Well, welcome, everyone. I'm your host, John Roy, and I cover technology in Water Tower Research. Today, I'm joined by Jim Lawson and Patrick Elliott of AdTheorent. Guys, good to see you again. Good to see you, John. One thing I should mention is that AdTheorent does have that safe harbor statement on its webpage, and if you feel so inclined, you should read it. Guys, like I said, good to see you again. I know we've had a few of these fireside chats in the past, but maybe those knowing you the first time, it would be good to give a brief introduction. Jim, let's just start with a refresher of AdTheorent. Great. Thanks, John. It's good to be here again. As a reminder, I'm Jim Lawson, CEO of AdTheorent. Thanks for the chance to share some of our strategic initiatives for 2023. To give everyone a refresher, AdTheorent is a programmatic demand-side platform or DSP. We use machine learning and data science to execute high-performing digital ad campaigns, we do this by targeting ads to the ideal media impressions. As a reminder, a media impression is digital real estate available for a digital advertisement. There are billions of media impressions available for ad placement at any given moment, we identify which media impressions are most likely to be valuable to our digital advertiser customers. We do this in a way that is privacy-forward, less focused on targeting users than predicting the performance of media opportunities. Most of today's commonly used ad targeting approaches are premised on having access to user IDs or user segments or user profiles. I get it, but if you're targeting ads, how do you do it without having specifically targeting of IDs? How does that work, Jim? That's a great question. Our machine learning platform is designed to augment programmatic bid requests to append a lot of data to each impression. In other words, we have about 1,000 data attributes attached to every digital impression that we consider for an ad. Machine learning and AI solutions are only as effective as the data they utilize. We also do a lot of work to curate and normalize the data that we receive from publishers to make it actionable. Using that data, our platform identifies ad impressions which have the highest likelihood of converting on a client's desired ad campaign goals, whether that be online sales or customer sign-ups or physical world actions such as store visitations. As noted, AdTheorent predictive targeting is not reliant upon third-party data, cookies, device IDs, or any form of unified ID. We're not dependent on them to target ads well or at all. Our targeting approach is not assumptions-driven. For example, assumptions about a user's interests based on web browsing behavior or assumptions based on only on a user's location. Instead, our platform analyzes more than 1,000 data attributes related to each ad impression, which successfully drove a campaign outcome, and then using that data, it predicts which future ad impressions will likewise drive value. Essentially, our platform asks the question: When users engage with a given campaign ad and then went ahead and purchased the advertised product, for example, what data characteristics did those programmatic bid requests have in common? Then we go try to find those programmatic bid requests in the future. This targeting approach is fundamentally different, and in our view, better, because it is based on statistics and data about ad impressions tied to real-time conversion events. Okay, interesting. Who do you typically work with on the client side? We work with the most sophisticated, data-driven advertisers in the world, advertisers who know digital and expect their digital campaigns to drive business results for them, we work across all digital channels: mobile, tablet, desktop, CTV, digital out-of-home. The sophistication of our machine learning technology and capabilities enables us to drive better results for customers, better ROI, better conversions on their campaign goals, that is what has driven our success since 2012 and the reason we are excited about the future. We have a large number of long-tenured clients who rely on our platform's ability to drive return on ad spend. These include agencies and brands directly. Very exciting for us, we are growing a solid base of self-service customers who appreciate our platform's pricing transparency, powerful optimizer tools, both performance and price optimizers, and robust suite of targeting options. Great. All right, Jim. Switching a little bit to talk about earnings. Last week, obviously, you reported your second quarter of 2023 earnings. What were some of the key highlights that you take away from the quarter? Thanks, John. Yes, our continued good work in the second quarter positions AdTheorent for a return to year-over-year growth in Q3 and keeps us on track for achieving our full year goals. In the second quarter, as forecasted, we saw some temporary softness in ad budgets from a few customers, but we are encouraged by the new advertisers scaling revenue on our platform. A couple notes. On a year-over-year basis, AdTheorent Health's advertiser count is 36% higher. The number of advertisers running CTV on our platform is 66% higher. In addition, users of our self-service platform or Direct Access are scaling at a robust pace. In the second quarter, we saw 75% sequential revenue growth, an acceleration from 19% sequential revenue growth in Q1. Predictive Audiences and Health Audiences, our new algorithm-based audience targeting products, are driving adoption as well. During the quarter, 19 campaigns leveraged Health Audiences, 50 additional campaigns utilized Predictive Audiences in verticals besides health. Great. Very impressive. Thanks for the update, Jim. Patrick, I know on the call you mentioned there was some softness in the ad budgets, but that you're very confident in the second half for AdTheorent returning to a year-on-year growth. What gives you that confidence? Yeah. Thanks, John. We're seeing a lot of demand and, and adoption levels for our highly differentiated machine learning products, which positions us for a return to the sustainable growth. On a year-over-year basis, at the end of the second quarter, our second half booked revenue is 7.5% higher, and our second half pipeline is 36% higher than a year ago. Of that, a materially higher percentage is at the contracting stage, especially so within our health vertical, giving us greater visibility and confidence. Much of the second half momentum is driven by the strong demand across our health vertical, CTV, AdTheorent audience products, and from self-service customer adoption. Our patient, deliberate, and innovation-first approach to the immense market opportunity is working, and the results will reflect this as we move into the second half. We are confident we can capture a growing share of the programmatic ad budgets. We deliver consistently superior campaign performance, cutting-edge machine learning and data products, and verticalized solutions, and we're leading the industry in data flexibility and transparency, ID independence, and pricing transparency. Patrick, that's a great uptick in the 2nd half for your booked revenue pipeline. Now, from what you've said, it sounds like demand, not only for AdTheorent's approach, is driving this, also your key pillars. Maybe if you could unpack this a little bit for us so we can understand it better. Maybe we start with your self-service platform. I know the growth in the 2nd quarter was notable. Can you talk about self-service growth? Yeah, yeah. We continue to see enthusiastic early adoption in our self-service platform from, from media buyers who want the industry's best programmatic brain on a self-service basis. Overall, Q2 was our most active quarter to date for self-service. On a sequential basis, we saw impressions up 92%, revenue was up 75%, and our advertiser count was up 49%. Self-service CTV revenue also continued to grow with 97% sequential growth from the first quarter. Retention is strong, pipeline continues to grow, customer satisfaction is high, and we are confident momentum will continue. We are winning back prior managed service customers who loved AdTheorent's performance but needed a self-service solution. Now, we offer that self-service option and the industry's best performance, which is gaining us new opportunities at an exciting pace. customers are choosing us because we can drive cost efficiencies and superior KPI outcomes. Our performance models do not rely on expensive third-party audiences, and as a result, our platform can put more media to work for advertisers. Great. Thanks, Patrick. Jim, can you give, give me an idea of why there is so much enthusiasm for self-service for, for AdTheorent? Yes. As Patrick mentioned, our self-service offering makes the AdTheorent platform available for self-service users directly, meaning programmatic media buyers who have the experience and knowledge to execute campaigns themselves. Our self-service model is exciting to customers for a number of reasons. First, our platform's advanced targeting capabilities, all premised on machine learning, as I mentioned, drive better performance for advertisers. The ROI advertisers get from our platform is higher. The cost per sale or other desired action is more efficient, meaning advertisers get more value for their advertising investment. This is due to the many platform components we have built, which are focused on identifying impressions which will drive conversions and avoiding impressions which are wasteful. Also, our products are highly differentiated. For example, our Predictive Audiences and Health Audiences, these are highly differentiated methods to target audiences without using IDs and without user profiling, and these methods work well and drive ROI for advertisers. Another reason is our pricing transparency. There is no hidden delta, as it's been called, when advertisers work with us. All fees are fully disclosed, and more value is provided to the end advertiser. Thanks, Jim. Now, you mentioned that there's been significant interest in the adoption of Predictive Audiences, the product there. Maybe you can refresh our memory on what that is, and how does that solution really work? Sure. The industry has been overdue for the transformational change we have brought to the practice of building targetable digital audiences with our new cutting-edge audience builder tools, which we refer to as ABi and HABi. Advertisers can use ABi with their own first-party data and/or AdTheorent platform data to create customized ID-independent audiences that are powered by AdTheorent's audience quality algorithms. Competing platforms target ads by activating cookie ID lists or other user ID lists, often with catchy names like Moms or Sports Enthusiasts. The origins of these ID lists are often not known or shared, and their effectiveness is limited. We have invented a better tool to drive actual data-driven audience quality. ABi combines everything advertisers already love about AdTheorent, with the ability to use primary source data signals to define their target audience. For example, in-market auto shoppers likely to purchase a car in the next three months. It uses those parameters to limit campaign delivery to that desired audience alone, and then further optimizes ad delivery within this audience only based on the statistical likelihood of achieving a campaign-specific KPI, such as purchasing a product, in this case, a car. This is a giant step forward from the black box ID lists used by other programmatic platforms. It also reduces third-party audience fees, providing incremental margin for AdTheorent or AdTheorent platform users, while helping us redefine the market. In the second quarter, I'm also pleased to report that we received valuable third-party validation for our AdTheorent Predictive Audience products. Neutronian's NQI Data Quality Certification, which is based on our superior capabilities in areas including consent and compliance, data sourcing, transparency, and performance. This certification from Neutronian provides independent data quality verification, easing media buyers' data vetting burden, and distinguishing AdTheorent as a high-quality provider in the industry. Also notable is that AdTheorent also earned the top ranking among pure-play DSPs in Neutronian's Q2 Data Privacy Scores report, strengthening our position as a machine learning-focused industry leader. All right, thanks, Jim. Patrick, can you give us an idea of the growth of adoption that you've seen with Predictive Audiences? Yeah. Yeah. As Jim mentioned, our algorithm-based and ID-independent Predictive Audiences, built by our Audience Builder, ABi, continued to yield strong customer adoption. We had 50 active campaigns in the second quarter and 37 campaigns already booked to date for the third quarter. Customer adoption remains strong, and we are driving excellent performance for these customers running AdTheorent Predictive Audiences. For example, in a number of head-to-head tests, AdTheorent Predictive Audiences outperformed third-party audiences across a variety of verticals, increasing our data targeting revenue in each and driving excellent results for advertisers. We had 55% more efficient CPA for an auto brand campaign, a 244 increase in engagement rate for a CPG brand, a 21% increase in a video completion rate for a travel destination, and a 363% increase in click rate, click-through rate for a state department of health campaign. Great. That's pretty good stuff, Patrick. If we switch gears, I want to talk about AdTheorent Health. I know, you know, it's a particularly important vertical health for you guys. Jim, maybe you can give us an update on AdTheorent Health. Yes, we continue to see strong progress in AdTheorent Health, which includes customers across pharma, healthcare, retail pharmacies, OTC, outpatient care, continued healthcare education, and healthcare recruiting. Health is an important beachhead for AdTheorent. We have strong competitive moat there since generalist DSP peers lack our custom health solutions and our ability to drive advertiser value while complying with stringent privacy laws and industry best practices. These advantages, our ability to drive KPI outcomes health advertisers care about, are driving rapid customer adoption. In the second quarter, we had 19 campaigns leveraging Health Audiences built by HABi, and 25 are already booked to run in Q3. For example, one health customer built and deployed an AdTheorent Health audience to reach patients suffering from a mental health condition. This campaign, advertising a prescription drug, outperformed the client benchmark across all metrics, achieving a 40% more efficient cost per diagnosis, 62% more efficient cost per qualified visit, and 33% more efficient cost per treatment. In addition, health campaigns typically run for a year, increasing the predictability of our revenue stream. Looking ahead, we continue to innovate, including our exciting self-service DSP for health. This highly specialized offering, which puts HABi and other health-specific advertising tools in the hands of self-service users, remains on track to launch in Q3. This innovative market advancement, premised on the immense power of machine learning, will give us an even greater opportunity to win market share within the $18 billion health advertising opportunity, and we are confident this momentum will accelerate. Great. That's a good update. I know another key growth area for you guys has been CTV. How is CTV adoption coming? I'll take this one. Yeah, John, we're seeing great momentum with CTV. We continue to ramp our specialized performance CTV business across our platform. Our offering wins because we offer a unique product that delivers superior return on ad spend, advanced attribution, strict privacy protections, and seamless omni-channel coordination. No other programmatic platform offers better outcome-based CTV capabilities. During this quarter, this was particularly impactful to our self-service platform, where we saw CTV revenue increase 97% versus the first quarter. We have also won a number of new and important deals because of our live addressable TV product. We launched that in late May, and this allows buyers to target live premium inventory across online cable apps. Our machine learning-based models for targeting, pricing, and optimization facilitate smarter media buying, and our real-world measurement proves effectiveness and ROI. Great. Thanks, Patrick. While I have you both here, maybe we could talk about some of the industry 10 trends and the key topics. I really want you to give our viewers a sense of, you know, how, how AdTheorent fits in, because I think that's, that's a key element of your story. Let's start with AI. Seems like everybody's doing AI. How is AdTheorent different? Yeah, John, in light of the attention being paid to generative AI tools, it is important to address how we are unique. Unlike some companies scrambling to bolt on AI products or layer an AI veneer on top of less innovative offerings, AdTheorent has an 11-year head start developing and consistently enhancing a purpose-built machine learning platform, with the singular focus of maximizing the performance impact of every advertising dollar deployed by our customers. Of the billions of ad impressions available for purchase in any given microsecond, our ML tools find the ones that drive sales, customer visits, form fills, prescription lift, lifetime value, or whatever business goal or KPI our customers care about. While we believe that broad, generic, white-labeled AI tools have their place, they can't compete with a proprietary, customized product with ML at its foundation. In addition, the performance of statistics-based ML models will only be as good as the data feeding the decisioning engine. With our ML-based approach to scoring and optimizing ad impressions, we've invested heavily in curating, augmenting, and normalizing the programmatic signals used by our algorithms. In addition, it's challenging to assemble high-quality, actionable data without relying on third-party ID lists or cookies. No other DSP can match the combination of privacy and performance embedded in our DNA at AdTheorent from the very beginning. While the current enthusiasm around AI brings a lot of noise into the market, we believe it provides a unique opportunity for us to demonstrate our unparalleled value to our brand and agency partners. In one example recently, regarding a campaign for an international airline partner, our predictive targeting drove the most efficient cost per action for online travel bookings and the best return on ad spend across 17 campaign partners, including a 42% more efficient CPA and a 61% higher return on ad spend, as compared to a very large, diversified technology company. Results like these help us expand our share of wallet with extremely large advertisers. Interesting. Thanks for that. Let's talk about cookies for a minute. It seems like the industry's been talking about, we're gonna get rid of them, we're no, no, no. You know, what's going on with cookies? Maybe you can give us an update. Sure. The industry is finally waking up to the reality of a post-cookie world and what that means. Google has confirmed that cookies will be deprecated from the Chrome browser starting in the first quarter of 2024 and completely retired by the end of the year. Despite this, many companies continue to rely on cookie-based solutions or consider ID-based replacement solutions, which have universally low customer adoption and are present in only a small fraction of programmatic bid requests. Meanwhile, we at AdTheorent continue to perfect the solution, which replaces IDs with the power of machine learning-based statistical scoring, shining a needed bright light of value, transparency, and privacy advancement into programmatic media buying. Building on our privacy first and ML-focused approach to digital advertising, we are engaged with the Chrome Privacy Sandbox initiatives to support the phasing out of third-party cookies. In short, through these API-focused initiatives, Google will make available to advertisers certain aggregated data which advertisers can use for pacing, optimization, and reporting. These data signals will connect easily and naturally to AdTheorent's existing data pipes, as we currently have approximately 1,000 data attributes available for our ML models. As the industry transitions to a post-cookie era, AdTheorent will emerge as a front runner, embracing ID independence and the power and value of ML-based media buying decisioning focused on alternative data signals such as contextual content, natural language processing, and behavioral patterns. Great. Thanks so much for addressing the AI and also talking about a cookie-less future. Maybe you could let us know a little bit more about what you think about your future. Where, where is AdTheorent headed, and what are you excited about? Thanks, John. I've, I've never been more excited about our business than I am now. We're seeing continued strength in areas of investment, such as self-service, our audience builder products, health verticalization, and CTV. As always, we're making steady and significant progress in our efforts to improve platform-based return on ad spend for customers, which in the end drives the adoption of the AdTheorent DSP and revenue growth. I'm very excited that in the third quarter, we're going to bring the best health-focused audience DSP to market for self-service users. We believe that it will be a huge part of our growth, and we believe that as the pharmaceutical companies review their options for 2024, we'll be very well positioned to capture a large share of those budgets. We are committed to investing in our platform and creating expanded, performance-driven, verticalized solutions to support our long-term growth. AdTheorent has remained consistently profitable and generated positive cash flow, enabling us to strategically invest in growth opportunities to enhance shareholder value in 2023 and beyond. Great. Well, I think we'll leave it there today. Thanks to you, both of you, Patrick and Jim, for spending time with us. I appreciate the time. To learn more about AdTheorent, you can visit our website at www.watertower.com. Thank everyone for joining us. Did want to mention that the views expressed in this fireside chat may not necessarily reflect the views of Water Tower Research LLC, and are provided for informational purposes only. This fireside chat may not be distributed or reproduced without the written consent of Water Tower Research and should not be considered research, nor a recommendation. WTR is an investor relations firm, not a licensed broker, broker-dealer, market maker, investment bank, underwriter, or investment advisor. Additional disclaimers can be found at watertowerresearch.com. Have a good day. Thank you.