking a visual first approach driven off the human curation that happens on our platform where we just understand user style and taste and preference. We just have a unique signal is completely distinct from any place else in the western world, and that's why we're able to do things like what we've showed on our -- the relevancy of our latest multimodal visual search models, where we're able to outperform the off-the-shelf models by over 34 percentage points on the relevance of shopping recommendations on our platform. That just gets you to a bit of the kind of unique things we're able to do with users. And so I think, again, it's a market-expanding moment. Multiple players are growing simultaneously. And very clearly, we are one of those players that is growing, delivering a lot of value for users a tremendous of shopping occurring on the platform. And in terms of not searching happening on the platform, I shared that in my prepared remarks, the 80 billion-plus monthly queries, the vast majority of which are visual in nature, which just, again, gets to how we're doing something that's very different than traditional search or even what chatbots are doing. So hopefully, that helps contextualize that.
The next question comes from the line of John Blackledge with TD Securities (sic) [Cowen]
Great. PINS historically has had all of its infrastructure running through AWS. Given the move in recent years of companies shifting to multiple cloud vendors, how should we think about PINS potentially diversifying to other cloud platforms?
Thanks, John. So first, I'd say we view our infrastructure and platform as strategic assets that support our performance, reliability and our AI road map. And on a fantastic partner for us, to be very clear. But in the same way that we are constantly testing all the various LLMs and benchmarking different LLMs across one another. We're also constantly assessing the best infrastructure options for us as we move forward, especially in an AI-driven world. And that infrastructure includes LLM, chip providers and hyperscalers. So again, if you look at what we've done over the last few years, you've seen us put AI at the center of our business, really effectively align that with the ability to monetize for users to deliver great results for users and do so cost effectively. And again, we've had great partnerships there. But the space is evolving rapidly, and we continue to pay really close attention to that and Denmark across multiple providers on each of those sort of layers of the stack. Hopefully, that's helpful.
This will be the last question from Michael Morris with Guldenheim.
Bill, you referenced a couple of times deepening engagement per user. And I'm hoping you can add some context to that. Are you talking about time spent per visit or frequency or some other metric? And do you see that as a leading indicator of reaccelerated growth in the UCAN market? And then secondly, on international, the growth there is significant. That has accelerated. How much runway do you fee to continue to grow internationally at that elevated level? And maybe -- you gave us a few drivers, but what do you see as the 1 or 2 key drivers as we look forward?
Yes. Thanks for the question, Mike. On the DP engagement per user, we talked about this very consistently over many quarters now is that we are deepen engagement per user across the areas that we want, which are around search, curation, clicks and actions. And I share a little more color on this call around the search behavior where we are getting more searches per user. So it's not just our searches are growing, we are getting more searches per user. We are getting it in the ways that we won't particularly on where we are very highly differentiated around our visual searches related items and other forms of visual searches drive the vast majority of that search behavior, but it is more searches per user happening on our platform even as we put up record high levels of users and also significantly growing actionability last year, just how much the clicks to advertisers have grown 5x over the last 3 years, we're driving a tremendous amount of clicks to advertisers. So it is that great relevancy driving great recommendations that leads to actionability that leads to more users coming back for more searches and more actions like that is that flywheel is spending on the deepening user engagement.
And to your question around is that a leading into monetization, I think absolutely yes. What I would say is that 3 years ago, Pinterest was pretty much upper funnel only. We've had a major transformation of the business, both in terms of user engagement, which, again, I think, continues to be the brightest spot in the business. And advertisers will always follow where users and commercial intent are. We stood up a performance ad platform pretty much from scratch over the last couple of years. And we are still a long way from having the capabilities of the very largest platforms. But even as we've made the basic capabilities of that available, we've really broken into those always on performance budgets. We have a lot more to do there. And with UCAN specifically, I shared those sort of 3 areas where I think there is significant opportunity around getting deeper in the full catalog of the largest retailers mid-market and SMB that are really driving a lot of the growth across the broader market, but it's a newer area for us. And the alignment of AI bidding systems and advertiser and sauces giving a clear view of full funnel attribution. I think those are things that will help us capture more of that value that we are driving. But I do think absolutely yes. Is generally true that user behavior is a leading indicator of where the advertiser dollars are going to follow. And we have the largest platforms are many years into their AI-driven ad systems, we are only a couple of years into ours. But because the user behavior is so strong, that's what's really letting us make progress.
And on the international side, as I shared in my prepared remarks, the playbook that we have used in UCAN, we are now exporting and we're seeing that really take hold internationally. We are still early on in our work there. We have a lot more of that opportunity in front of us, but we're really pleased with the progress we've made and how it's starting to show results. As I noted in Q3, Europe ARPU grew 31%, while rest of world ARPU grew 44%. We have a lot more of that to do. And I shared in my remarks, how shopping ads are really at the center of what's driving that. So is that commercial -- commercial behavior. So a lot more of that to go, but it's what's working in U.K. is exporting well. And again, to put it in perspective, 2 years ago at our Investor Day in September of '23, shopping ads represented just 9% of international revenue. In Q3 of 2025, it reached 30%. So Q3 shopping on revenue in both Europe and Rest of World grew over 2x faster than revenue growth of their respective regions. So we believe there's many years of runway of continuing to grow ARPU as we increase product catalogs, add additional ad demand, drive up relevance and thus, our ability to take a bad load, certainly for international, but again this year, we think there's a lot more to do in you can as well.
Thank you. I will now hand the call over to Bill Ready, CEO, for any closing remarks.
Thanks again to all of you for joining the call and for your questions. We look forward to keeping this dialogue going, and we hope you enjoy the rest of your day.
That concludes today's conference call. Thank you. You may now disconnect your lines.
Pinterest — Q3 2025 Earnings Call
Pinterest — Goldman Sachs Communacopia + Technology Conference 2025
1. Question Answer
Okay. I think with that, we're going to get going on the next one. Okay. So it's my pleasure to have the team from Pinterest here for our second fireside chat of the day. With me is Bill Ready, CEO. I'm going to read a quick safe harbor, and then Bill and I are going to get into the back and forth into the dialogue. So some of the statements that Pinterest will make today may be considered forward-looking. These statements involve a number of risks and uncertainties that could cause actual results to differ materially. Any forward-looking statements that Pinterest makes are based on assumptions as of today, and Pinterest undertakes no obligation to update them. Please refer to Pinterest's latest Form 10-Q and Form 10-K for a discussion of the risk factors that may affect its results. Okay. So we've put the safe harbor behind us.
Bill, thanks, as always, for being part of the conference. You've always been great about making yourself available. So I really appreciate it. To level set, here we are. We're in the second half of 2025. I wanted to talk a little bit about your key strategic priorities for the business, how they've been progressing as you move through '25 and we will use that as a jumping off point for the conversation.
Yes. Excellent. Well, we did our Investor Day almost 2 years ago now and strategy has been consistent with that. And I think if you look back at that our execution has really aligned very directly with what we laid out there, both in terms of what we're doing and the results that it's delivering. So on what we're doing, our strategy to make Pinterest a shopping destination with visual search curation and AI fueled off that unique curation behavior has really played out. And then leveraging that to turn Pinterest into a true performance ad platform. And so the things that I'd point to with that 8 straight quarters of record high users. Gen Z is now more than 50% of the platform.
So 3 years ago, when I came in as CEO, users were declining, the narratives of the Pinterest was aging up and aging out. This strategy has been so successful that 8 straight quarters of record high users. Gen Z is now the largest, fastest-growing demographic, over 50% of our users.
We're growing across all geographies, all generations that we track. And at the core of that is the shopability of the platform. And the shopability of the platform is being driven by using AI, tuned on a unique curation behavior within Pinterest. It's truly unique in the Western world. in terms of users making -- we have nearly 600 million users on the platform and what they're doing is associating products all the time and associating products as to like what products go together, what fits their taste and style and that curation signal, this is the thing I saw from my prior seat at Google is like in this AI-driven world, if you have unique signal, you're going to able to do really unique things with the AI and that's really at the heart of why it's not just that we're winning with Gen Z.
Again, we're growing across all the generations that we track. Shopping is at the core of that, driving that actionability, the performance ad platform also using AI to drive results for advertisers all that has hung together really well. And you see that delivering the solid mid- to high teens growth that we talked about at our Investor Day as well as helping us drive margin expansion cash flow generation while also being more relevant to our users than we have ever been with our best product market fit ever.
Got it. And in terms of just on the go forward, how should we think about how some of those priorities might change looking out over the next 12 to 18 months, if at all?
Well, a couple of things I'd say. So we see that strategy working exceptionally well. A good strategy has multiple phases to it. And I'd say, over the last 3 years, we've laid a lot of foundation on these things. But we've created a flywheel effect on multiple of these. We also talked about this at our Investor Day as well, that the ads can be great content when we have shopping behavior when the users in a commercial context, they don't care whether it's organic versus ads as long as you show them the right product.
We're making that flywheel spin, but we're also using the AI to drive better and better visual search capability. So the way this manifests for users, if you ask Gen Z why they're coming to Pinterest, One of the first things they'll say is, well, Pinterest just gets me. Well, what's behind Pinterest just gets me. It's using the AI to make really, really relevant shopping recommendations. And now we're bringing that -- we started laying foundation with AI in the background around recommendations. Some of the things you're starting to see us doing this gets more to your question of like what you can expect going forward.
We're bringing more and more of that to the foreground now, right? So with our visual search that we talked about. Visual search. Visual search has sort of always been at the core of Pinterest, but the visual search keeps getting better and better. I shared that our latest multimodal visual search models that are proprietary and in-house trained on our unique signal are outperforming off-the-shelf models by 34 percentage points on the relevancy of their shopping recommendations and so that's the tech behind it, but that's letting us do great new experiences directly to the user around how they can search individual elements of an image, how they can curate more and more of the individual elements of an image.
And starting to bring things to the user that also give them more language when they didn't have it. What we're really competing for is visual search. And in that world, what we're solving is the -- I'll know it when I see a problem. It's very different than the way sort of chat bots and general purpose search pursues that. We're solving the I'll know when I see a problem, and that is working quite well. In fact, so well. Adobe put out a study, it's not something we sponsored and independent of us. But that's 39% of Gen Z starts their searches on Pinterest. So how well is that shift to visual search and using the AI going, 39% of Gen Z is saying they start their searches on Pinterest.
So expect more and more of us bringing purely visual experiences, AI forward, helping people solve more and more of their commercial journeys with a great visual search experience with AI at the foreground.
So maybe just 1 quick follow-up on that. So with visual search at the core, when you think about -- and you actually have a background in this from your time at Google, how do you think about the shifting competitive landscape for search and positioning Pinterest visual search against your world view for that competitive landscape.
It's a great question. So step back a little bit, even before you got to the sort of latest round of AI, search has been fragmenting for years, right? Google continues to be fantastic for general purpose search. But over the last 15 years, you've had lots of even as they were growing very nicely, search fragmenting and competition increasing. How many products searches start on Amazon versus Google? How many travel searches start on a Booking or an Expedia rather than Google. And so there's been this sort of fragmentation and verticalization of search, it's been a decade-plus long trend. My view with Pinterest was not that we would go solve general purpose search and compete for anything that you might search for, but that around purely visual search, particularly shopping at the center that was an ownable space.
And particularly, one of the things I've talked about before that the first 25 years of e-commerce sort of solved buying, but killed shopping. The distinction being that the utilitarian part of the journey had been solved. If I knew what I want -- if I knew what I wanted, there were tools, Google, Amazon or the things that would help me get it the cheapest and the fastest. But if I didn't yet know what I wanted, if I didn't have the words to express what I was looking for, there weren't great tools for that. And if you look at the 75% or so of commerce that still exists outside the digital world, that's a lot of what people are doing is well, "Hey, I need to go look, I need to go sort of walk through a store, I need to go walk to bazaar, how do you solve that?"
Well, that's an entirely new space in my mind. And I think you're seeing that that's -- we're being quite effective at solving for that. And it's a rapidly growing pie. Even as search fragments, the pie is expanding because there's a lot of the experience that hadn't yet digitized, so we're going after new experiences that hadn't digitized, I'll know it when I see a problem and bringing that into the digital world. And that's -- and I think that's a unique ownable space and you're seeing that play out for us that even as you have lots of others that have introduced new experiences, chat bots and things like that are -- were 8 straight quarters of record high users and Pinterest is a platform being Gen-Z, they see us as a -- 39% see us as the first place to search. That's a great demonstration of the fact that they see us, our users see us as a unique experience separate from what's happening elsewhere and both can grow simultaneously in our.
Got it. So building on that Gen Z point, just in terms of the engagement levels you're seeing from Gen Z, how do you think about sort of building towards sustaining and building further momentum on top of that engagement on top of that user growth, what do you think about your product road map and sort of sustaining that in the years ahead?
Yes. So when I think -- I think about share of wallet on 2 perspectives, share of wallet with our user, our consumer and then share of wallet with our advertisers. And I'd say on both, where we are 3 years in, we have made tremendous progress improving Pinterest as a shopping destination, right? And we are a destination. 85% of our users come to our mobile app directly, 100% of our users are logged in. We are a destination. We are not nearly SEO dependent as others. We are a destination.
But how do we continue to differentiate that? We see that we are still, even as we have made tremendous progress, a relatively small portion of the overall share of wallet. And we've talked about on some of our earnings calls how shopping and retail has been a strength, but we see financial services that is adjacent to that becoming a strength. We talked about other emerging categories like autos and things like that, where -- or travel where our visual first experiences apply to a lot of other commercial journey. So I think that's opportunity for us to continue expanding share of wallet with our consumer as well as share of wallet with our advertiser where we've talked about how we've started to break in more and more to the always-on performance budgets of the advertisers, particularly with the largest, most sophisticated. But even there, we continue to gain more of the catalog, deepen share of wallet there.
Even as we go into more and more advertisers, we talked about that sort of $1 billion to $30 billion GMV group is our next segment. How we're starting to pick up traction there and then SMB after that. Well, those are all new buying experiences to come on to the platform that deepen the share of wallet with the advertiser but also give us more great products to show users that make it so that users see us as a great place to go for more and more of the things they're shopping for.
Got it. And in terms of continuing to build momentum there, how do you think about what's in your control in terms of product road map on the shopping side in the years ahead versus some of the threats or challenges people talk about when they talk about maybe a shift towards Agentic shopping over time. How do you think about balancing opportunities and the challenges.
Well, what I'd say the things that are directly in our control, we feel really great about the relevancy of our recommendations. We talked about we've more than doubled the relevancy of our search results over the last couple of years, our taste graph growing 75% so all the things within our control, we feel really great about. We also feel really great about the way that we're managing the ecosystem. So when you talk about new experiences like an Agentic, you really need to have thoughtful management of the ecosystem.
And if you step back from it, we don't call it Agentic because that's not how our users think about it. But when you just say things like Pinterest just gets me or I started a bit of my journey, but then I came back 2 days later and Pinterest had all these great recommendations for other things I needed to buy to complete or help me finish the journey. What is Agentic? It's helping users complete journeys. We're taking users in a completely automated way through more and more of the journey using AI. And so we feel like we are very well positioned around sort of the broader notion of Agentic experiences where people will look for the AI to take them further and deeper through journeys. At the same time, I think we're striking a good balance in the ecosystem management where -- and I've got past experience on this, where a lot of the sort of what the tech platforms would like to do around completing these experiences.
Like Agentic buying is not really a new thing. There's a thing called Google Duplex. If you remember that product, it was out for many years. And with a lot of those retailer participation is going to really matter. Understanding the user and what the user really wants matters. Retailers are not going to be happy about being relegated to dumb pipes and being disintermediated from the consumer. So when you look at the experiences that we're creating that create really seamless buying, we've done things like with Amazon, where you can do a one-tap buy right inside our platform but it's clearly branded as Amazon.
You don't even have to use our -- leave our platform to do it. You can just tap buy and the purchase just happens, but it's clearly Amazon-branded, they're clearly still getting a customer not just a transaction. So I think we've been laying a lot of the right foundation for the retailers and the ecosystem to feel like we are not making this intermediation play. We're actually still bringing them a customer. And from a user perspective, keeping them in the loop, keeping them in control, but then taking them much deeper in these journeys and then they can be in the loop when they're ready to complete. And I think that's actually what we're going to see a lot more of for the next couple of years versus telling the agent just go buy everything for me, let me know how it works out. And that sort of litmus test I always give people to sort of conceptualize this.
Think about the person that knows you best in your life, whoever that is, spouse or whoever, would you let that person pack your suitcase for a 2-week trip without you looking at anything that's in the suitcase? I have yet to meet a person that said yes to that question. And so the bar for what it takes to allow an agent to like fully complete your shopping journey, that bar isn't just be better than a human. It's be better than the human that knows you best in your life. So I think people are going to want to be in the loop for a while.
But I do think and we're seeing it on our platform, back like we basically created an AI-enabled shopping assistant already without calling it that is that people are very happy when you take them right up to the end of that journey and say, yes, that's the thing. That's it. And so if you lay all the stuff out and said, "Hey, I think I have got your suitcase, Is this right?" Yes, yes, yes. No. Yes, that was very helpful. Just back the whole thing, and I don't need to look and it just shows up on my doorstep. I don't think people are there yet someday, but I think that's not what's next. But if we look at what I think people are ready for in the here and now, we feel really great about how we're progressing that and how we're balancing the -- making sure it's great value for the retailers as well.
Understood. Okay. I like that test. I'm not going to ask my wife that. Switching to the advertising environment. What are the key messages you guys are receiving as a company broadly from advertisers about the operating environment today. And how is Pinterest roll in that environment, whether measured by brand spend or performance marketing spend continuing to evolve?
Well, we have really proven out Pinterest as a performance ads platform. I think when you look at not just where we are but the progress we've made in 3 years' time, Three years ago, Pinterest was almost entirely upper funnel brand ads, right? There were very few clicks and conversions happening on the platform. Now we are primarily a performance ad platform. So we've talked about strength with the largest, most sophisticated retailers out there. For those advertisers, we see 90% plus of their spend with us now is performance driven, right?
And so we have a very -- and I think it's a pretty unique thing. You haven't had somebody really break into performance budgets, particularly search performance budgets in a long time and we're carving out a space for ourself there. Now we're still as much progress as we made, I'd say still pretty early innings, which means there's a lot of runway ahead but I think we have very much proven out a role for ourselves because of the unique nature of our consumer shopping experience, right? So we've built up the basic components of a performance ad platform certainly not to the degree that the very largest have done because they've been at it for 20-plus years.
But in the last few years, we've stood up the basic components of a performance ad platform and then use that to tap into this completely unique shopping experience that happens on Pinterest, where users curate and then now increasingly take action, that's advertisers, particularly those are engaging in shopping and things that are shopping adjacent are seeing that as a really unique opportunity. We're able to drive performance increasingly through AI-enabled tools like Pinterest Performance Plus that's making it so that we cut their campaign creation time in half make it easier for them to come on board, those things are working well.
And then I think some of what was embedded in your question also was just you talked about the operating environment, sort of the macro and those things. And my comments here will be very consistent with what Julia and I talked about on our most recent earnings call, which is, I think, the macro, particularly for advertising is more constructive than it was at sort of peak tariff uncertainty. At the same time, there are puts and takes in the market, right? And I think even since our earnings call, you've seen other earnings calls happen since then where you see some of these puts and takes playing out? Do you see some of the very largest retailers talking about margin pressure from cost of tariffs and things like that.
But then you also hear those that cover small businesses, like the Shopifys of the world, talking about how well the small businesses are able to be dynamic and ship supply chains or raise prices to cover these things. And so you see how different parts of the market are handling that differently. So we played through those puts and takes previously. And I think 1 of the things that we've continued to demonstrate back to that consistent mid- to high teens growth is that we laid out at our Investor Day multiple ways to win. And so when we did face a bit of tariff uncertainty last quarter, you saw us play through that, I think, quite well coming in ahead of top of our guidance ahead of expectations or at least the analyst expectations anyway, it doesn't mean everybody's expectations.
And a big part of that was because we have multiple levers there, where even with a little bit of pressure in the U.S. from tariffs, we saw advertisers redistributing spend to international and international really picking up steam for us. And so I'd say the macro, again, very consistent with what we talked about at our last earnings, but you've now since seen others report earnings, and you see some of those puts and takes around there are places where there are pockets of strength like small business, which is a newer but growing exposure for us in a very positive way. But also we have some retailers feeling margin pressure. And so that means we're going to demand more performance than ever. And good news, we've been very focused on delivering performance for them.
Got it. And that's the externality that's the stuff that's sort of out of your control. When you pivot back the conversation to the stuff in your control. Talk a little bit about some of these mechanisms for monetization you're building for the long term. You talked there about Performance Plus. We've written positively about that from our own advertising industry conversations. But talk a little bit about the building blocks you're putting in place to continue to drive Pinterest as a platform towards more always on, more performance marketing dollars, more lower funnel conversion over time.
Yes. Well, maybe I'll start before I come to the ad side of it. The hardest thing in these is always getting the consumer behavior. That's always the hardest getting consumers to shop and engage and purchase that's the hardest thing to do. If you've got that, then it's sort of basic mechanics like how do you help advertisers tap into that. So I talked about the 8 straight quarters of record high users. You've also seen from us, I think this was maybe overlooked a bit in the last quarter, like in U-CAN, our largest revenue market we saw the fastest user growth, year-on-year user growth in U-CAN that we've seen since Q1 of 2021.
And we have seasonality in our business, which is why sometimes people miss that because of sequential, but you've got to look at the year-on-year so the seasonality doesn't mislead you. And year-on-year growth for U-CAN users was our fastest growth rate since 2021. So acceleration there even after 8 straight quarters of record high users overall. So we're getting really great user engagement. And then further to that, how are we getting the engagement. We've talked about even as we're hitting record high users, we are deepening engagement per user.
The way that we're doing that is with search and actionability at the core. So if you think about like query growth on our platform, even traditional queries, query growth is growing faster than user growth. Then within that, we're getting more and more people to visual search type experiences. So our visual search engagement, particularly when denominated by like the amount of clicks that we drive, right, because you want to drive actionability while you've got search queries with traditional search queries will be growing faster than users.
The visual search engagement driven by total clicks growing even faster than that. And then ad clicks growing even faster than that. And so we've talked about that dynamic before, like the deep engagement and the acceleration or the higher growth rates of the types of engagement that we want and those things being very commercial. That all is playing out very, very nicely, including our newest experiences like visual search and specifically my comments there around like related items, right, which is a purely visual search type experience on our platform that we continue to advance.
Then on the advertiser side, what we've been doing is make it easier and easier for them to tap into that, right? So I sort of think of this is like 3 legs of the stool that, first, we needed to go drive clicks and conversions to the advertisers. So a couple of years -- actually, roughly 2 years ago, we launched mobile deep links and direct links. That sent much more traffic to the advertisers. Then we came behind that and provided measurement solutions that made it so the advertisers could measure that, and that was really sort of start of last year.
We drove a lot of adoption through last year. And then at the end of last year, we launched Performance Plus, which was a third leg of the stool, which is the sort of automation suite to go make campaign creation instead of really seamless and easy cut campaign creation time in half. So now we're seeing all that really, really working and continuing to drive forward. And so we're taking that from the largest advertisers into the mid-market and small business, mid-market, we define is more like $1 billion to $30 billion in GMV.
That's been a multi-quarter phenomenon of deepening engagement there. SMBs, we're starting to see really good early signs with SMBs now the Performance Plus is out there. And international, we were taking that shopping playbook to the international markets and you've seen the denominators there are still small relative to U-CAN for us. But it's a huge opportunity. We have 80% plus of our users outside the U.S., but only roughly 20% of our revenue addressing that imbalance is a huge opportunity, and this is sort of the sequence of events we expected that we needed to solve shopping in our largest home market first.
But now we're deploying that to international, and you see that in the very nice growth rates we're putting up on international. So those are ways that just broad strokes, how I think about that continuing to play forward and the AI at the center of that. I think we're just -- all these things, I've said repeatedly like no hockey sticks, these are multi-quarter, multiyear. The shift to these AI-driven experiences in the kind of efficiencies that can be driven on this. This is a -- for the industry. This is a multiyear phenomenon and there's still a huge amount of sort of pie expansion to happen.
When you think about just how many ad dollars are still spent in inefficient places where you don't get great performance. All advertising dollars are eventually going to be performance advertising dollars. And I think the unique shopping behavior that we have our ability to help advertisers tap into that in a seamless way that's driving performance for them, I think, is carving out a nice place for ourselves in that, and there's multiple years of that runway ahead.
Maybe following up on that and maybe first starting with just partnerships, but it dovetails into international. How do you think about some of these efforts scaling and how much of it is elements of partnerships you've struck as much as its elements of owned and operated and building and scaling yourself. I think international is a good example, maybe to double-click on that.
Absolutely, yes. And I think it's also -- as we've done all these things, as we've built this performance ad platform doubled down on AI, really completely revitalized the platform. We've also delivered great margin expansion. So we're making this profitable growth, great cash flow generation and this gets to your question around how we use partnerships. We're being really thoughtful about how we make investments that are high ROI. On the AI side, that is like we build in-house for things that are truly unique to us but then we can leverage things off the shelf and tune them on our AI to get even better results. That makes us really efficient with how we deploy AI dollars.
On sales, in our largest markets, we -- first party sales is absolutely a focus for us. When we talked about expanding, we said, okay, we can work with partners to go round out gaps in the auction in smaller international markets where it may be less efficient for us to go fully do first-party sales, we can use partnerships to enter those, whether those be third-party ads, whether those are resellers, whether those are agencies and we use a composite of those things and sort of the balance between those shifts where larger markets, we tend to be much more first-party. Other places where it would be less efficient for us to do fully first party.
We'll mix in more partnerships to make us very sort of capital efficient on those things. And we see that working out really well. And I think when you survey those partners, particularly around agencies that given Pinterest didn't have much in the way of performance advertising 3 years ago, our agency partnerships are still new and evolving, but we see really, really good strength there, and to be very clear, unlike some others in the space who think that AI is just going to replace the agencies like we think the agencies are going to have a real meaningful role to play for some time, and we're very focused on how we partner closely with them, bring them into the equation.
And I think there's channel checks and things out there that talk about that where you hear from those agencies, I think the ones that are working with us are seeing more and more that we're delivering great performance and want to lean in there. So the partnership's aspect, partnerships with large, whether that's agencies, resellers, third-party, we think those are doing exactly what we hope to do, which is helping us be really efficient going into new markets or new areas of the auction where we needed to round out gaps. And we're demonstrating performance for them, making them part of the equation in a way that they feel good about as well.
Maybe just 1 quick follow-up. I think investors generally understand the opportunity when they see the base of users internationally versus the current level of monetization. Talk a little bit about what are the unique challenges internationally that maybe you don't face in North America that just sort of make that something that could play out over years and that people just need to maybe have some framing around like duration of execution.
I mean, I think all these things play out over years, even North America is we're 3 years in, and we have many years to go, and we continue to gain share of wallet with our users back to like deepening engagement per user, even as we grow users. But international, there are 2 things I'd say. One, the AI-driven experiences, the shopping experiences that we're driving, those are working at a global level. You see that in our growth rates. If you look at our -- I talked about how we're quite happy about how our U-CAN user growth rate was the highest it's been since Q1 of 2021. Well, our international growth rates on users is even higher. So the things we're doing around visual search, AI-driven recommendations, that is working at a global level.
But then to your question, like the multiyear trend or the multiyear duration on these things, there are some things that you need to do to solve 4 specific markets where shopping may happen slightly differently in some markets versus the next. I've solved that multiple times in past lives. These are very solvable. I just think about it is like you want to be sort of 95% global and then solve that 5% last mile or last kilometer in those international markets. And so that takes time, but we're actually seeing the generalizable part of that play out really well and it's reflected in our growth rates.
And again, that's a general phenomenon I've talked about of query growth being faster than user growth and then the actionability and the clicks being faster than that, particularly around the monetizable clicks. That general phenomenon is playing out globally for us. So I think the generalizable part of that is holding globally. We don't have to do a totally different product market by market, but there are sort of last kilometer of things that you need to do in some of these markets. And so that's where it played out over multiple years. But you can see reflected in our revenue growth rates in those international markets that we are picking up steam there.
Okay. I know we only have a few minutes left. So I wanted to end on sort of a bigger picture question that maybe ties some of this together. So we've talked a lot about AI development. Talk to us a little bit about how your priorities around AI development, most anchor around where you want to take visual search for the medium to long term. And where you want to take visual search, how does that feed into dynamics around competitive advantages for the platform? How does the data that Pinterest have feed into that broader dynamic when you think out over the next sort of 3 to 5 years?
Yes. This is the most differentiated thing, this is -- I've talked about from the day I joined. The curation that happens on Pinterest is truly a unique signal to feed the AI. It's something in past life is like you say, "Hey, we know everything that you buy, right?" But while there are other players that may know everything you bought, everything in your closet, they generally have no idea how you style it into an outfit. How do you pair those products together, right? And I'm not talking like the easy product associations like, "Oh, you just bought your first bag of dog food like you're going to need a whole bunch of other dog accessories like that's super easy." Which handbag looks good with which outfits and which one is actually aligned to you. And when we talk about our taste graph having grown 75% over the last 2 years, that is hundreds of millions of people on our platform every day, making these product associations where that lets them -- it's not just that we can personalize better for that user.
The next user can come in with just a very small starting point of maybe like I like that handbag. And we will know how many, many other people styled an outfit around that handbag. But even better than that, we know the intersection between how other people style that handbag and those that have tastes similar to your own style that handbag and then we can make a recommendation, then lets the users back to so many of our users say, "Well, Pinterest just gets me, right?" We're not ready to replace the most trusted person in your life yet for what you're doing with shopping, but we're going after that kind of joyful experience, right? Not utilitarian part of the people that want to get away from shopping. It's like, send a bot off to go do this for me, so I don't have to worry about it, the utilitarian journeys, make sure I don't run out of milk and eggs and detergent, bots may be good for that.
But the stuff that is -- there's a joyful aspect of shopping for so much of what is shopping where people want to be involved in what they're choosing, they just want help and assistance. That is going really well. And it is that unique curation signal that lets us tune the AI in ways others can't. So again, like our latest multimodal visual search model, which is proprietary and built in-house on our unique signal outperforms the most popular off-the-shelf models by over 34 percentage points on the relevancy of the shopping recommendations. And that is, one, we have a very focused effort. We're not trying to win generalizable sort of anything you can ask the model, but focus on shopping recommendations, we're able to do that when we have some great AI engineers, but also we have really unique signal around those product associations.
And I've shared this in other examples where I've said even when we take the off-the-shelf models and retrain them when we're using them for things that we don't want to build ourselves, even in cases where we say, we're going to take something off the shelf to be cost effective, but we're going to retrain it on our signal. I've shared that we'd see 300 basis points of lift just from training of our unique signal, which gets to that curation behavior, which, again, at least from my vantage point, is totally unique in the Western world, and I think is at the core of our advantage here and our ability to do things that are truly unique.
And so again, that flywheel spinning, users are curating more and more, gives us more signal, lets us make better recommendations, brings more users to the platform, gains more share of wallet, spins the flywheel but even more unique signals to train the AI, even more ability to bring advertisers in that, we see that flywheel spinning. And that was very much the theory of the case 3 years ago. A lot needed to go right for that to work. When I look back over the last 3 years, like it has gone exceptionally well. There's always use I'd like to grow this part a little faster, that part a little faster.
But overall, that has gone exceptionally well and that unique curation signal, I think, is something that people don't still -- I think a lot of them still don't fully appreciate just how important that is. It's -- in the Western world, I don't have another experience out there that has that signal. And that's why you see us really gaining share in search back to 39% of Gen Zs as Pinterest is a first place to go search. And now they're more than half the platform, that's the best evidence I can give you of just how effective that has been even as we still have a ton more to build.
Okay. Well, Bill, I always appreciate the opportunity to have a conversation. Thanks so much for the conference. Please join me and thank you Pinterest for being part of the conference this year.
Thank you, Eric.
Financial data from Pinterest
Revenue
Revenue is the sum of all sales generated by a company, e.g. for its products or services.
Revenue (TTM) metric explainedDirect Costs
Direct costs are the costs incurred directly in connection with the manufacture of the product or service.
Gross Profit
Gross Profit indicates how much of the revenue remains in the company after deducting direct production costs. If the percentage share of sales is calculated, this is referred to as the gross margin.
Gross Profit metric explainedSelling and Administrative Expenses
Selling, general and administrative expenses (SG&A) include all expenses for marketing and sales as well as the general administration of the company.
Research and Development Expense
Research and development costs (R&D) provide information on how much the company invests in the research and development of its products. The costs are particularly interesting as a percentage of revenue and in comparison to direct competitors.
EBITDA
EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization) is the company's earnings before interest, taxes, depreciation and amortization. The EBITDA margin is calculated as a percentage of sales.
Depreciation and Amortization
Depreciation represents reductions in the value of the company's assets (e.g. due to wear and tear on machinery).
EBIT (Operating Income)
EBIT (Earnings Before Interest and Taxes) is the company's profit before interest and taxes, also known as the operating income. The EBIT Margin is calculated as a percentage of sales at
.
Net Profit
Net Profit represents the profit or loss after deduction of all costs.
Net Profit metric explainedStocksGuide Premium
| Jun '26 |
+/-
%
|
||
| Revenue | 4,556 4,556 |
17%
17%
100%
|
|
| - Direct Costs | 935 935 |
19%
19%
21%
|
|
| Gross Profit | 3,621 3,621 |
16%
16%
79%
|
|
| - Selling and Administrative Expenses | 1,781 1,781 |
14%
14%
39%
|
|
| - Research and Development Expense | 1,568 1,568 |
17%
17%
34%
|
|
| EBITDA | 305 305 |
28%
28%
7%
|
|
| - Depreciation and Amortization | 34 34 |
44%
44%
1%
|
|
| EBIT (Operating Income) EBIT | 272 272 |
26%
26%
6%
|
|
| Net Profit | 249 249 |
87%
87%
5%
|
|
In millions USD.
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Pinterest Stock News
Company Profile
Pinterest, Inc. engages in the operation of a pinboard-style photo-sharing website. It allows users to create and manage theme-based image collections such as events, interests, and hobbies. The company was founded by Benjamin Silbermann, Paul C. Sciarra, and Evan Sharp in October 2008 and is headquartered in San Francisco, CA.
StocksGuide Premium
| Head office | United States |
| CEO | Mr. Ready |
| Employees | 5,287 |
| Founded | 2008 |
| Website | investor.pinterestinc.com |


