Ladies and gentlemen, thank you for standing by, and welcome to AdTheorent's Q1 2022 earnings call. At this time, all participants are in a listen only mode. After the speaker's presentation, there'll be a question and answer session. Please be advised that this conference is being recorded. I would now like to turn the conference over to your first speaker, David DiStefano, Investor Relations. David, please go ahead. Good afternoon and welcome to AdTheorent's Q1 2022 earnings call. We will be discussing the results announced in our press release issued after the market closed today. With me are AdTheorent's Chief Executive Officer, Jim Lawson, and Chief Financial Officer, Chuck Jordan. Before we begin, I'd like to remind you that today's conference call will include forward-looking statements based on the company's current expectations. These forward-looking statements are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release and our other reports and filings with the Securities and Exchange Commission. All of today's statements are made based upon information available to us today, and we assume no obligation to update any such statement except as required by law. We will also refer to both GAAP and non-GAAP financial measures during the call. You can find the reconciliation of our GAAP to non-GAAP measures, including in our press release posted to the investor relations section of our website at www.adtheorent.com. All of our non-revenue financial measures we discuss today are non-GAAP unless we state otherwise. With that, let me turn the call over to Jim. Thank you, David, and good afternoon, everyone. Thank you for joining our Q1 2022 earnings call. We are extremely pleased with our performance in the quarter. We delivered $34.2 million in revenue, 11% year-over-year growth and in line with our guidance, increasing wallet share with existing customers and bringing new logos onto the platform. Adjusted gross profit of $23 million was also up 11%, exceeding the high point of our guidance. We are pleased with our performance in the Q1. Demand for our machine learning-driven solutions remains extremely strong, and as a result, we are on track to meet or exceed our guidance for full year 2022. Before I dive into Q1 highlights, I'll provide a brief overview of what we do and how we win. While other DSP platforms focus on targeting users, AdTheorent predicts the performance of media opportunities using the industry's most advanced machine learning-powered media buying platform, and we do it in a privacy-forward way. Unlike other targeting approaches, AdTheorent targeting does not rely upon third-party data licenses, cookies, device IDs, or any of the new unified or individualized IDs being discussed in the market now. Most important, our platform and products drive industry-leading performance for our customers' campaigns, measured in real business terms such as incremental sales, store visits, registrations, travel bookings, online orders, drug prescription fills, insurance policy sales, and other business outcomes. We believe we are poised to lead the digital advertising industry into the post-ID era, where machine learning and statistics give advertisers unprecedented levels of targeting accuracy, but consumers are not alienated by corporate monetization of their identities. That is why we win. It is not just that we have a superior platform today. Our platform gets better every quarter as we operationalize and automate new and innovative machine learning advancements within our platform and verticalized solutions. Every enhancement we launch, every data partnership we bring on, and every campaign that we run improves our ability to drive campaign KPI performance for our brand and agency customers. As these improve, the gap between the return on ad spend we deliver relative to what our peers can produce continues to increase. The immediate result is increased wallet share as existing customers spend more of their campaign dollars with AdTheorent, and this momentum will increase as we start to see the real benefits from our sales and marketing investments. Importantly, we have and will continue to drive this growth profitably. Adjusted EBITDA came in above the high point of our guidance at $1.3 million for the quarter, despite meaningful growth investments across all facets of the business. Later in the call, Chuck will walk through the drivers of this performance. Before I turn it over to him, I wanna highlight a few wins from the Q1, including strong connected TV or CTV growth, several meaningful platform innovations, a new data partnership, and some news on Direct Access. Starting with connected TV or CTV. AdTheorent's unique ML-powered advancement, which we discussed on our last call, further increased the differentiation of our solution in this dynamic and rapidly growing channel. As a result, we delivered 42% CTV revenue growth during the quarter. This exceeds projected 2022 industry growth and is better than the growth many leading market participants have reported for the quarter. As it does on other screens, our data-driven and performance-focused CTV product and platform capabilities and the meaningful enhancements we continue to release are a competitive advantage that will sustainably drive above-industry revenue growth. Now let's talk about some of our platform enhancements for the Q1. These further exemplify our dedication to enhancing our existing technology advantages using focused innovation. There are many, but I would like to talk about three meaningful platform enhancements from the quarter. The deployment of our Inventory Marketplace, a big leap forward in our optimizer technology, and groundbreaking advancements in our cost per action, or CPA, models and full funnel capabilities. First, our new Inventory Marketplace lets customers bundle and package publisher digital inventory across campaigns, addressing a significant deficiency in the programmatic ecosystem caused by the fragmentation and inconsistency in publisher and content details. For example, CNN programmatic bid requests can appear in many ways, as a site domain, cnn.com, as an Android or iOS mobile app, or as a CTV app, to name a few. This fragmentation makes it difficult for advertisers to target a desired publisher's content. Our Inventory Marketplace unifies this publisher inventory into a single targetable entity, unlocking operational efficiencies and ease of use. It also allows customers to create and activate customized groupings of publishers and content, like grouping CNN into a news package for an end user who wants to target news content, or groupings by rating or language. All of this lives within a robust and easily activated library within the AdTheorent platform. Another meaningful platform enhancement relates to our optimizer technology. Our suite of optimizers provides automated algorithm-based campaign decisioning far more quickly and effectively than peer solutions, which are more reliant on the behaviors of individual traders. This is a big deal because widely varying media prices across the programmatic ecosystem often cause marketers to overpay for inventory if they bid too high, or exclude inventory if they bid too low. This is especially true for CTV, where pricing variation can be extreme. In Q1, we released a price optimizer enhancement that can dynamically adjust a single user-entered bid price using details about the CTV publisher, content, genre, and rating. This frees our customers from managing multiple, often widely variant bids. In the Q1 alone, this generated 1.5 million bid price adjustments, or an average of 12 bid price changes per minute without a trader. We also launched the first iteration of a multi-goal optimizer, which is designed to optimize campaign delivery simultaneously towards both bid price and KPI performance. Typically, price and performance are independent and inconsistent variables, requiring multiple tactics to manage a campaign. In other words, frequent and ongoing manual decisions about how to balance the usually competing goals of price and performance. Combining both price and performance into a single model obviates the need for multiple tactics, creates operational efficiencies, and advances advertiser goals. During the Q1, campaign data showed that the multi-goal optimizer improved campaign KPI performance by over 30% and cost efficiencies by almost 20%. During the quarter, we also made great progress expanding our full funnel approach to campaign and KPI optimization. By way of background, advertisers invest their media budgets across the entirety of the purchase funnel, meaning from preliminary awareness to investigation and discovery to pre-sales or sales activities. Different tactics are required at each funnel depth. For example, when we help an airline looking to optimize bookings, we may use CTV capabilities to drive upper funnel conversions, such as landing page visits, rich media to drive middle funnel conversions like browsing deals, and targeted display to drive lower funnel conversions such as bookings. AdTheorent's full funnel capabilities center around using machine learning intelligently to activate all these tactics as part of an integrated media plan, driving conversions at each funnel depth, deriving learnings at each stage of the funnel, and increasing our revenue opportunity. During the quarter, we launched important enhancements to our full funnel approach, including introducing funnel depth features into our CPA models, expanding on our already advanced model inheritance capabilities, and we introduced Conversion Influence Reporting to validate the efficacy of our performance at each stage of the funnel and illustrate how exposure throughout the funnel drives performance. These initiatives increase our ability to leverage the upper and middle funnel to drive superior lower funnel KPI conversions for our customers. I will briefly unpack each of these advancements and note how they will help us drive revenue. The new funnel depth enhancements improve how activities indicated as upper or mid-funnel conversion events inform our cost per action or CPA model, driving more efficient CPAs for the campaign's ultimate business goal or KPI. Prior to implementing funnel depth features, our model did not differentiate between engagement at the different depths of the funnel. As a result, they initially optimized toward landing page views, for example, or other high volume upper funnel actions until this generated sufficient KPI conversions to switch to a KPI-based model. With our new funnel depth information, as soon as we have enough next level events within the funnel, the model dynamically switches, getting us from zero to sixty much more quickly. In some early campaigns, getting to KPI or conversion-based targeting in just a couple of days. Bucketing activities by low, mid, or upper funnel, as well as recency and frequency, also allows us to score engagement at various funnel depths and have a more data-driven understanding about conversion at each phase of the funnel. These new funnel depth enhancements represent a key advancement to our existing model inheritance capabilities, which is essentially our platform's ability to use the predictive score from one model as an input or variable to another model. For example, we can use a click-through rate model or brand safety model as a variable or input in the CPA model. In the end, this drives operational efficiencies by reducing the number of tactics needed to create and manage the conversion funnel. Most important, the ability to guide consumers through the conversion journey is paramount to advertisers seeking demonstrable ROI on their media spend. The better we do this, the more advertiser budgets we earn. Equally exciting, and building on our full funnel capabilities, during Q1, we introduced our Conversion Influence Reporting, which highlights the effectiveness of upper and mid-funnel media exposure on the resulting conversion events by showing how different media types, line items, creatives, and strategies work together to drive conversion. For example, these reports can highlight that one media type drives the user to a landing page, while another takes the user from landing page to KPI conversion. Or it could show that a combination of creative and tactics are required to drive the conversion event. In Q1, we executed a campaign to drive home and auto insurance quote complete for a national insurance company, running a mix of cross-device display and video tactics. Our conversion influence reporting showed that users exposed to both video and display media converted at a 612% and 112% higher rate than those exposed to just video or display, respectively. This reporting illustrates the efficacy of the AdTheorent capabilities and drives customer retention and revenue growth. Moving on to our data infrastructure and how we are expanding our 1P data to drive results for customers. In the Q1, we finalized an important new partnership with a leading consumer data provider. This critical integration gives us more than 700 additional data signals for bid request scoring and modeling. In addition to more than tripling the number of available signals, these high-quality signals are indicating strong relevance to conversion uplifts and increasing the predictive ability of our models. As we noted in our last call, programmatic advertisers value unique first-party data and data insights. Our ability to leverage our ML capabilities across valuable seed datasets allows us to offer unique first-party data insights, which further differentiate us and advance our proprietary predictive modeling and measurement capabilities. This continuous innovation produces unmatched ROIs for our customers and drives our market share. Finally, I want to share some news on the ongoing investments we are making behind Direct Access. As we have noted, our platform is our product, and our customers can transact with our platform in different ways. Historically, most have used AdTheorent as an end-to-end full-service in-house digital partner, leveraging our teams for strategy, ad operations, campaign optimization and yield, client success, data and analytics, data science, creative, and more. However, we recognize that some customers, both agencies and brands, have some of these media execution resources in-house. They have not historically been AdTheorent customers, as they would prefer to leverage their internal teams to execute and manage campaigns with our platform. As a result, offering Direct Access enables us to transact with a whole new subset of potential customers using an enterprise pure platform offering model. Our Direct Access offering does not cannibalize our end-to-end offering. We are not transitioning existing customers to it, and it does not pressure our financial model. We are simply expanding our addressable market. We are excited to note that we hired Paul Dolan during the quarter, in part to help spearhead the growth of this initiative. Paul is an industry veteran with a long, successful track record in programmatic ad tech. Prior to AdTheorent, Paul was a founding member of programmatic media company Xaxis, as well as CEO of MDC Partners' media platform consultancy, Varick. His expertise will help guide our Direct Access efforts through the next phase of development as we continue to scale this offering and bring it to market. I would like to conclude my remarks by thanking the AdTheorent team, which is working harder and is more motivated than at any point in our ten-year history. Our team appreciates the immense business opportunity that our profound market differentiation makes possible. Despite broader macroeconomic uncertainty, we are tirelessly pushing the boundaries to increase our competitive advantage in the DSP landscape. This has been instrumental to the strong quarter just reported and is the reason we are able to reiterate confidently our guidance today. I will now turn the call over to Chuck to talk about our financial results and the exciting momentum we see in the business. Thank you, Jim, and thanks again to everyone for joining us today. Before discussing detailed financial results, I'd like to point out that in addition to our GAAP results, I'll be discussing certain non-GAAP results. Our GAAP financial results, along with a reconciliation between GAAP and non-GAAP results, can be found in our earnings release that is posted on our website, www.adtheorent.com. As Jim mentioned at the outset, we extended our track record of delivering strong, profitable growth in the Q1. Our revenues were up 11% year-over-year, driven by continued strength in the company's healthcare, pharma, and retail verticals. Adjusted gross profit as a percentage of revenue was 67.1% for the quarter, in line with the Q1 of 2021. During the quarter, we invested across all facets of the business and still delivered $1.3 million in Adjusted EBITDA above the high end of our guidance range. Now I'll walk you through our Q1 financial performance and then discuss our guidance for the Q2 and for the full year of 2022. Our business is seasonal, with Q1 revenues typically the lightest quarter of the year, following our Q4, which is historically the strongest from a top-line perspective. Total revenue in the Q1 was $34.2 million, an increase of $3.3 million, or 11%, as compared to the Q1 of 2021, due to continued strong demand for our performance-focused and privacy-forward offerings with both existing and new customers in our top verticals. Our CTV revenue grew 42% during the quarter to $2.5 million as compared to $1.8 million Q1 of 2021, fueled by expanded capabilities and integrations. In discussing the remainder of the income statement, unless otherwise noted, all references to our expenses and operating results are on a non-GAAP basis. You can find information on the most directly comparable GAAP metrics in our Q1 earnings press release. Adjusted gross profit, a non-GAAP metric that removes traffic acquisition-related platform operations costs, in the Q1 was $23 million, or 67.1% of revenue, compared to 67.2% in the same period of the prior year. Moving down the income statement to operating expenses. Q1 operating expenses were $38 million, an increase of $10.4 million or 38% versus the Q1 of 2021. The major drivers of this increase include increases in hiring-driven salaries and related costs of $2.4 million. As in the past, our hiring was focused in our sales and marketing, product, and technology teams. Public company-related increases in insurance, legal, and professional totaled approximately $2.1 million. Revenue-driven tech costs were up approximately $1.1 million. Software and hosting expense was up $1.5 million as well. Moving to earnings, we exceeded the high range of our Q1 guidance with our Q1 Adjusted EBITDA coming in at $1.3 million versus $6.7 million for Q1 of 2021. Adjusted EBITDA margin for the quarter was 5.6% versus 32.4% for Q1 of 2021. Now let's turn to our guidance for the Q2 and full year 2022. Q2 2022 revenue is expected to be between $45.2 million and $46.2 million, representing an increase of 13%-16% compared to the Q2 of 2021. Despite global supply chain disruptions continuing to impact the timing of the spend, in the aggregate, we continue to see substantial and growing demand from our customers across a diverse set of verticals. For the full year and consistent with previously provided guidance, we expect revenue to be between $202.2 million and $206 million, representing an increase of 22%-25% compared to 2021. We expect growth to increase materially over the course of the year as the significant investments made in 2021 in our sales organization and platform further materialize. Q2 2022 adjusted gross profit is expected to be between $30 million-$30.8 million, representing an increase of 13%-16% compared to the Q2 of 2021. For the full year and consistent with previous guidance, we expect adjusted gross profit to be between $131.5 million-$134.5 million, representing an increase of 20%-23% compared to 2021. Q2 2022 adjusted EBITDA is expected to be between $6.5 million-$7 million. We are also reiterating our full year 2022 adjusted EBITDA result to be between $31.6 million-$32 million or approximately 24% of adjusted gross profit. Adjusted EBITDA guidance reflects increased year-over-year operating expenses driven by investments to capture additional growth opportunities, some of which Jim described. Among other areas, investments have been and are being made in sales and marketing to continue expanding our footprint in order to keep up with demand, as well as technology and product to continue to enhance our platform and offerings and allow us to roll out more products faster. Additionally, and as anticipated, our increase in general and administrative expenses is largely driven by public company costs not incurred in comparable periods in 2021. Finally, it is worth noting that our 2022 guidance does not include the impact of potential M&A. In summary, we're pleased with our financial results, outperforming our guidance for the quarter and remain very enthusiastic about our strong outlook for 2022 and beyond. Now I would like to turn it over to the operator to moderate our Q&A session. Thank you. To ask a question, you'll need to press star one on your telephone. To withdraw your question, you press the pound key. Again, to ask a question, that's star one. Our first question comes from Maria Ripps from Canaccord. Your line is open. Great. Thank you so much for taking my questions. Last quarter, you talked about some of the marketing campaigns that have been shifted closer towards Q2 and maybe later in the year because of supply chain sort of issues. Have you seen sort of those campaigns materialize? Sort of just wanted to get an update on what I see in there. Then secondly, given your diversification from the vertical standpoint, can you maybe just talk about some of the verticals and sort of how they're performing, given all the sort of macro headwinds? Yeah, Maria, thanks a lot for the question. We feel really good about where we are at this point in the year. In advertising, you're always gonna have some movement from either quarter to quarter or month to month. We bake that into our plan, and that's something that we expect and plan for. You're gonna see a little bit of that, and we saw some of that certainly in the Q1. We're an interesting time in history, but it wasn't anything that we weren't expecting. Frankly, the supply chain challenges were, you know, there last year, and we navigated through that, as well. We're not surprised by it. We baked it into our plan. We have a prudent plan that contemplates the macro backdrop that we are in. We believe that, you know, some of the movement that we saw in the Q1, for example, we're gonna keep in the year, so we feel quite good about it. That's why we're confidently reaffirming our projections for the year. With respect to verticals, we are fortunate in that we have a wide variety and diversification of verticals. Top verticals for us have been BFSI, banking, financial services, insurance, and pharmaceutical. Those verticals have been largely immune from many of the challenges in the supply chain. You know, again, we have a lot of verticals, and we're seeing a lot of excitement and growth across the board. We don't report out specifically at this point the vertical growth quarter-over-quarter because we're new as a public company. We have a lot of exciting things going, creating a lot of new differentiation across those verticals, and it's a huge part of our growth story. Great. Thanks so much, Jim. Thank you. Our next question comes from John Blackledge with Cowen. Your line is open. Hi, good afternoon. This is James Kopelman on for John. With the continued push towards greater data privacy for consumers, I'm curious what kind of conversations you're having with advertisers, given your platform is obviously well-positioned as an alternative for many of these marketers. With the upfronts now behind us as well. What are the key trends you're seeing, and do you still plan to accelerate advertising efforts to attract these advertisers? Then as a quick follow-up, in terms of geographic expansion, could you just remind us which territories or regions should we be thinking about in terms of expansion and any color around potential timeline would be helpful as well. Thank you. Yeah, thank you for the question. One of the great benefits to the data approach that we take in that we do not rely upon user IDs and individualized data for ad targeting is that we're the most privacy-forward version of programmatic advertising that's really ever existed in the market. We believe that we're poised to lead the programmatic industry into a post-ID era, and that's because we use statistics. We score impression opportunities based on statistics about those opportunities, and we're not in the business of profiling users. CMOs wanna talk about that, our clients wanna talk about that, and it's been a huge win in our sales as we've been speaking about our business and our opportunities. One of the great benefits of being on this bigger stage is that we have more of an audience, and we're talking to a lot of great clients and opportunities about the predictive advertising possibilities and how you can move beyond cookie-based retargeting, and you can move beyond segment-based retargeting that are ID driven. We could not be more excited about the upside possibilities for the business for that. The regions in which we operate currently are the U.S. and Canada. Having said that, we're doing some very interesting testing on campaigns in Europe. We made some great progress in the Q1, and we look forward to sharing some of that information as we go. We believe our statistics-based, privacy-forward method are GDPR compliant by design, and that we think that we will have some very exciting opportunities in other geographic regions as we go forward. Great. Thanks a lot. Congrats again on the quarter. Thank you. Thank you. Our next question comes from Laura Martin with Needham. Your line is open. Hi there. I have two strategic and one financial. I'll ask the first strategic one this way. Everybody's trying to solve the cookies deprecation of ID. You guys have solved it through AI. My question is, why is it better than contextual or household IDs or commerce where you close the loop? Do you really believe that the open internet is better off without like a universal ID, a industry-wide solution? You think these point solutions that individual companies are taking, like yourself, actually work to actually make the open internet better in a post cookies world? Laura, great question, and thanks for that question. First of all, we don't think- Sure. That the world is better off without a unified ID that's not tied to cookies. We support those efforts, and we're actually contributing to that marketplace of ideas, ID ideas to get to a post-cookie unified ID. Our point is that we don't need it. We think you're better off being in a world where you can leverage a number of different statistics that are not tied back to the individual. We are supportive of both. We will support the effort to invest in a unified ID, both here in the U.S. and in Europe. At the same time, as that scale, as there's adoption and, you know, driving towards scale there, we don't need a ID in order to effectively target a digital ad. I think that is the key. That's not to say that if an ID is available and it could be used, that we would not avail ourselves of that benefit, but it is better to not be dependent upon an emerging ID structure or infrastructure. That's really what we believe on those topics. We fully support the unified ID both in the U.S. and Europe. We just are not dependent upon it. We believe also that back to your first question, the reason why predictive advertising, which is what AdTheorent delivers, in our view is better, is because the optimizations are tied back to convergent. In other words, if you're trying to sell something and there are ad units that are driving sales, in other words, someone views an ad, and then they purchase a product, if you have information and data about the attributes associated with the user that purchased that product in real time, that's more valuable than assumption about a user because of what ID they have and therefore what buckets they are put into. So in our view, real time, literally every day, every second conversion activity is a more valuable input for how do you target an ad than an assumption that was used to put an ID in a bucket or a profile. Okay, perfect. That's super interesting. Let's move to CTV. CTV revenue growth, very impressive at 42%. My question is, you guys have a full funnel. You focused on that full funnel product, offering. My question is, are you seeing that CTV is being used mostly for top of funnel, or is it your experience that CTV actually is being used bottom of funnel so far? Great question. CTV, in our view, can be both. We are very excited about our advancements in full funnel because we believe that the more data we have from all aspects of the funnel, the more effective we will be driving sales or driving conversion. In the market generally, CTV is an upper funnel tactic. The work that we have made, the work that we have put in, that we talked about after our, you know, 21 call. We talked about our content object, our metadata work, our work with fraud prevention, our work with Comscore and QR code. A lot of things that we are doing to make post CTV view more focused on performance. That's something special to AdTheorent. We believe that CTV, generally speaking in the marketplace, is an upper funnel tactic, and we believe we're bringing more of a lower funnel or a whole funnel focus to it, where we can use the data from the upper funnel to drive the lower funnel, and we can use CTV on its own as a performance-driving tactic. Okay. The way I interpret that answer, that $2.5 million of CTV revenue so far is mostly being used as upper funnel, and you guys are gonna try to really push people into full funnel consideration for CTV. Do I have that right? Yeah. I mean, I think the customers that we are talking to about CTV are very intrigued by the way that we use data, and that many of them are customers on other screens. They're very interested in using our CTV product because we bring so much more to it. We're not just trying to find screens and users on screens. We're trying to find who is gonna view an ad and then take an action after viewing that ad. We have capabilities, and we're making investments to do that better. Okay, cool. 'Cause I agree with you. I think bottom of funnel is super exciting. It's great you guys are on the cutting edge of that. Let me ask one financial question. Yep. I had revenue growth up 11% in Q1. We're gonna have to lower our Q2 estimates a smidge to growth of about 13%, and yet you're holding full year revenue estimates, and I'm thinking gross revenue, right now, at about 22%-25%. That would imply in the H2 of this year, you have to do, like, 30% year-over-year revenue growth to actually meet your full year guidance given the lower estimates for Q2. Can you defend? Can you tell us why you think you can accomplish that? Absolutely. I'm glad you asked that question. Our 2022 plan assumes directionally the same level of revenue contribution in the first two quarters as our 2021 plan. Our business is seasonal. It's been seasonal for ten years. We are fully on track with the H2 of the year taking us to our annual objective. Our annual forecast is prudent. It is not aggressive. We believe that we have exactly what we need to get there. None of the forecast even contemplates the contribution that we're gonna get from the investments that we've made on the revenue side, the sales and marketing. If we track the contribution by quarter that we did last year, we achieve our goals. If we increase that, we do even better. We feel really good about where we are, given the investments that we're making, to contribute to the Q2 of the year. Okay. It's not your point of view that this year's Q2 is a much worse macro with more uncertainty impacting ad spending than last year's H2. That's not your point of view, I guess. No, we're not seeing that at all. I mean, I think last year's H2 had its challenges, certainly. There was a lot of uncertainty. I think with the pandemic ending, and a lot of the optimism there, we feel really good. We're not seeing it. We're not seeing any pullback or concern worth noting from our customer base. We see a lot of optimism in terms of marketing and advertising products and services across all of our different verticals. It's nice to see a lot of the verticals coming back strong after being challenged in a pandemic environment, in an economic shutdown environment. No, we're not seeing that at all. Fantastic. Thank you so much for your answers. Really appreciate it. Very helpful. Yeah. Thank you, Laura. Thank you. As a reminder, to ask a question, you'll need to press star one on your telephone. Our next question comes from Andrew Boone with JMP Securities. Your line is open. Good afternoon, and thanks for taking my question. Jim, there were three main products that you highlighted in the press release, as well as in the script, in terms of Inventory Marketplace optimizer and then full funnel campaign and KPI optimizer. From the outside, it's a little hard to understand the importance of these various products as they go live. Is there one that really stands out in terms of really being able to move the needle? And then what else are you really excited about in terms of the business that you think investors should be focused on as something that can change conversion rates and really drive performance for advertisers? Thanks so much. Yeah. Thank you, Andrew. Great question. You know, we realize when we share some of these product and tech and data science advancements, that many of them are quite technical. We also feel that it's valuable to share the level of innovation that's taking place at AdTheorent. Our view on the market and our view on capturing a larger share of the market is that the more differentiation that we have and the more ability that we have to drive an efficient cost per action, so we're able to drive sales for less cost than the other platforms, the better we do that, the more opportunity we have, the more revenue we have. It might seem technical, but our ability to leverage upper funnel and mid-funnel outcomes as part of our CPA models, which are really the models that drive conversion activity in the lower funnel. Our ability to do that better, our ability to do that faster, our ability to get models tuned and actually optimizing based on conversions, drives that CPA down and makes our customers happy. When our customers are happy, we get bigger budgets and we have more opportunities. We're excited about it. I think it comes through in just the level of effort and the work that we're putting into these advancements. It's really gonna move the needle for our business. When we think about things like model inheritance, the ability to take multiple models and use model inputs from one model in another model, again, our cost per action model, the goal is advertisers spend money with us. They wanna spend as little money as possible to drive an action, and that is what we do. That is our mission. The better we do that, the more revenue we can drive. With respect to, like, the Conversion Influence Reporting, that's just about us getting credit for our work. We can drive and we can do different things at different phases of the funnel. We can use a CTV upper funnel or mid-funnel. We can use rich media to drive engagement and do different things and really drive user engagement. Then at the end of the day, we're trying to sell a product for a customer. Our ability to connect the dots and identify and quantify the contribution of those media investments at different phases of the funnel, again, drive confidence with our customers that we're showing them, "This is what you spent your money on. This is what we delivered." We're delivering a really transparent version of programmatic digital advertising that I don't think it's ever been done before. Thanks so much, Jim. Thank you, Andrew. Thank you. Our next question comes from Dan Kurnos with Benchmark. Your line is open. Great. Thanks. Good afternoon, Jim. Couple things I wanna touch on. I think the publisher unification, inventory unification tool is super interesting. We just hosted teams today, and you know, they've got access to a ton of premium publisher inventory. We talked with SSPs that really kinda highlight, you know, kind of that expansive access, and we're starting to see some repackaging of some of their own, you know, tools and inventory or access to kind of different brackets there. Obviously, you guys, you know, utilize the SSP side of the market, and I'm wondering, to the extent that this sort of I know this hasn't historically been true for you, but if this potentially deepens the relationships with some of the SSPs that you can get access to start sort of alerting them that, hey, you know, this tool will simplify and allow brackets so that way in a safe, brand safe, and selective way, you know, we can kind of direct advertisers to your premium publishers and thus drive up yield across the chain. I'm curious if that is a potential use case for this. Dan, that's a great question. We are having some really exciting conversations with our publisher partners, our SSPs specifically about the way that we can make their inventory more valuable. You know, at the end of the day, you know, there's some conversations in market about direct integrations with publishers and, you know, maybe not going through the SSPs. For us, the real issue is do you have the best supply? Do you have tools to remove noise and resold inventory and bad supply and those types of things? We believe that our significant advantages in those areas really drive success. Our partnerships with our SSPs are very valuable to us. You know, we think that we can use our machine learning to drive profitability for them as well. They see it because they know that we're able to use our machine learning to find pockets of inventory that might not be considered "premium" by some, but they are premium if they have the right users and if they're the right opportunity for a given product or service. Our ability to use machine learning to find those pockets of value that might not be obvious to everyone is very intriguing to a lot of our SSP partners. Got it. That's helpful. Then Laura kind of touched on the performance side of CTV, but just you guys also announced after Q1 the DV certification. I'm just curious how that helps conversation and to spur conversation if that was a contributor to accelerating growth. Absolutely. It's a component to having a best-in-class solution that we have a zero tolerance for IVT and fraud. Having that certification, having those low rates of fraud and invalid traffic is obviously a key part of the solution. It's table stakes in our view. Definitely, it's a part of our story. We use data both to drive performance, but part of doing that is identifying garbage, eliminating it and not wasting your money on it. Can you expand on the partnership in the quarter? You declined to announce whom, but you know, obviously more variables, better ML, better output, you know, and throughput. I'm just curious. You know, how we should be thinking about order of magnitude, investment or, you know, ROI on that, just any incremental color you can give us on this announcement. Yeah. The more data attributes, the better ability that we have to augment a programmatic bid request with data means that our models have more to choose from when deciding what variables are driving conversions. We've done really well in the past, and we've had, you know, 200 variables, generally speaking. Now we're gonna have, you know, 700 more variables, many of those demographic variables tied back to a location. That is going to give both our models more optionality in terms of what variables, feature selection, are gonna drive conversions, and then we can provide a lot more of a detailed accounting to our customers as to where conversions came from. I think that's an important part of the story as well. I mean, it might. You know, moving from a pure audience mindset to a machine learning mindset requires an understanding that the data at a very granular level is going to drive the conversion. There's also an expectation on the part of the customer that after the campaign, you can tell them the story. Where did the conversion activity come from? Part of these new data integrations, in addition to having more for our models to ingest and analyze and consider in deciding where to bid, and again, this is all in microseconds, we can also tell the story after the campaign that these are where your conversions came from. That's interesting, and that's something that customers are quite interested in talking about. Got it. I really appreciate all the color and you know, nice start to the year. Looks actually 2Q, I thought was pretty good relative to us, so, looks like it's moving in the right direction. Thank you. Yeah. Thank you so much, Dan. Thank you. There are no other questions in the queue. I'd like to turn the call back to Mr. James Lawson, CEO, for closing remarks. Thanks a lot. Just wanted to thank everybody for listening today. In closing, we believe there's never been a better time to be part of the AdTheorent community. We have big plans, and we are executing those plans. We look forward to sharing more updates as our work continues. We're grateful for our investors' support, and we will continue to work very hard to execute these ambitious goals. Again, thank you everybody very much for joining us today. We appreciate it. This concludes today's conference call. Thank you for participating. You may now disconnect. Everyone, have a great day.