The Exchanges

Q Ok, I have a hard question. How are you going to become a trillion dollar company?

A I mean, as an advertising business, again, I said this earlier in the pod, but you got to make money, otherwise you don't have a really good advertising platform, and we fortunately make a lot of cash, and we like to think, just in traditional finance terms, you're worth your cash flow after SBC and what you expect that to be many years out into the future and the terminal value of it. And if you think about where we are today, We probably on an EBITDA basis, I think we're over a seven billion dollar run rate, and we generate somewhere around 75% cash off the EBITDA dollar. Now, the business itself, and then that's sort of after SBC. If you took us three years ago, that number was much, much smaller. It was probably one 20th of where we've gotten to in three years. To take it from this scale, Up and be worth a trillion dollars. We've got to believe that we can get to thirty billion plus of cash flow a year. If we could get to thirty billion dollars plus cash flow a year, depends on how quickly you can do that in the future. Investors probably give you a pretty good multiple on like cash flow to get you to that. And so when we think about the things that we're working on, everything that we work on has to have a very large economic opportunity. So, um, typically in investor terms, you think about total addressable market. Well, The games category we've done really well and we bu…

AI assessment note: “We've got to believe that we can get to thirty billion plus of cash flow”

Q What do you think is going to happen to them?

A Uh, a lot of times when companies reach that point where it's tough and revenue multiple and potential cashflow multiple, if you do big layoffs ends up pretty low, they start getting accumulated by private equity or effectively plucked off the public markets taken private because the only way to recover it is a complete restructure. You fire a lot of people, you cashflow it, you lever the business up and that fits the private equity model. It doesn't fit the public markets all that well anymore. Once you can't Convey that you've got pricing pressure in a big market on the other side, you tend to lose all your, your, your multiple in the public markets, and then you're not a good public company.

AI assessment note: “they start getting accumulated by private equity or effectively plucked off the public markets”

Q How has AI changed the making of ads?

A It's early. It's not like, like, you can get a good clip, a short ad, out of some of the large language models. The challenge is to get them to put together a 30 to 62nd video advertisement for a brand that doesn't mess anything up, because you can't, like, anything wrong in that video, the brand's not gonna approve it to run. And so, can't mess anything up. Have to be engaging. And for a pretty long extended time frame, not that easy yet. So it's not at a place where you're just going to get a massive amount of inflow of advertisements that are diverse and creatively inspired and going to create lifts and campaigns, but their tools are available now so that humans can create ads much faster and much lower cost. So we've seen much more ad content coming into the system. It's just not at a point where the average marketer can go type into a box and say, here's a great ad and off we go.

AI assessment note: “tools are available now so that humans can create ads much faster and much lower cost”

Q What is more data that you have behind those ads? Because you serve to effectively like a billion people. I see this on your website and they sit there for 60 seconds and they get to serve this ad. So what is the typical click through? Like, how do you determine that?

A Well, you have the engagement. So you have how they're playing, what they're engaging with, then you follow them through conversion funnel, right? So We serve the ad, user engages with the ad, user goes to install or doesn't install. Sometimes people will just say, I don't want to engage with this ad at all. I'm not going to, I'm not going to click anything on my device other than skip the ad. And so, you know, that person just really doesn't like that ad. And on the other side of the extreme, someone might follow the ad all the way through the app store, go download an app. So now you know, okay, this is pretty warm. They're interested in it, but just a download for us means nothing. We're trying to deliver to the advertiser engagement and revenue. So to get really hot, The user then has to engage very regularly and has to go generate revenue, whether ad revenue or in-app purchasing revenue for the customer. The benefit of, of doing what we do is that we, we can serve the beginning of the conversion funnel and then close the loop all the way at the end. And the advertiser gives us data to help close that loop. And then geo system can then take all of this data, which across our, our business is a ton and put it all into this model to then determine, okay, now I've got One thing that this person's really hot on, what other users are like this person? What should I start predict…

AI assessment note: “you have how they're playing, what they're engaging with, then you follow them through conversion funnel”

Q move faster. But I like to ask this question on more of a personal performance standpoint. Um, for you, Adam, Michael Barton said you were the most locked in person that he's ever met, but I'm curious from maybe both of your standpoints, how did that come to be? And maybe is there anybody that you've been inspired by that keeps you motivated? How did you become that locked in?

A I don't know if I'm locked in. First of all, that was a great native ad. Um, it's, uh, your partner should thank you. But, uh, uh, it's, I always optimize my life. To remove all distractions and focus on the one thing that I always get at, which was building a business in the category that I'm in. And for, for me early on, it was find my passion. I don't know why advertising became the passion, but it was sort of an extension of something I used to do, which is derivatives trading, finance, math, algorithms, placement, prediction, all those things came together in advertising. And so I found my passion and then I tried not to do things around it that would create distraction. I'm not I'm not out there super active on social media. I'm not out there making a whole bunch of other investments. I'm not out there, um, speaking at a lot of different conferences. I'm basically a hundred percent wired in to try to do the best job that I can with this. And if I can do that well, then I feel like I'll, I'll have succeeded. And so that's my answer. I don't know.

AI assessment note: “I always optimize my life. To remove all distractions and focus on the one thing”

Q How do you continuously challenge each other internally?

A Let me, let me cover that, the prior question, too, and then we'll get to that one in a second. But I think the big mistake I've seen is people Really handhold new talent and bring them along slowly. So one of the things that's a little unique is like whether geo is an intern or a full-time employee just started maybe even right out of school, um, they can push code within the first week of being here. And so one of the end of the day, we're an advertising company. So if we went to a really high IQ, um, graduate out of one of the top universities, And said, you're going to build ads. It's probably not easy to go get them excited about this opportunity versus all the other opportunities they have in front of them, especially in the field of AI. And like here, they come in and intersection of math and engineering, and they're building models or data and plumbing to support the infrastructure that we need to run the models that we have. They come in and they just get to deploy code. So they get hands-on experience. There's no process in front of them. There's a lot of controls. In place to make sure that their code doesn't blow up the whole system, but there's no process in front of them where it's go through all of this training and go like review this, this, and this, and talk to these 15 people who will bring you along in over six months. And then now you get to be a little bit…

AI assessment note: “Let me, let me cover that, the prior question, too, and then we'll get”