Title

Presentation

Pinterest, Inc. beats earnings expectations. Reported EPS is $0.27, expectations were $0.22.

Operator: Hello, everyone. Thank you for joining us, and welcome to Pinterest, Inc. first quarter 2026 earnings conference call. After today’s prepared remarks, we will host a question and answer session. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, press star 1 again. I will now hand the conference over to Andrew Somberg, Vice President of Investor Relations and Treasury. Please go ahead.

Andrew Somberg: Good afternoon, and thank you for joining us. Welcome to Pinterest, Inc. earnings call for the first quarter ended 03/31/2026. Joining me on today’s call are William J. Ready, Pinterest, Inc. CEO, and Julia Brau 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 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. I will now turn the call over to William. Thanks, Andrew. Good afternoon, and thank you for joining our first quarter 2026 earnings call.

William J. Ready: We entered 2026 focused on delivering the next phase of growth at Pinterest, Inc., 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, Inc. 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 dataset. Together, they allow us to solve a problem that text-based general purpose search was never built for. It is the classic “I will 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, Inc. 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.

Ten 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 actions 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, Inc. 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 has led to meaningful gains in user experience and advertiser performance over the last several quarters, and with ongoing model improvements, we see significant opportunity ahead to extend these models to more surfaces over time. An example of this is PinRack, our proprietary generative retrieval system, which is trained on user activity and our taste graph. Rather than building separate models optimized for each surface, PinRack 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 thousand user actions over a two-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, Inc. data. Canvas allows us to build experiences that reflect the high bar for visual quality and aesthetics that users and advertisers expect from Pinterest, Inc., while operating at an order of magnitude lower cost than leading third-party models. It already supports Pinterest, Inc. Performance Plus 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, Inc. 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, Inc. Performance 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, Inc. Performance Plus will be a multiyear customer adoption and product cycle. Just over a year in, approximately 30% of lower-funnel revenue is now running through Pinterest, Inc. Performance Plus 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, Inc. Performance Plus 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, Inc. Performance Plus 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, Inc. Performance Plus campaigns to their existing ones. And 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, Inc.

Performance Plus campaign to its business-as-usual approach. The Pinterest, Inc. Performance Plus campaign delivered a 46% increase in ROAS and a 62% increase in conversions, which led Mejuri to adopt Pinterest, Inc. Performance Plus 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, Inc. 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, Inc. 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: help them better understand the full value Pinterest, Inc. 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, Inc., we are also extending that performance to the biggest screen in the home through our acquisition of TV Scientific, which closed in Q1.

With TV Scientific, we are unlocking the ability to extend Pinterest, Inc.’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, Inc. audiences and signals with TV Scientific’s algorithms via TV Scientific’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, Inc. audience data in its CTV campaigns. These are early days, but they demonstrate what becomes possible when Pinterest, Inc.’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, Inc. Performance Plus, turning Pinterest, Inc. 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 in 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, Inc. best practices to market across every region.

Looking forward, our ongoing go-to-market work is organized around three 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 solution 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, Inc.

is doing something different, and that difference matters. What sets Pinterest, Inc. 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, Inc., 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, Inc. 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 to prioritize positivity. Our new brand campaign brings that differentiation to life for consumers. Launched earlier this month in the US and UK, 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, Inc.: 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, Inc. 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 are doing that in a way that stays true to what makes Pinterest, Inc. distinct: helping people discover what they want and then go do it in the real world.

I am proud of our team’s execution this quarter and excited about the work ahead. With that, I will turn the call over to Julia to share more details about our financial performance.

Julia Brau Donnelly: Thanks, William, and good afternoon, everyone. Today, I will 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 William 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 $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 will 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 US 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 $1.08 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 are making to diversify our revenue base. Turning to our geographical breakouts for Q1: in the US 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, cash equivalents, and marketable securities of $1.3 billion. Now I will 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 one 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 TV Scientific 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 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 are 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 TV Scientific.

Importantly, we are already starting to see strong yield from our GPU capacity investments, including the engagement and performance improvements that William 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 TV Scientific 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 are 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 will hand it over to William for some final words.

William J. Ready: Thanks, Julia. I want to thank our teams at Pinterest, Inc., our advertising partners, and all the people that come to Pinterest, Inc. to find inspiration and take action. And with that, we can open up the call for questions.

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Operator: 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 1 to raise your hand. To withdraw your question, press star 1 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 Douglas Till Anmuth from JPMorgan Chase. Please go ahead.

Douglas Till Anmuth: Thanks so much for taking the question. Can you talk more about the drivers of upside in Q1 across the core business, TV Scientific, and FX? And also how you are thinking about Q2, and do you expect to maintain revenue growth in the mid-teens on an FX-neutral basis in the back half? Thank you.

Julia Brau Donnelly: Sure. Thanks, Doug. So on Q1, the story of the strong quarter is really two things. First is the continued broadening of our revenue base, and 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 are 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 do not intend to break out TV Scientific’s revenue contribution specifically going forward, but I will say for Q1, the TV Scientific contribution was broadly in line with the updated guidance we gave in mid-February. Looking ahead to Q2, given the change in FX impacts in Q2, our guidance for Q2 revenue growth is 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, which is roughly 75% of our revenue. We achieved double-digit growth in Q1 in UCAN, and we expect to repeat that in Q2. We are really encouraged by the stability we are seeing in that core market. We believe we are 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 are making deliberate leadership and structural changes in 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, and that modest disruption is playing out here in our international regions in Q2. And then, as a reminder, in Q2 we are 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 US tariffs. We are still significantly under-monetized internationally relative to the strength of engagement and commercial intent we see on the platform, so our long-term conviction in international is unchanged.

We think the changes that we are making now best position us to fully capture that opportunity over time. To your last question on the outlook for the rest of the year, we do not guide beyond one quarter, of course. But stepping back, the plans that we laid out last quarter to return to our mid- to high-teens long-term growth targets are proceeding well, and we are encouraged by the early progress here in the first half of the year. The work that we are doing across the business is focused on returning us to consistent delivery of those targets over time.

Operator: Your next question comes from the line of Eric James Sheridan from Goldman Sachs. Please go ahead.

Eric James Sheridan: Thanks so much for taking the question. Maybe coming back, William, to some of your comments about the hiring of Lee into the role in the organization. I 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 will see showing up in the business in the years ahead? Thanks so much.

William J. Ready: Thanks for the question, Eric. First of all, at the platform level, it is really important to remember that today our user engagement and commercial activity continues to outpace our monetization. While we have 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 three years, we have gone from primarily selling upper-funnel ads to large US CPG and retailers to selling full-funnel performance solutions across more verticals, more advertiser segments, and more geographies than ever before. As those channels have expanded, they have also introduced a higher level of scale and complexity, and that is exactly what Lee is laser-focused on addressing.

That scale and complexity is a great thing for our business, but clearly it requires a different operating approach for us to fully pursue the opportunity. What he is 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 is doing is making performance more visible and measurable and making sure we are 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 are 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 are doubling down on measurement and technical selling capabilities across the organization, and that includes increasing accountability for technical sales teams by adding product activation and customer engagement targets to how we measure performance. As industry has advanced on attribution, we know that we need to move faster, and that is an area we are very focused on improving. Stepping back, I have high confidence in Lee and in the team, and we are 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 have spent the last several years putting in place.

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

Ross Adam Sandler: Great. Julia, you mentioned that the small and midsized accounts accelerated in March. Just curious what you are seeing both in that area and with the large accounts since the conflict started and what the early read is on Q2. In particular, when do we expect the larger accounts to start maybe pick up the pace a bit? Any thoughts there? Thank you.

Julia Brau Donnelly: 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 by ad platform and product improvements. And then outside of those large retailers, the rest of the business—the areas we have been talking about in terms of driving growth—accelerated in Q1 relative to Q4. To your question on macro and the Middle East, broadly the environment we are seeing in the ad market is relatively consistent with last quarter. Those large retailers do continue to navigate some tariff-related margin pressure, though we are seeing some stability there. We are continuing to focus on how we grow outside of that business, driven by a lot of the product and go-to-market changes that William was just talking about and that Lee is really focused on driving.

We are tracking the conflict in the Middle East, but I would 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 is really isolated to certain verticals impacted by higher oil prices. This has all been factored into our Q2 guidance range.

Operator: 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 us move on to our next question, which comes from the line of Colin Alan Sebastian from Baird. Please go ahead.

Colin Alan Sebastian: Great. Thanks. Good afternoon, and thanks for taking the question. Maybe as a follow-up to Ross’ question regarding the efforts to diversify the advertiser base, Performance Plus now running at approximately 30% of lower-funnel revenue. What adoption trends are you seeing within the mid-market and SMB segments? And related to that, given that Performance Plus adopters are growing their spend at, I think, twice the rate of non-adopters, how are you leveraging tools like Canvas and PinRack to lower those barriers for smaller advertisers? Thank you.

William J. Ready: Thanks for the question, Colin. As I noted, we are 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 have talked about—we feel really good about the progress we are making there. On SMB, to be very clear, we are referring to advertisers with tens of millions to $100 million of GMV—not really the long tail of mom-and-pop advertisers. It is also important to remember that Pinterest, Inc. Performance Plus only reached general availability approximately a year ago. For the first time, we have a product built to serve smaller advertisers that do not have the time, resources, or expertise to manage campaigns across multiple platforms, and we are 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.

Early adoption is encouraging. The 30% of our lower-funnel revenue that is now running through Performance Plus campaigns—we feel good about that, but obviously that is still early in the journey of capturing the full opportunity, both in terms of driving continued adoption—because there is significant room to grow adoption—and also because we continue to roll out meaningful performance improvements, a few of which I noted on the call, and we see much more opportunity for that to continue. We are adding more functionality across bidding, targeting, creative, and measurement over time, and a lot of that leverages our in-house capabilities and taste graph—things that we think we are really uniquely positioned to do and are demonstrating.

I would also mention that mid-market, enterprise, and international are also still relatively early opportunities for us. We made a good start in both areas last year, and now we are focused on building the teams, processes, and go-to-market motions required to serve a much broader set of advertisers at scale. As I commented earlier, that takes a different level of operational rigor than serving a smaller group of large retailers, and that is exactly what Lee is focused on building. We feel good about the early progress, but we still have a lot more to go—much more of that opportunity is in front of us. 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 to do that.

We are building out the go-to-market to do it as well, but much more build is still in front of us to fully capture that opportunity. We are encouraged by the progress.

Operator: Your next question comes from the line of Jason Helfstein from Oppenheimer. Your line is open. Please go ahead.

Jason Helfstein: Thank you. I will ask a high-level question and then a quick margin question. How are you viewing the impact from chatbots with respect to the competitive landscape and emerging visual discovery? And second, I know you are 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 might be a higher level of investment this year after the headcount reduction? Thanks.

William J. Ready: Thanks for the question. Obviously nobody can perfectly predict the future, but we are actually several years into a massive AI adoption cycle, and that means we can really learn a lot from what people are already doing. I would start with what we can see and what our users are telling us through their actions already. It is important to note that at the same time chatbots have grown in popularity over the last few years, we have put up ten straight quarters of double-digit user growth and deepening engagement per user. Users, including Gen Z, are engaging with chatbots and Pinterest, Inc. at the same time for very different things. Of Pinterest, Inc.’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 are seeing specialization versus generalization play out among the AI models on enterprise versus consumer, but consumer search has historically had a 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 are deepening their engagement with Pinterest, Inc. Users come to Pinterest, Inc. leaned in with intent, and Pinterest, Inc. offers something that other platforms are not built to solve, which is visual search and discovery. We surface relevant, personalized recommendations before the user even knows how to ask for what they want, and we connect that to real products that they can act on.

We are solving the “I will know it when I see it” problem, which is such a significant component of so many consumer shopping journeys. We are seeing this dynamic play out right now even amongst the largest players, where it is clear that focus has been more successful than trying to be all things to all people all at once. Pinterest, Inc. is a specialized platform, and that is a position of strength. It is 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, Inc. offers, and specialization is where we believe we can win. In comparison, general-purpose chatbot platforms start with 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 does not yet have the words for what they are looking for.

When these platforms generate an image, there is often no path to a real product, brand, or purchase, versus on Pinterest, Inc., where that same journey centers on shoppable content, product comparisons, and real purchase paths, particularly in a primarily visual nature. On agentic commerce more broadly, you have 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 technical, but around user behavior and ecosystem incentives. We have been clear about partnering with advertisers and not disintermediating their relationship with customers. Hope that helps to give a little more color, and I will give it to Julia on the second part of your question.

Julia Brau Donnelly: It is obviously too early to talk about 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 being the ones we are shooting for in the medium term. We laid out those targets at the very end of 2023 and made very rapid progress toward those targets. This year we are aiming for 29%, partially because we are including TV Scientific, but if you exclude that, we are basically flat year over year. I still think the 30% to 34% targets are the right ones to be focused on, and we will have more to say specifically on the exact trajectory for 2027 as we get later into this year.

Operator: Your next question comes from the line of Justin Patterson from KeyBanc. Please go ahead.

Justin Patterson: Great. Thank you. William, 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.

William J. Ready: Thanks, Justin. While we do not comment on or validate third-party data, our user and engagement strength continues to be one of the real highlights of the transformation we have driven over the last few years. It is eleven straight quarters of record-high users, and it is important to note that 100% of our reported users are logged in and 85% come directly to our mobile app, making Pinterest, Inc. a clear destination app. We have also had ten straight quarters of double-digit user growth. We see ourselves as having effectively turned Pinterest, Inc. 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 are deepening engagement, we are doing so in the areas that matter most, globally and in UCAN: 80 billion monthly searches, half commercial in nature, which is a much more significant skew toward commerciality than you would see in general search elsewhere or in chatbots.

We have also talked about how we are winning with Gen Z—over 50% of our platform and our fastest growing cohort. Not only are they coming to Pinterest, Inc. 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. 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 are looking for next—all built off of our proprietary signals and unique curation behavior.

I have talked about this consistently since joining Pinterest, Inc.: that curation behavior that occurs on Pinterest, Inc., 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 cannot. That is why Gen Z—who are obviously very familiar with chatbots—are coming to Pinterest, Inc. in larger and larger numbers and with increasing depth of engagement per user, as they clearly get something very different from Pinterest, Inc. than they get from chatbots.

Julia Brau Donnelly: One other thing I would add on user and engagement trends: it is 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 thirty-day lookback 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, we feel really great about where the user and engagement trends for the business are heading right now.

Operator: 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 Victor Josey from Citibank. Please go ahead.

Ronald Victor Josey: Great. Thanks for taking the question. Two, please. William, as part of the sales reorg that we talked about, I believe you talked about having ad sales closer to clients. Can you talk 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 around personal assistant and shopping assistant getting greater adoption—we are seeing consumers do that—but talk to us about how retailers are preparing for this going forward. As you look out maybe one to three years and we hear about the personal assistant on Pins, how do you envision that future going forward? Thank you.

William J. Ready: Thanks for the questions, Ron. On the sales reorg, we have had regional focus previously—really around segments that report as UCAN, Europe, and Rest of World. 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 in the US and internationally. As we have built a broader set of user engagement, that allows us now to 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. We really just got the ad product that would let us start to go beyond those largest retailers into mid-market and SMB—that went GA approximately a year or so ago.

Over 2025, we saw good early progress there, but we also saw that we need more specific efforts around those different segments, and we need to target our sales and go-to-market approaches differently for a mid-market or SMB than for the largest retailers, which is where more of the approach had been focused in the past. As you do more and more performance selling, you have more to do around measurement and technical selling. We talked about measurement and the things we are doing around getting more technical sales capabilities and the right measurement implementation. As I mentioned, we have more than 5x’d the number of clicks we send to advertisers over roughly the last three years, but our monetization has not increased nearly at that rate, which means there is a lot more shopping activity that we are driving than what our monetization currently reflects.

Part of that is driving deeper measurement integrations to get credit for that. So 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 going a little bit deeper on the go-to-market there. On the second part of your question—shopping assistance and AI—a few things. We launched Pinterest, Inc. Assistant in beta in Q4 of last year. As we continue to have strong user engagement trends, we are being intentional and taking our time on getting the product-market fit right with Pinterest, Inc. Assistant and incorporating important learnings into our core user experience. I think you have seen some false starts from others in the space that they then had to pare back.

We have such strong commerciality and great traffic that we are driving to advertisers that we want to make sure we are doing this in a way that deepens the relationship between the user and the advertiser. Over the past couple of months, we have materially advanced capabilities of the underlying model powering the Pinterest, Inc. 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. As we bring that to market, we are 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. For our brands and retailers, we want them to gain a customer, not just a transaction.

We have 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. We are seeing good ability to do that, with more to come in terms of how we will continue to ramp that over the coming months and quarters. Last, on models across the industry, the industry is converging on a view that we reached at Pinterest, Inc. relatively early on: the unit economics of relying on large proprietary third-party LLMs do not make sense for many use cases, as companies end up paying a significant premium for what might be an overengineered generalized capability that is not necessarily optimized for company-specific problems. It is increasingly clear that the narrative that you have to rely on only one of the largest proprietary models to get significant benefits from AI is not 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 have 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 infrastructure when they are the right tool, and then we post-train them on our own proprietary data. That has multiple advantages: since it runs in our environment, it is more secure; it has much lower latency; and since it has been trained on our unique data, it delivers better performance than off-the-shelf proprietary models at a fraction of the cost.

That is all enabled by the unique feedback loop that we get from the curation on our platform. Pinterest, Inc.’s dataset is fundamentally different from what third-party models have been trained on. As we think about advancing our assistant, pairing our fit-for-purpose in-house models that are great at understanding and driving commerciality and recommendations with some basic LLM capabilities—and then post-training that in the places that can be helpful to the user—we think that unique combination can really help a lot and we can do differentiated things. Lastly, 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 would point you to what we are doing with TV Scientific.

It is a very tangible example of what we can do with that data beyond our Pinterest, Inc. app, where we have been able to achieve a 27% increase in outcomes and a 65% increase in purchases by leveraging our taste graph on top of TV Scientific’s algorithms. That is one tangible example we talked about on the call of how we can use our data on top of algorithms to get even better outcomes and is part of what we are doing with AI models generally—both what we build in-house and where we retrain open-source models. Hopefully that gives you a sense of how we are thinking about the assistant and the advancement of the AI landscape overall.

Operator: Your next question comes from the line of Shweta Khajuria from Wolfe Research. Please go ahead.

Shweta Khajuria: 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, William. Thanks, Andrew.

William J. Ready: Thanks, Shweta, for the question. We are 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. We have 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-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. Beyond what is 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.

In addition to making accounts private by default for users under 16, we have supported phone-free schools and App Store age verification, and we apply AI in ways that prioritize and tune for positivity. The response from users reflects that there is genuine consumer demand for a more positive and safer space online, and Pinterest, Inc. 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, we welcome that conversation. We have been an active voice in those discussions, and we have seen policymakers recognize and appreciate the proactive stance that we have taken on these issues. For the sake of all our young people, we are hoping to see more advancement of that dialogue.

Operator: Your final question comes from the line of Brian Thomas Nowak from Morgan Stanley. Please go ahead.

Brian Thomas Nowak: Great. Thanks for taking my questions. Maybe just two. 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. As you look into Q2, are you assuming you see further benefits from that attribution modeling across even more advertisers, or would that be a source of upside to your base case expectation? And then secondly, William, you have quite a few innovation irons in the fire. 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 the attribution modeling was?

William J. Ready: On the first part of your question on attribution—this is not a guidance commentary, to be very clear—but as I mentioned in the prepared remarks, linking our AI bidding systems to the measurement sources of truth of the advertiser allows the AI to deliver more and more outcomes that are aligned with the way the advertiser sees value. As we rolled it out in Q1—and we were in beta with that in Q4—we are seeing that work well. We have more deployment to go, and we are excited about that. We also think that, as I mentioned a few times, continuing to deepen our measurement integrations with our partners should allow us to capture much more of the value that we are creating. Again, we have more than 5x’d the number of clicks to advertisers over the last three years, but revenue has not increased nearly as much as that.

As you look at what is happening with other platforms, you hear them talking about model conversions, you see them growing revenue faster than the rate of their supply growth. Those model conversions and similar dynamics mean that some platforms are doing a better job of taking credit for clicks and conversions that they may not have driven directly or where they were a more tangential part of the path. We think as we get more deeply integrated into measurement platforms, that gives us opportunities to get more of our rightful credit for those things. Simultaneously, 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. As we see that playing out, we think that is generally, in the long term, a good thing for our platform, but there is a lot of work to do in terms of getting the measurement and integrations adopted—both from a product standpoint and via the sales and go-to-market efforts—which is why we have had the meaningful retooling of our sales and go-to-market.

In terms of innovation, one of the things I would point you to—we see and are driving much more commerciality than what we believe we are getting credit for today, and we also think that commerciality can let us take that very unique, highly commercial audience that we have and drive outcomes well beyond just our owned-and-operated property. TV Scientific can be thought of as the first move in that direction, and we shared some of the stats we are really excited about: the 27% increase in outcomes and 65% increase in purchases when you brought the Pinterest, Inc. audience on top of the TV Scientific algorithms. We have a lot more to do in CTV, and we are very excited about that. We also think there is more we can do in terms of leveraging our audience beyond surfaces—beyond just the Pinterest, Inc.

app—which we think is a really interesting area of opportunity. Connected TV is off to a good start; lots more to do, but we think there is more that we can do in terms of the value of that audience more broadly.

Julia Brau Donnelly: To wrap up, our plans here all factor into our Q2 guidance numbers. It is way too early to talk about what is happening in the second half of the year, but we are feeling really good about the first-half progress against the plans, and our goal is to continue hitting consistently our mid- to high-teens revenue growth targets, which are our long-term targets.

Operator: This concludes our question and answer session. We will now turn the call back to William J. Ready for closing remarks.

William J. Ready: Thank you 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.

Operator: This concludes today’s call. Thank you for attending. You may now disconnect.

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