PINS

I will now hand the conference over to Andrew Somberg, Vice President of Investor Relations and Treasury. Please go ahead.

Good afternoon, and thank you for joining us. Welcome to Pinterest's earnings call for the first quarter ended March 31st, 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.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. 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-it 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. 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 multi-year 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. 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 interests.

We initially launched this model on search and related surfaces in 2025 and subsequently extended it in Q1 to serve content globally site-wide. 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 Plus, our AI-powered performance ad suite, continues to drive strong results for advertisers. In particular, we are focused on driving adoption of Pinterest Performance Plus campaigns, 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 Plus will be a multi-year customer adoption and product cycle. Just over a year in, approximately 30% of lower funnel revenue is now running through Pinterest Performance Plus campaigns. 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. 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. We are starting to see strong early results. For example, Mejuri, a leading fine jewelry brand, ran a four-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%-20% improvement in lifetime value ROAS. These and other bidding optimizations help 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. 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 omni-channel 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 tvScientific 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. 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. 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. 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're 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. 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 pegboards 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 preschools 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. 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 a billion-dollar convertible note and cash on hand, this 2 billion dollar 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 dollar 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 1st 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%. 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 continued headwind from our largest retailers in Q1. 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 under-monetized 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 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-$1.153 billion, representing 14%-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-$276 million.

We anticipate Q2 2026 non-GAAP cost of revenue to grow sequentially from Q1 2026 by mid-single digits%, 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. 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. With that, we can open up the call for questions.

We will now begin the question and answer session. Please limit yourself to one question. If you would like to ask a question, please press star one to raise your hand. To withdraw your question, press star one again. We ask that you pick up your handset when asking a question, and if you are muted locally, please remember to unmute your device. Your first question comes from the line of Doug Anmuth from JPMorgan Chase. Please go ahead.

Thanks so much for taking the question. 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? Do you expect to maintain revenue growth in the mid-teens on an FX neutral basis in the back half? Thank you.

Sure. Thanks, Doug Anmuth. You know, on Q1, the story of the strong Q1 is really two things. First is the continued broadening of our revenue base, and then second, you know, 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. You know, 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 guide, you know, contributions 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. On looking ahead to Q2, given the change in FX in impacting 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, you know, 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, there are a few factors which we expect to moderate international growth in Q2. You know, 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. 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. You know, we're still significantly under-monetized internationally relative to the strength of engagement and commercial intent we see on the platform. 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.

Stepping back, I think, you know, 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. 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. Please go ahead.

Thanks so much for taking the question. Maybe coming back, Bill, to some of your comments about the hiring of Lee into the role in the organization. Just wanna 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 so much.

Thanks for the question, Eric. First of all, you know, at the platform level, it's really important to remember that today our user engagement and commercial activity continues to outpace our monetization. While we've made real progress building a full funnel performance ads platform, you know, 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 three 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. 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.

That scale and complexity, you know, it's a great thing for our business, but, you know, clearly a different operating approach for us to go fully pursue that opportunity. 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 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, you know, 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. 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, you know, spent the last several years putting in place.

Your next question comes from the line of Ross Sandler from Barclays. Please go ahead.

Great. Julia, you mentioned that the small and mid-size 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. In particular, when do we expect the larger accounts to start to maybe pick up the pace a bit? Any thoughts there? Thank you.

Yeah, happy to take that one. You know, as we said, you know, 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. 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. You know, those large retailers do continue to navigate some tariff-related margin pressure, though we're seeing some stability there.

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, 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. 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. 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. Please go ahead. Rich Greenfield, if you could double-check that your line is unmuted. While we troubleshoot, let's move on to our next question, which comes from the line of Colin Sebastian from Baird. Please go ahead.

Great. Thanks. Good afternoon, thanks for taking the question. Maybe as a follow-up to Ross's question regarding the efforts to diversify the advertiser base, Pinterest 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? Related to that, you know, given that Pinterest Performance+ adopters are growing their spend at, I think, twice the rate of non-adopters, how are you leveraging tools like Pinterest Canvas and PinRec to lower those barriers for smaller advertisers? Thank you.

Thanks for the question, Colin. You know, as I noted, we're really encouraged by the progress in Q1. Our business accelerated in the quarter, that acceleration was driven by growth outside of our largest retailers.

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. You know, 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. We're only about a year into that journey, which we expect to be a multi-year cycle, just as it was for the larger platforms when they deployed their AI-driven automation suites. Early adoption is encouraging.

The 30% of our lower funnel revenue that's now running through Performance Plus campaigns, you know, we feel good about that, but obviously that's still early in 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. We're adding more functionality across bidding, targeting, creative, and measurement over time. You know, a lot of that on our, you know, 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. You know, 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. You know, as I commented on a bit before, you know, that takes a different level of operational rigor than serving a smaller group of large retailers, and that's exactly what Lee's focused on building there, so we feel good about the early progress there. We, you know, we still have a lot more to go there, a lot more of that opportunity in front of us.

We still very much believe that SMB, along with mid-market and international, can become, you know, a meaningfully larger part of our business over time. You know, 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. We're encouraged by the early progress. Hopefully, that helps.

Your next question comes from the line of Jason Helfstein from Oppenheimer. Your line is open.

Uh-

Please go ahead.

Thank you. I 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? Just second, I know you're not guiding for next year, but, you know, is there any way to think about how we should be thinking about expenses for next year relative to what, you know, may be a higher level of investments this year, after the headcount reductions? Thanks.

All right. Thanks for the question. You know, obviously, nobody can perfectly predict the future but, you know, we're actually several years into a massive AI adoption cycle. That means that we can, you know, we can really learn a lot from what people are already doing, given we're several years into the AI adoption cycle. 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. 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.

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. 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, you know, many, if not most of our users have interacted with AI chatbots, but yet are deepening their engagement with Pinterest. That's really because 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. We're, we're solving the "I'll know it when I see it" problem, which is such a significant component of so many consumer shopping journeys. Again, you know, we're seeing this dynamic play out right now, even amongst the largest players, where it's clear the focus has been more successful than others who try to be all things to all people all at once. 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, specialization is where we believe we can win.

In comparison, general purpose chatbot platforms start with, you know, a blank screen and a command line interface, and the user has to know what to 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. When these platforms generate an image, there's often no path to a real product, brand, or purchase versus Pinterest, on that, you know, on Pinterest, that same journey centers on shoppable content, product comparisons, and real purchase paths, particularly in a primarily visual nature.

On agent to 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 to progress in agentic were likely not, you know, technical, but around user behavior and ecosystem incentives. We've been clear about partnering with advertisers and not disintermediating their relationship with customers. Hopefully that helps to give a little more color, then I'll give it to Julia Brau Donnelly on the second part of your question.

Yes, I think, it's obviously too early to talk about sort of 2027 margins specifically. I will reiterate what we said on the last call about the long-term targets of 30%-34% adjusted EBITDA margin still being the right ones and still be the ones we're shooting for here in the medium term. We laid out those targets at the very end of 2023. We made very quick rapid progress towards those targets. This year we're at aiming for 29%, partially because we're including tvScientific, but if you exclude that, we're basically flat year-over-year.

I still think those 30%-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 KeyBank. Please go ahead.

Great. Thank you. Bill, I wanted to touch on your deepening engagement point a little bit more. What do you see as the core levers to continue doing that? Given UCAN is a more established market, how much more runway do you have to drive further engagement growth here? Thank you.

Thanks, Justin. You know, while we don't, you know, comment on or validate, you know, third-party data, you know, our user and engagement strength continues to be one of the real highlights of the transformation we've driven over the last few years. You know, 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. You know, as I mentioned before, you know, 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, you know, large portions of how people actually shop.

You know, 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. 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. You know, 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, 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.

You know, we continue to see gross growth across generations, including with millennials. 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. You know, all of that, you know, built off of our proprietary signals, and that unique curation behavior, which I've talked about consistently since joining Pinterest.

You know, 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. 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, you know, Q2 is typically our seasonally softer period for quarter-to-quarter sequential user growth, particularly in Europe. You know, we measure monthly active users on a 30-day look back from the last day of the quarter. 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. 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. Please go ahead. Apologies for the technical difficulties. Your next question comes from the line of Ronald Josey from Citibank. Please go ahead.

Great. Thanks for taking the question. 2 please. Bill, as part of your the sales reorg that we talked about, I believe you talked about having ad sales closer to clients. I just wanted to talk just a little bit more about how the sales force is now structured going forward. Are we looking more regional versus vertical? Any insights about go-to-market would be helpful. Teeing off on your latest comments there around Pinterest Assistant and how shopping assistants gaining greater adoption. We're seeing consumers do that. 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 Pinterest Assistant on Pins, how do you envision that future going forward? Thank you.

All right. Thanks for the questions, Ron. On the first one, on the sales reorg, you know, we've had regional focus previously, you know, really around like the segments that report versus, you know, UCAN, Europe, rest of world. 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, you know, really, you know, went to market with a smaller number of large CPG and retailers, you know, both in the U.S. and, you know, in Europe and international.

You know, as we've built a broader set of user engagement, that allows us to now, engage with a much broader set of advertisers, you know, there are different, you know, different things required for a very large enterprise versus a mid-market advertiser, versus an SMB. 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, you know, GA, approximately 1 year or so ago.

Over 2025, you know, we saw, you know, 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'd need to target our sales and go-to-market approaches differently for a mid-market or SMB than say, you know, the largest retailers, which is, you know, where more of the approach had been focused in the past, as well as you do more and more performance selling, you have more to do around that. It's not just about organizing around those customer segments within the regions, but also about more technical selling. You know, we talked about measurement and the things that we're doing around measurement and getting more technical sales capabilities around getting the right measurement implementation.

As, as I mentioned, you know, we've, you know, more than 5x, you know, the number of clicks we send to advertisers over roughly the last 3 years. Obviously, our monetization hasn't increased nearly at that rate, which means there's a lot more monetization, or there's a lot more, you know, shopping activity that we're driving than what our monetization currently reflects. Part of that is, you know, driving deeper measurement integrations to get credit for that. That is part of the go-to-market motion. The technical selling capability is a really important addition. Those are some of the things, in terms of, you know, just going a little bit deeper on the go-to-market there.

Then, you know, the second part of your question on, you know, shopping assistance, and, you know, AI, like a few things I'd say, just, you know, we launched Pinterest Assistant in beta in Q4 of last year. As we, you know, continue to have, you know, strong user engagement trends, we're really being intentional and 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, you know, pare back. We have such really great commerciality and, you know, great traffic that we're driving to advertisers. We wanna make sure we're doing this in a way that deepens the relationship between the user and the advertiser.

As we've been testing over the past couple of months, we've been able to, you know, really materially advance the capabilities of the underlying model, you know, 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, you know, that power that assistant. As we bring that to market, you know, we're actually growing our excitement about being able to solve more of the shopping journey, but in a way that more deeply connects, you know, the user to the advertiser. You know, basically for our, for our brands and retailers, we want them to gain a customer, not just a transaction. We've been really successful in doing that over the past few years.

You know, we want to make sure we continue to do that with our Pinterest Assistant, and we're seeing, you know, good ability to do that. You know, more to come in terms of how we'll continue to ramp that over the coming, you know, over the coming months and quarters. Last thing I'd say on this point around the models is that, you know, it's worth really just commenting a bit on what's happening with these models across the industry. You know, the industry is converging on a conclusion that we reached here at Pinterest relatively early on.

you know, the unit economics of relying on large proprietary third-party, you know, LLMs, you know, 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 over-engineered generalized capability that's not necessarily optimized for company-specific problems. 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. you know, 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. We've seen these consistently produce better results at far lower cost for the majority of what our product does.

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. That's all, you know, enabled by the unique feedback loop that we get from the curation on our platform. You know, Pinterest data set's fundamentally different from, you know, what these other third-party models have been trained on.

As we think about advancing our Pinterest Assistant, you know, taking that combination of our fit-for-purpose in-house models that 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's gonna be helpful to the user, we think that unique combination, you know, can really help a lot there, and we can do some differentiating things there. You know, the last thing I'll mention is In terms of the incredibly valuable assets that we have with our data and our Taste Graph and how, you know, 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, you know, 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. You know, that's one tangible example that, you know, we talked about in 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, you know, AI models generally, both what we build in-house and those where we retrain open source models. I know that I expanded on quite a bit there, but hopefully 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. Please go ahead.

Thank you for taking my question. 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, Bill. Thanks, Andrew.

Thanks, Shweta, for the question. You know, 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. You know, we've proven that prioritizing safety and wellbeing can lead to better business outcomes. As a specific example, when we made accounts private by default for under 16s 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.

We see that, you know, 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 wellbeing. So, you know, 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. 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.

While neither we nor anybody else can perfectly predict what happens in the regulatory environment, you know, we welcome that conversation and, you know, 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. You know, 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. Please go ahead.

Great. Thanks for taking my questions. Maybe, just two. One on the upside in the first quarter. Sounds like it was driven by some of the attribution improvements from the large advertisers toward the end of the quarter. The question is, you look at the 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? Secondly, Bill, you have quite a few innovation irons in the fire, I guess. Are there any one or two 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?

On the first part of your question on the attribution, like, this is not a guidance commentary to be very clear. You know, as I mentioned in the prepared remarks, you know, 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. You know, 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. You know, we're excited about that.

We also think that, you know, 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, you know, 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 conversions, those kinds of things. Like, some of that means that those platforms are, you know, 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.

We think as we get more deeply integrated into measurement platforms, you know, that gives us an opportunity to get more of our rightful credit for those things. Simultaneously, I would say another positive trend is that, you know, as, you know, 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.

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, you know, not only from the, you know, getting people to leverage our product, but the sales and go-to-market efforts, which is why we've had the meaningful retooling of our sales and go-to-market. Hopefully that helps, you know, give a little bit more color as to some of what we're seeing from the products there.

In terms of, you know, innovation, you know, one of the things I'd point you to on innovation, you know, touch on this a little bit, you know, we see and are driving much more commerciality than what we believe we're getting credit for today. We also think that commerciality can let us, you know, that very unique audience and high commercial audience that we have, we think we can drive outcomes well beyond just our O&O property. tvScientific, you can think of as a 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.

You know, 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. Again, connected TV, we're off to a good start. Lots more to do, but we think there's, you know, more that we can do in terms of the value of that audience, more broadly.

Yep. 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.