Adam Foroughi, Applovin CEO: Surviving a 92% Drawdown, Ads as ML 1.0 & the $50B Game Ad Market
All-In with Chamath, Jason, Sacks & Friedberg
Adam Foroughi, CEO of AppLovin, discusses the company's evolution from a massive IPO valuation to a significant market cap drawdown and its
Key takeaways
- AppLovin's market cap experienced a massive volatility swing, dropping from a peak of $40 billion to approximately $3.8 billion in 2022.
- The company executed an aggressive buyback program, spending roughly $6 billion to retire 20% to 25% of shares outstanding.
Main topics
- Mobile gaming advertising market
- IPO volatility and stock buybacks
Notable quotes
Advertising is like ML 1.0.
Conclusion
The episode offers a profound look at how a high-growth tech company c
Transcript preview
Speaker 3 (0:00) Adam is probably the best founder no Speaker 2 (0:02) one's ever heard of. There's an ad platform hiding Speaker 3 (0:05) inside 100,000 mobile games and Speaker 2 (0:07) is quietly outperforming Facebook ads for e-commerce brands. Of all those thousand plus IPOs, the number one most valuable is Applovin. Applovin Speaker 3 (0:16) CEO, Adam Perugy. The Speaker 1 (0:18) founder mentality has got to be chase winning. They're going to print something like $6 billion in cash this year. In a world where things don't make sense, people think you're cheating. instead of realizing you built one of the cooler technologies the world's ever seen. Speaker 3 (0:30) Please welcome Adam Farooqi. Speaker 3 (0:43) Welcome, Adam. Speaker 4 (0:45) Hey, man. Hey, man. How you doing, bro? Good to see Speaker 2 (0:47) you. Speaker 4 (0:47) Likewise. Speaker 2 (0:48) Adam, thanks for being here. We thought it'd be really great to chat because a lot of people don't talk as much about, you're not in the headlines all the time with your business. You're operating your business almost like absent media. You don't do a lot of press. You don't get out there a lot talking about the company, but it's such an incredible business. Can you just tell the audience kind of what AppLovin' is and maybe also frame up the market a little bit for us? Speaker 1 (1:11) Yeah, totally. I think the fact that we were able to build a very big company without having VC funding at the early stage created this world where we just had to build quietly. And then obviously the goofy name didn't help us all that much as well. But what we are ultimately is an advertising company that's helping mobile game developers monetize that space. Now, what people don't realize is just how big the mobile gaming universe has become. You've got over a billion people a day playing mobile casual games. These are all adults, heads of households, and the scale of the opportunity is just humongous. We disclosed last January, so nearly two years ago, that on our own platform, there was $11 billion a year of ad spend. Since then, we've grown 60 % year over year, roughly. And so if you gross that up to a nice round number today, you get $20 billion. Now, we're not the only player in this marketplace. This is a market that's monetized by a lot of other ad companies as well. So then you'd probably more than double that again and round it off and say there's probably about $50 billion of advertising being spent every single year in this mobile gaming ecosystem. It was not very long ago that social was a $50 billion opportunity. Space is growing really quickly. A lot of audience. These people watch ads. A lot of times they watch the ads to get rewards. And so that dynamic creates this possibility to create intent. For most of the company's life, we've been creating that intent to drive a user to take one game's experience and go to the next game's experience. And what's really gotten investors excited about our company and just us excited about the opportunity that we have in front of us is that deep learning models have gotten so powerful now that you could take that same space and try to take that adult and give them a shopper behavior experience. Speaker 1 (2:59) allows us to tap into much larger economies, make more of an economic impact in the world. And that's why our team's just really, really pumped up on what we're doing. Speaker 4 (3:07) The first wave of internet advertising was in many ways the spark for a lot of critical technologies that then sort of diffused out into the world. So like, if you think what Google was able to do with AdWords, AdSense, Applied Semantics, all of that whole range of technology, is that true in this generation of internet advertising? Are there Are there technologies and things that are being birthed here that are consequential and foundational now to the rest of the internet? Speaker 1 (3:34) Yeah, I mean, advertising is like ML 1.0, but really was the first implementation of all these technologies that now are driving AI today. And the economic value of a large language model and what it's doing in our society today is much greater than advertising. But advertising is a very profitable implementation of a deep learning model. Now, recommendation systems are structured differently than large language models, but in a lot of ways they follow the same trajectory. So a lot of the research that's being done in the space, in the large language model space, can port to recommendation systems, and vice versa, a lot of the researchers in the large language model space might have started early in their careers looking at advertising systems. So these two spaces are really related. The nice thing about our business and any advertising business, is that when you build a model, you're predicting a future outcome, an advertisement, or if you're building a social network, an engagement post, or a sequence of them. But you can translate the value of that prediction immediately. Speaker 4 (4:33) Is it true that there's just a broad-based behavior around humans' reaction to ads in 2026 versus 2006? Like, has there been an evolutionary arc that's very predictive? Speaker 1 (4:46) Yeah, it's interesting. I started my career in 2005, so I saw the ads back then. Complete garbage. It was all spam and the technologies just weren't powerful enough and your old company Facebook did a really good job of realizing if you can take all the data we have in front of us and Pair it with good technology the ads can become really relevant And if you talk to most people who shop today most of their shopping recommendations are coming from Instagram The ads have become very much like content and in our domain as well people love the ads that we show And you would think people wouldn't like them, but we see tons of engagement on little mini games that are appearing in other games and people are playing these previews because the technologies have gotten so good at recommending something relevant to someone. Speaker 3 (5:29) There's been a lot of hand-wringing about the impact AI will have on the ad networks, specifically Google's interface, and OpenAI has an ad product now. I'm sure you've been monitoring it and trying to learn from it. What is... advertising going to look like when people are doing five or six queries with a chat bot? Because it's pretty obvious, 95 % of the world are not going to pay 20 bucks a month for this technology. They're going to expect it to be free. ChatGPT has already said they're going to make it free. Tell us what they're doing in advertising, and is it going to be less effective each time, but in aggregate, people are going to use it more, or is it going to just be even better than Google Search's franchise? Speaker 1 (6:12) Yeah, I mean, there's two sides of advertising. One part of it is bottom of funnel advertising where a consumer sort of knows what they want to buy, but they're doing