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AdTheorent CEO James Lawson on Going Public, Future of Adtech

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·10-min read
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By Jarrett Banks

Advertising-technology company AdTheorent Inc. plans to merge with SPAC MCAP Acquisition Corp. (Nasdaq: MACQ). The company uses machine learning and data science to optimize advertising and marketing campaigns for its customers.

IPO Edge sat down with CEO James Lawson to find out more about going public and the future of adtech. 

IPO Edge: We’ve seen a number of adtech companies enter public markets in recent months. How are you different from others in the space?

Within the programmatic ecosystem, AdTheorent is a Demand Side Platform, or DSP – but we’ve reimagined what that means.

We are fundamentally different because we have pioneered a new method to target digital ads in a programmatic marketplace without relying on the primary methods of the past: cookies and licensed audience segments. Our new method – Predictive Advertising – drives industry-leading campaign performance without relying on user-specific profiles and individualized data. In place of legacy targeting methods, AdTheorent’s Predictive Advertising platform leverages award-winning data science and machine learning (ML) capabilities to deliver advertiser-specific business outcomes for our advertisers.

Our brand and agency customers today not only want, but require, measurable business outcomes from their ad spend. That’s AdTheorent’s specialty. If a brand’s KPI is an online insurance quote application, for example, our platform and ML models will identify data attributes present most often when there is a conversion event. Then, our bidders automatically optimize toward those attributes to drive KPI performance, and our models learn and refine optimizations over time as more conversions occur. These attributes may include things like device type, operating system, one or more keywords in the URL, keywords in the page content, geographic data, time, or approximately 200 other data attributes that are available to inform our machine learning models. Using historical conversion data, we can determine the likelihood that each specific bid request will drive the online or real-world actions our clients desire. We model towards and deliver advanced conversions, not just clicks, and our ability to do so continually improves as our machine learning platform makes automated optimizations which make our ad targeting even more efficient. And this ability really sets us apart from our peer group.

On top of this revolutionary platform and approach, AdTheorent’s proprietary suite of tools, methodologies and vertical solutions maximize performance and ROI for advertisers while operating in a privacy-first manner, which has become an essential element for brand marketers. AdTheorent’s platform is more effective and privacy-forward than other AdTech companies. This combination of consistent performance and more reliable business outcomes is what keeps our customers coming back and entrusting us with more of their business over time.

IPO Edge: Why are you going public now, and how will it benefit the business?

There has never been more demand for our capabilities and unique offerings, and now is a good time for us to accelerate the scale of our operation. We spent the past few years investing heavily in AdTheorent’s technology, accelerating organic growth and increasing efficiency. From a financial perspective, we are operating in excess of the ‘Rule of 50,’ with Revenue Less TAC growth and adjusted EBITDA margin each expected to be around 30% annually between 2020 and 2023. The market continues to move toward AdTheorent, which is validating for our business model and makes us excited about the opportunities ahead.

Collectively with our investors, we believe AdTheorent’s unique positioning can drive outsized growth in the $90 billion market for US programmatic digital media spend, projected to grow 17.6% per annum through 2024. The public company structure and proceeds provided by the transaction will allow AdTheorent to optimize growth by increasing investment behind multiple growth vectors, both organic and inorganic.

IPO Edge: You are going public through a SPAC merger with MCAP but your record of financial performance seems to set you apart from most SPACs, can you tell us about your thought process there?

It is true, we are not a typical SPAC target given our historical strong financial performance. We expect great things from ourselves in the future, of course, but we come to the table with a track record of past financial performance that should be exciting and assuring for MCAP shareholders, and we think this makes us very unique among SPAC targets. We had lot of strategic options for this next chapter but ultimately decided to continue our solid partnership with Monroe given our history with them (as our lender) and their track record of success with other SPACs. We believe we will perform very well as a public company given our disciplined approach to running a profitable and growing business.

IPO Edge: AdTheorent recently announced Q2 2021 business results, which showed continued growth in revenue. Can you give us insight into these results and the business drivers for them?

We are very pleased with our Q2 2021 financial performance, which outpaced our expectations, growing revenue by 89% to $39.9 million compared to $21.1 million in the second quarter of 2020. This growth demonstrates the power of AdTheorent’s technology and solutions and our ability to deliver strong ROI for our advertiser clients. Brand marketers understand the value we provide to them and we have never been more confident about our ability to drive long-term durable growth.

As a result, we raised our outlook for full-year 2021 and now expect revenue of at least $161.6 million, compared to our prior outlook for 2021 revenue of $157.7 million and expect full-year 2021 Revenue Less TAC* of at least $106.2 million, compared to our prior outlook for 2021 Revenue Less TAC of $102.4 million.Revenue Less TAC is a non-GAAP measure that adjusts for costs incurred to execute customer campaigns: advertising inventory, third party inventory validation and measurement, and data – which is collectively referred to as “traffic acquisition costs” or “TAC”.

IPO Edge: Based on your experience thus far throughout 2021 and the nature of the digital market, what are the best opportunities to expand your business for the rest of this year, and into 2022?

According to the Winterberry Group, digital media spending will exceed $171 billion in the US in 2021 and is poised for exceptional growth, driven in large part by programmatic advertising. As I mentioned earlier, programmatic digital spending in the US is a $90 billion Total Addressable Market in 2021, forecasted to grow at a 17.6% CAGR to $141 billion by 2024.

Since 2012, AdTheorent has pioneered a new way to target digital ads programmatically without relying on user-specific personal profiles and individualized data. We have a history of operating efficiently, with consistent margin expansion the last four years, tracking toward 30% revenue growth and 30% adjusted EBITDA margins in 2021.

We see a number of meaningful organic opportunities, including increased revenue in Connected TV, or CTV, continued vertical growth and expansion, and we will look into international expansion given our privacy-forward approach to ad-targeting. We will also look to opportunistically invest in M&A to accelerate these opportunities.

CTV, in particular, is a major growth opportunity for AdTheorent. Streaming services like Hulu are the fastest growing sector as traditional TV dollars shift to digital. AdTheorent applies machine learning to CTV to drive performance-based outcomes based on our advanced, proprietary analytics capabilities. With limited investment, our 2021 CTV revenues are anticipated to be $40 million, representing approximately 300% growth year-over-year, and with additional investment, we believe we can continue to materially outpace expected annual industry growth of 18%.

With respect to vertical growth, we believe it is important to continue to invest in solutions which solve our customers’ unique campaign challenges. That means coming up with new and better ways to attain their campaign KPIs, sensitive to data limitations and rules in various regulated industries. We have a list of innovations and new offerings that we are excited to explore across a number of different verticals, and this investment capital will help us accelerate our plans.  

IPO Edge: At the moment, cookies are the biggest trend in the digital advertising industry. Google has declared its intention to doing away with cookies, and Apple is restricting the use of device IDs for advertising. How do you believe this will impact the industry, and what will happen to the existing digital ad market, which is almost entirely compromised of cookie-based and ID-based ads? And how does AdTheorent benefit?

Google recently announced that by 2023 third-party cookies will not be used within its Chrome browser, following Apple’s work to phase out the use of third-party cookies from the Safari browser. Google has delayed this transition for a number of reasons, including the chaos that would likely ensue if the cord were pulled too quickly. Without the proper groundwork in place, publishers could be forced to enact paywalls on their content across the internet, which would alienate consumers.

While the industry scrambles to figure out a replacement for third-party cookies and competitors in the adtech space are distracted by the coming transition, we will continue to improve our algorithms and Predictive Targeting methods using machine learning. We will continue to win with customers because we deliver superior ROIs and measurable results on the business actions that matter most to them.

Unlike our competitors, AdTheorent is already prepared for a cookie-less future, whether it comes tomorrow or years in the future. As stated previously, AdTheorent’s advantage is that our ad-targeting approach does not require us to know anything personally identifiable or sensitive about the user, including the user’s name, interests or website activity. We simply look at a moment in time – when a person accesses a piece of digital content – and we optimize media buying decisions based on the statistical likelihood of a given ad impression converting on a given customer KPI. The bid requests ingested by our platform include a number of different values and data points, including device type, operating system, one or more keywords in the URL, keywords in the page content, geographic data, time, or approximately 200 other data attributes that are available to inform our machine learning models.

From there, there are microseconds in which AdTheorent and other DSPs are deciding whether to bid on that digital real estate. Our platform essentially says: “The bid request has these data elements present. What do our models tell us? Is this going to be valuable for a brand trying to sell sneakers online?” Our models are there to tell us that and make the best decision in an instant. Our platform evaluates more than one million impressions per second and we bid on less than 0.1% of those impressions. This is the magic of AdTheorent and why we are able to consistently drive high ROIs for our customers. This keeps our customers coming back and spending more with us over time.

IPO Edge: What do you see as the next big thing in the digital advertising industry?

Since 2012 the AdTheorent team has been working on the shared vision of ML-powered programmatic advertising. We’re not the product of acquisitions, tuck-ins or bolt-ons. We created AdTheorent from the ground up, we have a gifted CTO who is an ad tech pioneer and who has been here with his core team from day 1, and we will continue to rapidly innovate in the space and deliver the best results for our customers. This is the key going forward, as the the digital advertising industry will continue to grow and adapt, based on consumer behaviors and preferences. I believe there will be an evolution of AdTech towards machine learning-powered advertising, and AdTheorent is at the forefront of this shift.

At its core, data science and machine learning are easier to practice in rhetorical form, as many companies do on websites and in marketing collateral. In practice, it is quite difficult to operationalize efficiently. Using data science and ML to target ads in microseconds is hard, especially when you consider the advanced KPIs our customers expect us to drive for them. It has taken AdTheorent a significant amount of time to build and refine our platform and solutions, and we have a great team of data scientists and engineers and product professionals who have helped us get here. We feel this has made for a deep, wide moat when compared to others in the space.

 

Contact:

Jarrett Banks, Editor-at-Large.

jb@capmarketsmedia.com

Twitter: @IPOEdge

Instagram: @IPOEdge

 

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