I would like to share a few notable data points. 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. 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 Q2, we saw a 75% sequential revenue growth, an acceleration from 19% sequential revenue growth in Q1. Predictive audiences and health audiences are driving adoption. During the quarter, 19 campaigns leveraged health audiences, 50 additional campaigns utilized predictive audiences in verticals besides health.

Looking to Q3 and the second half of the year. Our highly-differentiated machine learning solutions are driving increased demand and adoption levels, positioning us for a return to sustainable growth. On a year-over-year basis, as of the end of July, second half booked revenue is 7.5% higher, second half pipeline is 36% higher. And 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 this second half momentum is driven by strong demand across our health vertical; CTV, AdTheorent Audience products and self-service customer adoption and growth. Our patient delivered an 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 programmatic ad budgets by delivering consistently superior campaign performance, deploying cutting-edge machine learning and data products and verticalized solutions and leading the industry in data flexibility and transparency, ID independence and pricing transparency. Along those lines, we continue to prioritize investments in high ROI opportunities across several newer and growing revenue streams, our self-service platform, our AdTheorent Health offering, our predictive or algorithm-based audience offerings and CTV. These focused investments are working. I’ll make quick comments about each before moving on to some emerging industry themes that further validate how we are approaching the market.

On our self-service platform, we continue to see enthusiastic early adoption from media buyers, who want to use 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, impressions were up 92%. Revenue was up 75% and advertiser count was up 49%. Retention is strong, pipeline continues to grow, customer satisfaction is high, and we are confident, momentum will continue. We are even winning back prior customers who love the AdTheorent’s performance but needed a self-service solution. Now, we offer a self-service option and the industry’s best performance, which is gaining us new opportunities at an exciting pace. We continue to see strong progress in AdTheorent Health, which includes customers across pharma, health care, retail pharmacies, OTC, outpatient care, continued health care education, and health care recruiting.

Health is an important beachhead for AdTheorent, and we have a strong competitive moat 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, and our ability to drive KPI outcomes health advertisers care about, are driving rapid customer adoption. In Q2, we had 19 campaigns leveraging health audiences 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, 63% more efficient cost per qualified visit and 33% more efficient cost per treatment.

In addition, health campaigns typically run for one 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. We are confident, this momentum will accelerate. Turning to AdTheorent Predictive Audiences. We are pleased with momentum across other verticals, where like Health, our primary sourced ID independent data and transparent and efficient workflow for audience creation and activation sets us apart from other media buying platforms.

Customer adoption of our algorithmic audiences remains strong, and we are driving excellent performance. For example, in a number of recent 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, including a 55% more efficient CPA for an auto brand campaign, a 244% increase in engagement rate for a CPG brand, a 21% increase in video completion rate for a travel destination, and a 363% increase in click-through rate for a state Department of Health campaign. Additionally, we received valuable third-party validation for our new AdTheorent Predictive Audience products, Neutronian’s NQI data quality certification.

Based on our superior capabilities in areas including consent and compliance, data sourcing transparency and performance. This certification provides independent data quality verification, easing media buyers’ data vetting burden and distinguishing us as a high-quality provider in the industry. In addition, AdTheorent also earned the top ranking among pure-play DSPs in Neutronian’s Q2 Data Privacy Scores report, further strengthening our position as a machine-learning focused industry leader. Finally, we continue to ramp our specialized performance CTV business across our platform. Our CTV offering wins because we offer a unique product that delivers superior return on ad spend, advanced attribution, strict privacy protections and seamless omnichannel coordination.

No other programmatic platform offers better outcomes-based CTV capabilities. During the quarter, this was particularly impactful to our self-service platform, where we saw CTV revenue increase 97% versus the first quarter of 2023. We’ve also won a number of new and important deals because of our live addressable TV product, which launched in late May and allows buyers to target live premium inventory across online cable apps. Our ML-based models for targeting, pricing and optimization facilitate smarter media buying and our real-world measurement proves effectiveness in ROI. Throughout all of these investment areas, innovation remains at the core of our strategy. Looking to Q3, we are expanding our contextual signals and natural language processing capabilities by deploying AdTheorent themes into our models, which will revolutionize the way we categorize web content.

AdTheorent themes use language models instead of human-defined categories to sort web pages based on their actual content, making classification more unbiased, effective and efficient. This groundbreaking addition to our platform further enhances our market-leading AI features and optimizes content delivery based on topical relevance in all of our CPA models, improving performance without relying on IDs. Now I’d like to talk about a few industry trends and dynamics that we believe validate our work as a pioneer in advanced machine learning. The first theme relates to programmatic waste. A recent study by the Association of National Advertisers that examined transparency in the programmatic media supply chain provides useful practical context for the specific value AdTheorent solutions provide, which others in the industry lack.

According to the ANA report, 23% of the $88 billion spent globally on the open web programmatic advertising is lost due to waste in the supply chain. AdTheorent’s platform uniquely address these challenges cited by the ANA report by applying advanced machine learning techniques in a flexible and transparent manner, driving exceptional real life business outcomes for our customers, while delivering price efficiency almost double that of peers in controlled head-to-head tests. We do this in a few ways. First, we tackle the data deficit advertiser space by leveraging our ML approach to curate and augment programmatic signals, providing rich data other DSPs cannot. Put another way, using ML, our media buying is enhanced by our superior knowledge and insights about available publisher supply.

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Second, we avoid low-value risky ad placements that drive meaningless clicks by adhering to ANA recommendations, running campaigns on an approved list of high-quality sites, and using highly advanced real-time anti-fraud techniques. Finally, our core platform thesis and data approach prioritizes delivering superior return on ad spend, measured by business outcomes such as new sales or store visits by evaluating millions of impressions per second, bidding only on those that drive favorable results, and maximizing cost efficiencies through our advanced cost optimizers. Second, 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 the broad generic white label to AI tools have their place, they can’t compete with a proprietary customized product with ML at its foundation. Additionally, 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 have invested heavily in curating, augmenting, and normalizing the programmatic signals used by our algorithms. In addition, it is challenging to assemble high-quality actionable data without relying on third-party IDs or cookies.

No other DSP can match the combination of privacy and performance embedded in our DNA from the very beginning. So, 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. And one recent example, 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.

Finally, the industry is 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 Q1 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 continue to perfect the solution, which replaces IDs with the power of ML-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. So, in conclusion, we are happy with our progress in Q2 and continued strength in areas of investment, such as self-service, our healthcare vertical, our predictive audience offerings and CTV.

And as always, we’re making steady and significant progress in our efforts to improve platform-based return on ad spend for customers, which is what drives adoption of AdTheorent’s DSP and revenue growth. Since 2012, we have used ML to solve real-world problems that advertisers care about. It is not marketing spin. It is core to everything we have built over the last 11 years and to what we continue to build. That work is accelerating, and more and more advertisers are taking notice. We are confident in our ability to continue delivering exceptional results for our customers, returning to growth in the second half, and driving long-term value for our investors. Thank you for your support and confidence in the AdTheorent team. Now, I will turn it over to Patrick.

Patrick Elliott: Thanks, Jim, and good afternoon, everyone. We are pleased to deliver Q2 results largely in line with expectations set during our prior call. The quarter’s adjusted EBITDA surpassed our outlook, and we are confident in achieving our full year goals for 2023. In the second quarter, our revenue was $37.6 million, a decrease of $4.9 million or 11.5% compared to the second quarter of the previous year. As expected, when we provided our outlook on the last call, this decline was largely a result of the ongoing macroeconomic pressures that have impacted budgets and led to uncertainties in advertising campaign timing and size over the past 12 months. Additionally, we saw lower than expected budgets in the quarter from a small number of retail and healthcare customers and delays in the timing of certain campaigns, driving revenue $1 million below our expectations.

Despite this slower pace of spend, the number of health advertisers increased during the quarter. And as we enter Q3, we are in an exceptionally strong position overall. As of the current point in the quarter, our bookings for the second half exceed the second half of 2022, and we have a growing pipeline with more advanced and committed opportunities. More on this later. During Q2, the demand for our self-service offering remained exceptionally high. We delivered substantial growth in self-service revenue, which increased by 75% sequentially in Q2 compared to 19% sequentially in Q1. Additionally, there was 92% growth in impressions served and a 49% increase in advertiser count from Q1 to Q2. CTV revenue also continued to grow, particularly within our self-service platform.

As Jim mentioned, self-service CTV revenue experienced 97% sequential growth from the first quarter. These results demonstrate the strong performance and positive trends in our self-service and CTV offerings, as both offerings continue to become a higher percent of our overall revenue mix. Turning now to expenses. In the second quarter, our adjusted gross profit calculated as GAAP revenue less traffic acquisition costs, was $24 million or 64% of revenue, which aligns with our projected outlook and consistent with Q1 results. This percentage is lower compared to the same period in the previous year, where it was 66.7% of revenue. The decrease in AGP margin can be attributed to two factors. First, we offered introductory services at competitive pricing to encourage adoption among first-time customers.

Second, there was a change in the mix of services across device types, particularly in CTV, which carries premium media inventory costs. Total GAAP operating expenses were $38.3 million in the second quarter, down $2.9 million or 7% from Q2 2022. The reduction in operating expenses was driven by lower equity-based compensation, traffic acquisition costs and insurance premiums, offset by increases in data infrastructure, hosting and travel. Stock compensation expense in the second quarter was $1.9 million, showing a decrease of $2 million or 52% compared to the $3.9 million recorded in Q2 2022. Adjusted EBITDA for the quarter was $3.3 million, down $4 million compared to the second quarter of 2022, primarily due to the declines in year-over-year revenue and AGP offset by lower operating expenses.

Consistent with our track record of cost discipline and commitment to prioritizing profitability, we, once again, exceeded our quarterly EBITDA outlook. Moving to cash flow, we used $2.3 million of free cash flow in the quarter compared to a use of $300,000 in Q2 of last year. Year-to-date, we have generated $600,000 in free cash flow versus $1.8 million for the first six months in the last year. Consistent with Q1, we had an increase in capitalized software costs associated with our product and platform initiatives. Capitalized software development costs have increased $1.2 million year-to-date. We exited Q2 with a strong cash and liquidity position. At the end of the second quarter, we had $73.1 million in cash versus $72.6 million at the end of 2022.

We have no debt on the balance sheet, but continue to have access to $40 million on a revolving credit facility. Regarding our outlook for the full year 2023, we are reaffirming the previously provided projections for revenue, AGP, and adjusted EBITDA. For the full year, we continue to expect revenue to grow year-over-year, adjusted gross profit to be between 64% and 65% of revenue and adjusted EBITDA to be within 16% and 19% of adjusted gross profit. We anticipate revenue growth in the second half of the year, driven by strong demand for our new products across various verticals. The progress in our key investment areas, including AdTheorent Health and Audience Builder products and CTV and self-service offerings are driving improved visibility and outlook for the second half of the year.

Our forecast assumes no significant changes in the macroeconomic environment, and we continue to expect the quarterly seasonal revenue composition to look more like 2021 than 2022. And although Q2 revenue was below our internal expectations by approximately $1 million, we are encouraged by the positive trends in bookings and our pipeline opportunities. At this point in the year, our pace for bookings in the second half exceeds the same time last year, up nearly 8% year-over-year, and our pipeline shows strong double-digit growth with more opportunities in advanced stages. These indicators support our confidence in achieving our full year outlook. For Q3, we expect revenue to be between $39 million and $42 million, representing 8% growth at the midpoint compared to Q3 2022.

The adjusted gross profit for Q3 is expected to be consistent with the first half of 2023 at around 64% of revenue. We anticipate adjusted EBITDA to be between $3 million and $4.5 million for the third quarter. In summary, we are encouraged by the many growth opportunities that lie ahead for AdTheorent. Across our key growth pillars, we see enthusiasm from brands and agencies and the sales pipeline has never been better. The business continues to track towards our longer-term goals, and we remain confident in our ability to achieve our full year outlook. At this time, we would like to transition to the Q&A session moderated by the operator.

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