The Exchanges

Q Well, you just wanted to have an app because you saw everything shifting there?

A Yeah, I wanted to have an app because I wanted to own the audience before we got into anything else, and so actually, like, that, that transition that goes to the third app we launched was the first version of App Levin. It was an app discovery app, and this was, I think it was in, in late summer to fall, 2011. You and I would go connect on this app, App Levin, and it would tell you, hey, Adam's playing Words of Friends, you should go play Words of Friends with him. And that was the entirety of the app. It was just an app recommendation app. The app itself stunk, but when you got that push, the response rate was through the roof. Everyone who was on that app was going and downloading other things. So we're like, okay, well, there's a, potentially this app source is going to be bigger than people realize. There's gonna be a ton of content. This app stinks, but this recommendation algo is really cool. And so that, that's what really turned into what we became, which is we took that recommendation algo and just launched it. Eventually as an advertising platform on other apps.

AI assessment note: “Yeah, I wanted to have an app because I wanted to own the audience”

Q borrowing? You're, you're down 3.8 billion market cap, right? Explain like how you were thinking, the difference between how you were thinking about inside the company versus, you know, the world telling you about your business, because there had to be a lot of people around you saying, what the hell's wrong with you? You gotta be nuts going into debt. To buy back your stocks of this shitty company.

A I mean, look, a lot of times, like, people like to be conservative when it comes to cash, and so one, to, to lever up is scary to people, but then two, to lever up to buy your own shares, when everyone's telling you your, your company's a piece of shit, that's really scary to do. I never believed in saving cash for a rainy day. I feel like I'm a big believer in what we're building. I believe in where we're going. So if I believe in the future, and we're a really high cash-generated business, We should always be buying back our shares. So at a bottom point where the valuation became that juicy, there's no reason to be afraid of it. And the good news is, I mean, I don't have a lot of experience with boards and we can talk about that in a bit, but our board was very supportive because it's not rocket science. You look at a, a multiple of five times cashflow and you go, okay, why don't we just buy all the shares by as much as you possibly can. And so Because it was so cheap, and we had a lot of conviction on our future growth prospects, we just hit it, and hit it as hard as we could.

AI assessment note: “Because it was so cheap, and we had a lot of conviction on our future”

Q Let's just focus on this. So now you're, you know, 350 to 400 of them today. What were you back then?

A Uh, so we were more, yeah, I'd say probably close to double that, and so this guy, Giovanni, who just started as CTO, he joined, and he, he joined in November, 22, and he's responsible for him and Basel, that the CTO I talked about, they, they basically together worked on the Axon two model, really, Giovanni led it, and then built out the team, and he runs the team. Now, the reason I raised his name is, he came in, and he started asking me interesting, but difficult questions. Questions like, why do we have this person? Why do we have this team? Why do we have, like, these processes? And as a business, you sort of go, when I first started, I didn't want any process. I have almost a no meanings rule. Like, I wanted everything to be as highly efficient as possible, but over a decade plus, you inherit some process. You go public, you're told you need these processes, you need these people. Well, you got someone in who's fresh blood, who's really hungry, insanely high IQ person. I mean, one of the smartest people I've ever met. Much smarter than I am. And he's grilling me with this question every day. Like, why is this person in this role? Why is this person here? Like, how come this person is a VP to this person and the person underneath that person is much better than the VP? So I kept getting these questions and I was like, either I'm going to have to address these questions or …

AI assessment note: “so we were more, yeah, I'd say probably close to double that”

Q What does the business consist of at that point?

A It changed a lot. So when we first started, we grew really quickly, and I mean, we cleared over a hundred million dollars of EBITDA, and we had a very simple algorithm. In advertising business, the algorithm is key if you're doing performance ads. So our very early algorithm was if you play a solitaire and you play a poker game, people who play solitaire and poker also play these games. And it just pushed you games, and you'd see game, game, game, game, game. Eventually you download off of a simple algo like that. What we realized, um, as really machine learning technologies evolved, and, and Facebook built this fantastic platform. Over the 2010, once they got their mobile marketing platform out, they really did turn ads into content.

AI assessment note: “In advertising business, the algorithm is key if you're doing performance ads.”

Q So explain when you knew it was working the way it is now, and what was happening before Like, what was the, the model before that?

A Yeah, I mean, so where we are today is, and, and this is where we wanted to get to, which is the product has to be good enough to sell itself. Otherwise, if we're begging for business, we don't have a good advertising solution that's scalable. We don't have the salespeople to go beg for business. And so what does that mean? Well, if you're a game developer today and you plug into our platform, you're gonna spend a thousand dollars. You're gonna know with certainty you made more than a thousand dollars on that spent. You may have a business model that says, I want to break even on that thousand dollars in a year, and by year five, I know I'm gonna make 5000 dollars, and so you put the thousand in, you get a thousand back in a year, and year five, you're at 5000 bucks. You may have a shorter cycle. You might break even on the thousand in 30 days, and then by six months out, you made two, 3000 dollars. Whatever your business model allows, you're gonna be able to price into our system and generate more money from the dollar spent than, than what you put into the system. Now, what's important about that approach, Is that they become an arbitrage. The only constraint on them scaling in our system is the money that they have in their bank account. Cause if you tell someone you're certain to make more money than what you put in, you're going to know it. Our reporting is going to tell y…

AI assessment note: “where we are today is, and, and this is where we wanted to get to”

Q How much profit do you think you were making on a, on a monthly basis out of that million?

A Barely. It was, it was a little bit profitable, but the, I mean, back then, nowadays, like ARR ramps are astounding, but, and as our valuations, back then, to build a business in mobile and have it go from zero to twelve million dollar run rate in that short amount of time was really phenomenal. And so, Once we did that, it was easy to recruit investors in November. I mean, it's like, okay, looks pretty good. It was more around for a few folks that I had just known for a while and a few other folks that I thought could be helpful to the business and to mark my own dollars in. And so we did that round in November and then we didn't raise another round. So back to the board point, and we did raise another round, there was more liquidity later, but back to the board point, um, I didn't have a board in this business until 2018.

AI assessment note: “Barely. It was, it was a little bit profitable, but the”