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Operator: Thank you for standing by. My name is Rebecca, and I will be your conference operator today. At this time, I would like to welcome everyone to the DoubleVerify First Quarter 2026 Earnings Conference Call. [Operator Instructions] I will now turn the call over to Brinlea Johnson, Investor Relations. Please go ahead.

Brinlea Johnson: Good afternoon, and welcome to DoubleVerify’s First Quarter 2026 Earnings Conference Call. With us today are Mark Zagorski, CEO; and Nicola Allais, CFO. Today’s press release with this call may contain forward-looking statements that are subject to inherent risks, uncertainties and changes and reflect our current expectations and information currently available to us, and our actual results could differ materially. For more information, please refer to the risk factors in our recent SEC filings, including our Form 10-Q and Form 10-K. In addition, our discussion today will include references to certain supplemental non-GAAP financial measures and should be considered in addition to and not as a substitute for our GAAP results.

Reconciliations to the most comparable GAAP measures are available in today’s earnings press release, which is available on our Investor Relations website at ir.doubleverify.com. Also, during the call today, we’ll be referring to the slide deck posted on our website. With that, I’ll turn it over to Mark.

Mark Zagorski: Thanks, Brinlea, and good afternoon, everyone. We delivered strong Q1 results as we continued our solid execution on our product innovation, strategic and financial road maps. In Q1, we achieved 10% year-over-year revenue growth, led by accelerating growth of our social verification and optimization solutions, and we delivered a 31% EBITDA margin, which exceeded expectations, largely due to AI-fueled operational efficiencies. Advertiser growth was positive across all key industry verticals in the quarter as we continue to benefit from our focus on further diversification of customer engagements and ad spend across various client types. We also repurchased $100 million worth of shares year-to-date, reflecting confidence in our business and our commitment to returning capital to shareholders as a core element of our long-term value creation strategy.

We expect to deliver a strong 2026 as we successfully execute on our strategic plan to verify the quality, optimize the investment and prove the impact of digital ad impressions across any platform, media or market or advertiser spend. The solid results this quarter were fueled by our core growth catalysts, social activation and measurement products, streaming TV verification and our dynamic suite of solutions that empower advertisers to better navigate the evolving ecosystem of AI advertising platforms and Gen AI content. Across all of these sectors, our incredibly durable value proposition remains tantamount. DV is the independent essential trust layer that marketers rely on to ensure their ad spend is protected from fraud in unsuitable context and most importantly, delivers the highest possible return on investment.

And this essential role in the ecosystem continues to expand as new product innovations power our growth flywheel. Let me share a few recent stats that underscore the impact of these investments. Driven by continued success on Meta, social measurement grew 23% year-over-year, a significant acceleration from Q4. Social activation, our fastest-growing solution set, grew 92% year-over-year in Q1, up from 62% in the fourth quarter. Authentic Advantage on YouTube, which combines Scibids AI optimization with prebid filtering and post-bid measurement launched in Q3 last year and is also expanding rapidly. It is now on track to deliver $10 million of expected ACV in 2026. CTV measurement impression volumes also grew, up 28% in the quarter. And our ABS-enabled streaming TV prebid Do-Not-Air List entered general availability in January.

With 3 top 15 customers representing hundreds of millions in CTV spend implementing these DV-only streaming TV controls. DV continues to break new ground in the drive towards greater transparency in streaming TV. AI measurement tools like Slop Stopper, which is now available on YouTube and AI agent ID are showing meaningful engagement rates. Our AI Slop Stopper measurement solution for mobile and online video and display is already applied to over 40% of measured impressions, and the prebid tool is being tested by 6 of our largest advertisers. Our midterm goal remains to increase the contribution of social, streaming TV and AI-driven solutions from under 30% of total revenue today to approximately 50%. As we drive this evolution, our mobile and online video and display business remained stable in Q1 with approximately 2/3 of impressions that we engage with delivered on mobile, in-app and mobile web environments.

We remain focused on creating a revenue mix that closely aligns with the fastest-growing global digital ad sectors. TV continues to drive new revenue opportunities, distance ourselves from competition and create meaningful margin expansion through AI efficiencies and product innovation. AI solutions, social activation tools and streaming TV quality solutions are positively impacting our customers’ ad performance and building a foundation for TAM and market share expansion for DoubleVerify. Shifting focus to the role that AI is playing in the ongoing expansion of our product-led growth cycle, we continue to lean into AI to operate more efficiently, launch products faster and improve margins. And as the emerging AI advertising universe evolves, it is creating new revenue opportunities that expand our TAM as we extend our essential role in this burgeoning environment.

Regarding this new environment, we’ve identified 3 main areas where DV has the largest AI growth opportunities and which we are already seeing traction with customers. First, the Agentic Buying and selling of media, where we are building new products, connecting with and leading the development of the numerous protocols that will help advertisers lean into AI-based buying. Second, we are empowering advertisers to navigate the dynamic AI-impacted advertising landscape as AI cyber fraud and AI content slop becomes prolific. And third, we are digging into the massive potential ad market on LLM chatbots where many of our current advertisers are beginning to deploy their marketing dollars, GIFT had little in the way of transparency and independent measurement.

Let me talk briefly about each one of these opportunities. First, we are focused on establishing security and trust in the agentic advertising ecosystem. Trust has always been essential in our industry, and we recently joined the Ad Context Protocol, AdCP, a coalition of ad tech companies established by Agentic Advertising organization to define standards for ad buying and selling by AI agents. According to eMarketer, about 2/3 of ad buyers plan to focus more time on Agentic ad buying this year. While in early days, we are actively engaged to make sure DV is at the forefront of establishing standards that will continue to preserve trust and transparency for its advertisers wherever they choose to deploy their advertising investments. As with all of our engagements, we remain independent and agnostic and the way we operate in the agentic advertising world will be the same with the ability to plug into any agentic protocol from the IAB framework to platform-specific systems that are important to our customers.

Second, we are expanding tools to protect ad investments from AI-fueled challenges. We continue to enhance our market-leading suite of AI tools that combat the increasing challenges of navigating AI Slop and avoiding AI cyber fraud. With the launch of DV AI SlopStopper for Social, we’ve expanded our capability for advertisers to avoid low-quality AI-generated content on YouTube and will broaden our coverage to other walled gardens in the coming quarters. Fueled by malicious AI, cyber fraud continues to become more sophisticated, threatening to challenge the ROI and efficiency gains driven by the positive use of AI. In Q1 2026, DV’s fraud web continued to harness AI to fight fraud as AI-powered fraud schemes proliferated at a record pace and became even more sophisticated.

AI-powered bot schemes continue to evolve faster than ever with 140% more bot scheme variants emerging in Q1 ’26 compared to Q1 ’25. In parallel, app-based fraud continues to accelerate dramatically, especially across mobile and CTV, where we have classified over 1,300 apps as fraudulent since the beginning of 2026. Finally, we are focused on capitalizing on the massive potential ad market that AI chatbot marketing will represent. According to eMarketer, ad spend on LLMs is forecasted to grow by over $25 billion by 2029, with ad spend expected to cannibalize over 14% of search spend, a $400 billion market that DV has historically not been able to access. OpenAI recently shared that they expect to generate $100 billion in advertising revenue by 2030, underscoring just how the market may be moving even more rapidly than analysts are predicting.

As has been the case for the open web, mobile, streaming and social environments, unbiased independent measurement will play a key role in engendering the advertiser trust needed for this new ecosystem to thrive. While AI platform ad models continue to evolve, advertiser demands remain the same, ensuring ad transactions are trusted and transparent and ads are viewable, brand suitable and delivered to legitimate traffic within authentic content environments. Our enterprise customers and agency platforms have made it clear to us that expanding beyond test budgets in AI environments will require even greater transparency and trust than is present today. We are confident that, as we have shown on social and streaming platforms, our role as an essential trust layer will extend to this new ecosystem, and we are engaged in discussions with several LLMs who are leaning into ad-supported models.

As AI drives digital advertising to become more automated, agentic and opaque and as AI Slop becomes the must-avoid content category for advertisers, the need for independent verification, protection and performance measurement has never been greater. Regardless of platform, buying mode or message, DV will be an integral trusted part of the ad equation. Moving to social verification. The social sector remains our fastest-growing business segment and is a core driver of our next phase of growth. No other verification or measurement provider has more innovative solutions for advertisers seeking to protect their spend on social platforms and ensure it performs. Social activation accelerated meaningfully to over 90% year-over-year growth in the first quarter, up from around 60% growth in Q4.

This acceleration was driven by continued scaling of our social prebid solutions, elevated by enhanced product capabilities on Meta as well as expanded capabilities across TikTok and YouTube. 87 advertisers have now utilized Meta activation since launch, up from 68 in the fourth quarter with 31 of these customers coming from our top 100 clients. As of the end of the first quarter, our Meta activation product was already at a $12 million annualized run rate. On YouTube, DV Authentic Advantage has seen strong customer adoption. Some of our largest CPG customers have started scaling on the solution, driven by the significant ROI improvements that it delivers. Through the combination of Scibids AI optimization with social prebid filtering and post-bid measurement, DV Authentic Advantage customers have seen their media CPMs decline by as much as 36%, while reach has expanded by 64% and brand suitability integrity remains strong.

As with DV’s Meta prebid solution, we are just starting to scratch the surface with the impact that Authentic Advantage can have on our customers’ business and our growth profile, and we’re excited about the significant opportunities ahead for both products. As mentioned previously, our social suite of tools are ramping, and we recently announced the expansion of DV AI verification to include DV’s AI Slop Stopper for social. This new industry-leading offering is designed to help advertisers navigate the growing challenges posed by low-quality AI-generated content and safeguard brand reputation across social and video-centric environments, starting with YouTube. DV’s AI Slop Stopper for social is another DV tool that empowers advertisers to ensure their brand investment is protected wherever they spend while driving stronger media outcomes.

Additionally, in the quarter, we expanded brand suitability coverage across Snapchat’s Discover feed format, enabling our advertisers to have complete coverage across Snap Discover Tiles placements. And we recently announced that we achieved Media Rating Council or MRC accreditation for TikTok video viewability, becoming the first measurement vendor to receive the accreditation. As advertising investment continues to grow across video-centric social platforms like TikTok, independent verification plays a critical role in ensuring transparency and accountability. And with accredited measurement informed by tens of trillions of historical ad transactions, advertisers can now evaluate campaign effectiveness with greater confidence and ensure their media investments deliver real value.

This milestone underscores our commitment to delivering the highest standards of measurement accuracy and transparency and further demonstrates the company’s alignment with the MRC accreditation process as a critical layer of accountability in digital advertising. Turning to streaming TV. We continue to deliver product innovation to address advertiser demand for independent transparency and increasing fraud in streaming environments. Our continued product innovations helped grow CTV measurement volumes by 28% year-over-year this quarter. We’ve already begun to see solid adoption of ABS Do-Not-Air list from 8 of our largest advertisers as well as strong interest in our authentic streaming TV solution. And in this quarter, we announced that Spectrum Reach became the first partner to join DV’s certified transparent streaming program, reinforcing its commitment to secure program level transparency across streaming TV inventory.

Spectrum Reach will share key show level data across their programming, including news and live sports, spanning both direct IO and programmatic buying. These insights will be available directly within DV Authentic Streaming TV reporting, giving advertisers verified post-bid visibility into the specific programs their ads ran alongside. By combining real, not implied or aggregated show-level transparency in a privacy-focused way with DV’s performance analytics and optimization capabilities, advertisers can now better understand how contextual relevance drives outcomes and make smarter decisions to optimize future streaming investments. This is just the start of our drive to deliver granular unaggregated show-level transparency across all streaming environments, and we are seeing momentum from additional platforms to join our certified transparent streaming program.

The results of our innovation leadership are clear. We are growing client engagements and winning deals with new solutions where there aren’t any competitors. We work with over 340 advertisers now generating more than $200,000 annually. And our unique solution underscored a 77% greenfield win ratio in Q1, meaning that we’re winning deals with solutions in new areas in which there are no competitive incumbents to displace. Investment in innovation continues to be DV’s secret sauce to get stickier with our customers, win new deals and gain market share. And AI is enabling us to innovate more efficiently than ever as we continue to expand margins while launching and expanding the tools that cement our role as the essential trust layer for buyers and sellers of digital media.

With strong execution in the first quarter, we’re leaning hard into AI-powered innovation that will continue to extend our leadership position. Looking ahead to the rest of the year, we remain focused on product development acceleration, partner expansion and market share growth and continued strong margins and cash flow. With that, let me turn the call over to Nicola.

Nicola Allais: Thanks, Mark, and good afternoon, everyone. For the first quarter, we achieved 10% year-over-year revenue growth and 31% EBITDA margins. Off the strong start to the year, we are reiterating guidance for the full year. For the first quarter, total revenue was $181 million, representing 10% year-over-year growth. Total advertiser revenue, which includes activation and measurement, represented 90% of total revenue and grew 9% year-over-year, driven by 12% growth in volume or MTM, partially offset by a 4% decline in fees or MTF. Activation revenue grew 6% with ABS representing 53% of activation revenue in the quarter. As of quarter end, over 75% of our top 500 clients were using ABS. Measurement revenue grew 16% year-over-year with social measurement revenue increasing 23% and representing 49% of measurement revenue and international revenue increasing 18% and representing 27% of measurement revenue.

Supply side revenue represented 10% of total revenue in the quarter and grew 12% year-over-year. We’re driving growth by adding new CTV and digital platform partnerships and by continuing to expand DV solutions on retail media networks. Moving to expenses. In the first quarter, we delivered 82% revenue less cost of sales. Our continued investments and use of AI capabilities are allowing us to scale at a consistently efficient rate even as we measure increasing levels of volume. We delivered $55 million of adjusted EBITDA, representing a 31% margin as compared to 27% margin in Q1 of 2025. Total expenses for product development, sales and marketing and G&A increased 2% as compared to 10% revenue growth. We are showing early signs of the benefit of using AI capabilities to grow through improved productivity across the organization and increased software capitalization related to product development.

We are scaling the business more efficiently, which results in increasing EBITDA margins. Stock-based compensation was $24 million in the first quarter, flat to prior year. For the second quarter, we expect stock-based compensation of approximately $25 million to $27 million and weighted average fully diluted shares outstanding of approximately 157 million shares. For the full year, we continue to expect stock-based compensation to range between $102 million to $107 million, a decline year-over-year, reflecting the impact of our updated equity incentive plan that reduced the annual value of equity grants in 2026 by over 40% as compared to 2025. Turning to cash. Year-to-date, we have repurchased 9.8 million shares for $100 million, of which 7.3 million shares were repurchased in the first quarter for approximately $75 million and 2.5 million shares were repurchased in April for approximately $25 million.

Year-to-date, the 9.8 million shares we repurchased represent approximately 6% of fiscal year-end 2025 outstanding shares. Net cash from operating activities in the first quarter was $4 million and was impacted by timing of collections and payments at the end of the quarter. For the full year, we expect free cash flow conversion of approximately 60%. We ended the first quarter with approximately $174 million in cash and no long-term debt. Now turning to guidance. For the second quarter of 2026, we expect revenue to range between $199 million and $205 million, representing a year-over-year increase of approximately 7% at the midpoint. As a reminder, we’re lapping our 21% growth rate in Q2 of 2025. And we expect adjusted EBITDA to range between $63 million to $67 million, representing a 32% adjusted EBITDA margin at the midpoint.

For the full year 2026, we are reiterating our prior guidance. We expect revenue to range between $810 million and $826 million, representing an 8% to 10% year-over-year increase and expect adjusted EBITDA margins of approximately 34%. As discussed on our prior call, incremental growth in 2026 will be driven by 3 product-led growth engines. First, continued adoption of our solutions across social and streaming TV; second, growth from existing enterprise clients scaling our product offering; and third, continued new customer acquisition driven by DV’s differentiated products. Our first quarter results demonstrate progress on each growth driver with increasing social activation revenue growth, increased adoption and scaling of new products and a consistently high win rate.

Our first quarter results show solid execution. With a clear focus on durable growth and expanding profitability, we’re well positioned to continue to deliver long-term shareholder value. And with that, we will open up the line for questions. Operator, please go ahead.

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Operator: [Operator Instructions] Your first question comes from the line of Matt Swanson with RBC Capital Markets.

Matthew Swanson: Congrats on a solid start to the year. I think I’ll pick up right where Nicola left off there. So I mean it was a great quarter for social measurement. But I mean, really focusing on that growth opportunity in social activation. Any time you have something with over a 90% growth rate, we should probably start there. Can you just kind of give us an update on how things are trending and kind of how the rollout has been going relative to your expectations with your customers, especially on Meta?

Mark Zagorski: Yes. Thanks for the question, Matt. So obviously, we’re really pleased with the scale — scaling and speed of scaling on social activation, which is really being driven by all 3 prongs. The first, as you mentioned, Meta activation and the new Meta prebid tools we have there. The second, growth in YouTube through our Authentic Advantage solution; and third, through TikTok as well, which is — continues to grow at a really nice pace on the pre-bid side. So our social activation business is really running on all cylinders. And one of the things I think this really underscores is the fact that our solutions are really playing an essential role in the walled gardens. I think there were some questions about whether or not, hey, is DV as powerful or as needed in the walled gardens as it is in the open web.

And this — the growth of this is proving that out. I think it also underscores the power of the prebid and kind of post-bid engine where we can launch prebid solutions where we already have measurement in place, we see a nice catalyst for growth. So it’s scaling well. Meta, in particular, now is over 80 clients have engaged with it. Some of our biggest advertisers are now engaged there. We mentioned, I think, in the last call, we wanted to get to a $15 million ARR by the end of ’27 — or ’26, I’m sorry, and we’re already at $12 million. So like this is growing well. I think it’s scaling well. And again, it’s definitely being driven by Meta, but it’s also that social activation 90% growth number is being supported by our innovations in TikTok and YouTube as well.

Matthew Swanson: Great. And then, Nicola, just kind of thinking more on the guidance side. I know over the last couple of years, you’ve become less exposed to kind of the CPG and retail sectors. But if there’s anything from kind of a macro standpoint that you would point out to us? And then just any update on the advertiser who went through the agency change last quarter?

Nicola Allais: Yes. So I’ll start by saying from a vertical perspective, we spoke a lot about retail and the impact it had on our business for the end of the year. That has normalized as we had expected. We already spoke about it on our last call. And overall, all of our key verticals showed growth in the first quarter of 2026. And we haven’t seen material changes across the verticals. If anything, we’ve been able to diversify further into healthcare and technology, which allows us to not be as reliant on retail and CPG. So it feels more normalized, and it feels that we are continuing to diversify in a way that’s going to help to create a more predictable business for us. In terms of macro, if you look at the verticals, I’ll address the 2 verticals that I generally mentioned in terms of uncertainty based on what’s happening in the macro for us, auto and travel are fairly small verticals.

So we’re not as exposed to those. And just a general comment on macro. We’re obviously not assuming strong tailwinds, but we’re assuming an environment that’s going to remain fairly stable.

Operator: Your next question comes from the line of Brian Pitz with BMO Capital Markets.

Brian Pitz: Mark, since I know Slop Stopper is one of your favorite topics, maybe you could give us your latest expectation around penetration rate and maybe thoughts on the future opportunities around this product. And then maybe stepping back more broadly, as AI content continues to proliferate across the Internet, talk about what you’re hearing from advertisers in terms of how they’re adapting to this changing environment? Are they starting to get more comfortable? Maybe just a little bit more insight.

Mark Zagorski: Thanks for the question, Brian. And yes, I love Slop Stopper just because I love saying the name on these calls so much. As we noted in the call, Slop Stopper is now being applied on the measurement side to about 40% of all of our impressions. That’s a pretty — it’s probably one of our fastest scaling attach rates for any different category that we’ve seen. So on the measurement side, it’s really being picked up pretty quickly, and that’s a great thing. And it also shows to your second part of your question that advertisers are still just trying to figure out how they navigate this world of AI content. And Slop Stopper is built for a specific reason. It’s to avoid low-quality, questionable AI content, right? Not all AI content is bad, but there’s certainly stuff out there that advertisers want to avoid, and that’s what Slop Stopper helps them do.

When we think about kind of what’s next for that tool, so we launched a prebid Slop Stopper solution on YouTube. We’re going to expand that to additional social platforms over the next few quarters. And it’s the platforms that — the social platforms, particularly around video, that are the most kind of challenging for advertisers to try to figure out where they should and shouldn’t advertise against. So we see this as, again, another catalyst for higher attach rates for our solution and another catalyst for folks to actually lean into working with DV, maybe even if they’re not because it gives them another tool to use to navigate challenging content. And I think the other thing, and as I mentioned in my earlier question, there is — there’s a growing need for our solutions within the walled gardens and not because the content there is particularly better or worse than any other platform, but the content there is becoming really overrun with a good amount of AI content and the advertisers really are looking for tools to help navigate that.

So the problems that advertisers saw in the open web are evolving to different types of challenges behind walled gardens. And the great thing is that we’ve got solutions to address all of them.

Operator: Your next question comes from Maria Ripps with Canaccord.

Maria Ripps: Mark, you said that you were in discussions with several LLMs regarding sort of verifiying ads on their platforms. Is this the same brand safety stack that you offer today? Or will the agentic ad environment require sort of a fundamentally different product? And how are you thinking about sort of pricing — sort of structuring pricing models for agentic ads?

Mark Zagorski: Thanks for the question, Maria, and it’s a really great one. So when we think about what’s going on with the ad-supported LLMs, what we’ve seen so far, even as recently as this week, there’s been announcements that OpenAI is embracing third-party ad solutions, right, from demand solutions and creative optimization through companies like Cargo and Pacvue and Smartly. The next step for them, as we’ve noticed, is really to start looking at measurement and verification. And we’re leaning into discussions with lots of different LLMs on that front. And when it comes to kind of what we think about what our solution can do there, it really is to play the same fundamental role that we do in social and in streaming and in display and online video, which is acting as a trust and transparency layer.

And that has everything — has to do with everything from ensuring that ads are viewable and visible by a real human to ensuring that the context where it ends up with is aligned with what that brand and who that brand is and where they want to be. So from a general thesis perspective, the application of our solutions in that environment is pretty much the same. It’s building trust between the buyer and the seller. When it comes to the business model around it, we’ve got lots of different business models when we employ with platforms. But almost all of them are advertiser-paid and they’re based on volume of engagement. So as we look at the opportunity within the LLMs, our assumption is that model will extend into there as well, which will be volume-based, advertiser paid based on the scale and level of engagement of that advertiser with the impressions on those platforms.

Maria Ripps: Got it. That’s very helpful. And then just following up on Slop Stopper. So as we think about the product, do you view it primarily as a retention tool sort of bundled into existing relationships? Or is this a product that can be priced and sold independently? And sort of you just launched it on YouTube, it’s coming on other platforms. But sort of what’s the realistic time frame for this product to move the needle on revenue either directly or indirectly?

Mark Zagorski: Yes. It’s another great question. So I think of Slop Stopper really as 2 — having 2 positive impacts on our business. The first, as you noted, is the retention. It creates greater value in our engagements with our customers by giving them another category of content to have greater transparency on. So for current customers, who already are using our measurement, I think it gives us kind of a stickier, more ingrained relationship. That is always helpful as we go back to renegotiate deals and look at price increases down the road, right? So that’s one. The second is it helps with attach rate, right? So it helps advertisers who maybe, for example, aren’t using us on Prebid, on YouTube. But now knowing that they can avoid AI slop by using our solution, that drives up attach rates for our solutions there.

So I think it has, again, a two-pronged impact the way it currently is structured. A, it helps us retain and grow our relationships with current customers, but it also drives up attach rate. If there’s a third aspect as well, it is a differentiator in the market, right? We’re — it is a unique solution for DV that our competitors don’t have. It allows us to win deals on a greater scale than we would if we didn’t have it. So there’s a direct impact to kind of the new customers that we are able to bring on as well. I think we’re already seeing — and so the last part of your question is like when does it create a financial impact in the business. I think we’re already starting to see that a little bit. When you see kind of our measurement growing at 16%, which is a great rate for us there.

When you see our social activation growing, which — of which AI Slop Stopper is part of social activation growing at 92%. Those numbers are fueled by features like this, which are unique to DV, which drive attach and create new customer engagements.

Operator: Your next question comes from the line of Andrew Marok with Raymond James.

Andrew Marok: Maybe just one for me on the chatbot surface again. Obviously, we’ve seen OpenAI kind of evolve its offering from a CPM to a CPC over time. And of course, nothing is finished yet. But from the architecture of the chatbot ad offering itself, is there anything that they could do that would be more or less advantageous for you to partner with? Are there any kind of structures that you kind of hope that they might lean toward?

Mark Zagorski: Thanks for the question, Andrew. You made some great points. The first is that the model is evolving, and it’s evolving very quickly, right, as both advertisers experiment and as the LLMs experiment with advertising, right? So they’re changing pretty quickly. The current setup of the structures actually lean very well into what we do very well, which is analyzing content and context that’s text-based at scale very rapidly. So the way that the engagements are set with consumers, the predominant nature of how consumers engage with those chatbots falls kind of very nicely into what DV has done for the last 15 years, which is analyze advertising in contextual or text environments. So that current structure actually fits well to what we do.

Our experience working with walled gardens and getting real-time feeds of content, whether it’s from folks like TikTok or others, gives us kind of a really strong legacy to build upon, to be able to analyze the ads in those environments. So I guess that’s a long way of saying we’re pretty flexible. We’ve built for many different types of systems from video systems to short-form video systems to text-based open web engagements. So the way that ChatGPT or any of the platforms are set up today are relatively easily engaged with our current system and our current classification system based on what we’ve done in the past. So we are ready. We’ve built for very challenging environments before, real-time environments, unique environments based on an individual engagement.

And I don’t think this is going to be a significant lift for us to move beyond that.

Operator: Your next question comes from the line of Matthew Condon with Citizens.

Unknown Analyst: This is [ Briana ] on for Matthew Condon. Just a question. You’ve raised the Authentic Advantage on YouTube ACV to $10 million from $8 million last quarter and then Meta activation, I think it was now $12 million versus $8 million prior. Just can you help us understand the incremental growth you’re seeing within these 2 products? How much is it coming from new advertisers? Or is it more so the existing advertisers ramping spend?

Mark Zagorski: So it’s a combination of both. So it’s current DV advertisers that we’ve upsold to this solution launching and the previous advertisers who we brought on board actually scaling. As we’ve noted, we went from high 60s number of engagements to 80-plus now. So we’ve got new customers scaling the solution on Meta Prebid. The same kind of scaling is happening on Authentic Advantage. So it is a combination of both. What we love about it is once advertisers get engaged, they really do stay sticky and scale with us over time. And we’ve got a handful of our largest advertisers kind of growing at very solid rates across both Meta and Authentic Advantage. I mean when you get a 90% growth rate on something like social activation, it’s going to be fueled not just by new customers, but by current customers really starting to scale their business, and that’s what we’re seeing here.

Unknown Analyst: Got it. That’s helpful. And then just on the social side, activation grew 92%. Just on activation revenue, it slowed to 6% from the 4Q number. Just can you help unpack what’s going on within that line item?

Nicola Allais: Yes. So activation for the quarter was up 6%, which equates to the growth that we had in the fourth quarter of last year. Mark spoke of the social activation growth, which is a high percentage on a smaller base. The rest of the business, as we said in our remarks, has remained fairly steady in the first quarter, and the majority of that business would be driven by mobile and online video and display business. Now we are obviously focused on being able to verify and continuing to grow where the advertisers are spending. And so tied to that growth that you see on social activation is the social measurement growth of 23%. Those are the vectors that we’re focused on so that we’re able to continue to verify wherever the advertiser is spending.

Operator: Your next question comes from the line of Mark Murphy with JPMorgan.

Mark Murphy: I’ll add my congrats. Interested in behaviorally, what are you seeing out of the group of 6 or 7 of the large retail and CPG companies that had started to drag on your growth rates. I think that was about 1.5 years ago. And with the understanding, obviously, you would have lapped that slowdown. Is there any signaling from those companies relating to their own internals or how they’re coping with commodity prices or consumer spending trends? I’m just wondering if you see any kind of different behavior there? And I have a quick follow-up.

Nicola Allais: Mark, we’re not seeing any different behavior than the overall vertical, right, for both CPG and retail. And as I said earlier, Retail, in particular, we’ve sort of seen the spend patterns normalize after the end of last year, which is a positive for us. And then in general, across the verticals, basically all of our key verticals showed growth in the first quarter. So the performance we had was spread. We are diversifying away from CPG and retail because we have large clients that are scaling, especially in healthcare and technology. And so as much as we can diversify as a result of us signing larger brands in different verticals, that obviously helps the business. But to go back to the initial part of your question, what we saw in Q1 is more of a normalized pattern of spend for CPG and retail.

Mark Murphy: Okay. That’s encouraging. So my other question is coming back to the prospect of working with the LLM providers, whether it’s OpenAI or Perplexity or someone else. I’m curious when you think might be the earliest opportunity for some of those ads to maybe run in scale where they could conceivably be measured and verified in a way that would start to contribute noticeably. And then — and also, is the push to do this coming more from the LLM providers themselves? Or do you think it’s coming more from the brand advertisers?

Mark Zagorski: Yes. Mark, it’s a great question. Things are moving very rapidly on the LLMs with regard to advertising. We’ve mentioned in the last call and this call that our advertisers are more than excited to test them out, but to scale budgets, and they’ve been very clear with us and their agent has been clear with us to scale budgets, they’ve let the platforms know that they’re going to need third-party measurement, they’re going to need more transparency and more verification. So the drive to kind of integrate into the platforms is really coming from our partners and the brands who want the same level of transparency, the same level of currency-type measurement on the LLMs that they get everywhere else. I mean, on Meta, on YouTube, on TikTok, on the open web, on streaming, they get that kind of agnostic verification and they’re demanding it on the LLM.

So things are evolving rapidly there. We saw this week that ChatGPT and OpenAI opened their ad platform to numerous third parties to buy — to allow for buying and creative optimization on those platforms. So it’s clear that they’re definitely embracing the marketplace. They’re embracing third parties to come in and help build that business. And when you throw a number out there like $100 billion by 2030 in ad revenue, they’re going to need partners to do that. So we’re very positive and bullish on the opportunity. It certainly hasn’t materialized yet, and we’ve been very clear on that, but we do believe that if we can use history as a guide with what’s happened with social with us and streaming and mobile, et cetera, that we think this will be a great opportunity for DV down the road.

Operator: Your next question comes from the line of Tim Nollen with SSR.

Timothy Nollen: Could I switch topics to CTV? Actually, you’ve had an announcement or 2 during the quarter. And I’m just curious, what are you bringing to TV measurement to CTV that is new and different versus what has existed thus far? And I’m using the term measurement loosely, there’s a lot of new ways to measure TV. I’m just curious what is the opportunity for DV in a much more complicated TV market these days than it used to be. And just relatedly, you mentioned MTMs for CTV were up 28%, I think, in the quarter. Could you just put that in a bit of context for us? I assume that’s accelerating on the new products and kind of where is that trending for the rest of the year?

Mark Zagorski: Yes, Tim, thanks for the question. We’ve said that of our — we’ve got 3 pillars we’re focused on for growth: social, AI, which we spend a lot of time on, but streaming is incredibly important to us as well. Impression growth last quarter was up 28%. And it was driven by higher attach rates for some of our new solutions. So the launch of verified streaming TV, which gives advertisers the ability to actually measure and ensure that their ads are being delivered on a high-quality full episode player, not on an outstream or embedded video someplace that it is a truly streaming TV environment. That is gaining traction and driving attach rates up on the post-bid measurement part of our business. We’ve also seen with our tools like the automated do not air list which allow advertisers to create dynamic exclusion lists of programming that they don’t want to be around.

Our attach rate has almost tripled for that across our prebid solutions on specific DSPs. So we’ve seen attach rates grow, which drives prebid. We’ve seen — and when prebid attach grows, post-bid attach measurement grows as well. And I think it’s because that advertisers have been demanding more transparency on CTV, right? Believe it or not, they probably get less granular verification data on CTV than they get on social or even on like short-form video and YouTube. So I think our solutions are starting to touch a nerve with advertisers. It’s driving up attach rates. And it’s increasing, obviously, the number of impressions that we’re measuring across streaming TV as well. This is all good for us. Attach rates mean more money on how people are using our solutions more.

Nicola Allais: Yes. And Tim, on your question for the volume of impressions. So yes, it grew 28% in the first quarter, and we do expect that to continue to outpace the overall revenue growth of the company just because it is the area that is growing. So we do expect that to continue.

Timothy Nollen: Okay. And just a quick follow-up. When you’re talking about — I use the term CTV again kind of loosely, but — and you mentioned streaming, Mark, are you specifying this from video that you’ve been measuring on — in other areas like in social?

Mark Zagorski: Yes. CTV, we designate as something that actually ends up on a large player in a living room. Streaming TV includes CTV, but includes high-quality branded entertainment that may end up, for example, on a mobile device or a tablet, but it’s Hulu. It’s not a TikTok video. It’s Paramount. It’s not a reel. That’s different. So streaming TV, think of it includes all high-quality TV. CTV includes stuff that ends up in your living room on a big screen.

Operator: Your next question comes from the line of Youssef Squali with Truist.

Robert Zeller: This is Rob on for Youssef. On the gross margin expansion due to AI, I’m just curious if we could unpack that. And then is this the new norm for 2026? Or are you still targeting the 80%? And then I’m just curious on the drivers behind the sequential trend in large advertising customers and ARPU for that as well.

Nicola Allais: Yes. So on the gross margin, we achieved 82% in the quarter. And the way we’re able to do that is that we are using AI tools to essentially allow us to verify and classify content a lot more efficiently. And our expectation is that even though the volume of impressions that we measure will continue to grow, we’ll be able to maintain a healthy gross margin. Whether it’s 80% or 82%, it’s going to depend a little bit on the volume that comes from the new batch of verification that we will have to do, including on the AI platforms. So it’s hard to say. But one thing is certain is that we will be able to continue to remain efficient as the volumes grow. And so 80% is a safe benchmark, and it’s a very healthy benchmark.

And then on the other question, which was trending on large advertisers, what we’re seeing — and we called this out in the last call, which is the average dollars per client for the top 100 is continuing to grow year-over-year. We look at that on an annual basis, but it is certain that our large advertisers are being upsold to the new solutions and are part of the growth rates that we mentioned on social activation. So the ARPU is growing as we’re able to offer them new products, especially on social and soon on CTV.

Operator: Your final question comes from the line of Justin Patterson with KeyBanc Capital Markets.

Jacob Armstrong: This is Jacob on for Justin. I guess kind of hitting on that last point about how you’re using AI internally on classification. Can you talk about maybe some of the areas that DoubleVerify is using AI internally in terms of ramping engineer productivity and maybe how you’re keeping that — keeping a scaling token costs in mind while kind of ramping adoption internally these tools?

Mark Zagorski: Yes. Thanks for the question, Jacob. We look at obviously, 2 large buckets of how we are leveraging AI. First is in kind of internal execution where we focus on efficiency and effectiveness and better client engagement. And the second major bucket is kind of the AI product development, which we’ve talked about a lot on this call. When it comes to kind of internal AI execution, we are focused really on agentic development and using agents to create code. So far, we’ve seen 40% faster software development. We’re triaging IT tickets at rates we’ve never seen before. And it’s allowed us to, as we’ve said before, maintain a headcount that will continue to show efficiencies over the coming year. So, a, just in general, engineering operations, we’ve been able to balance the cost of tokens with kind of the impact on it.

And we look at everything from an ROI perspective when we lean in on using AI. You also mentioned core classification. And we’ve been using that to help our core systems kind of do what they do much faster. It’s increased our productivity by 4x in classification. We’re driving labeling, what we do when we label content by about 2,000x faster. And we’ve been very clear that we’ve got a decent number of contractors that have been helping us with the labeling and feeding our models. That number of contractors will be reduced by over 100 by the end of the year. So we’re seeing efficiencies by using AI and an engineering team across core classification. And eventually, we’re going to see this with client interaction as well as we start moving towards more natural language interfaces that enable better client interactions with less client service engagement and overhead.

So it’s a big impact on our operations. That’s why we’re seeing not only increasing margins, but faster go-to-market with product and more efficient client engagements.

Operator: I will now turn the call back over to management for closing remarks.

Mark Zagorski: Thank you all for joining us this evening. As we look ahead, we remain confident in the performance of our business and our priorities are clear: deepen adoption of the core products with core customers, accelerate the growth of our solutions for social, streaming TV and AI and drive industry-leading margins by leveraging the power of AI. We appreciate your continued support and look forward to connecting with many of you at upcoming conferences.

Operator: Ladies and gentlemen, that concludes today’s conference call. Thank you all for joining. You may now disconnect.

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