A Product Market Fit Show | Startup Podcast for Founders
00:30:20 · Dan Novaes
And then if we get capital, we are going to take a play out of like, if you think about what we're doing, we're sending consumers into other services and then an advertiser is paying us a certain amount because they have a bigger LTV on the other end. So I was like, can I just do that for myself? Like, can I go and acquire other apps and games and send my own consumers into those apps? But instead of be just collecting the CPA fee or the CPM or whatever, I can actually capture the entire LTV on the backside. I'm going to ask you
00:30:48 · Pablo Srugo
[00:30:48] S1: for a small favor, a tiny little favor. In fact, it's not even now that I think about it, it's not even really a favor for me. I'm actually trying to help you do a favor for you. Just hit the follow button. You won't miss out on the next episode. You'll see everything that we release. If you don't want to listen to an episode, you just skip it. But at least you don't miss out. Can we maybe pause here? Yeah, let's think about maybe like, just to make this all concrete, right? Take a game. Like, I have a mobile game, right? How do I earn money as somebody who makes a game? Like, realistically, people paying in-app and doing these things and ads. I mean, those are probably my two ways that I make money. I need to get people to play my game to begin with. You know, let's just imagine ad revenue is the main thing. People are paying me to show their ads in my game and I'm paying the App Store or Google or whatever to show my game, you know, to other people. and I might pay you. You know what? Why am I paying somebody to see something or paying somebody to click something to maybe then download and then have that funnel? I can just pay you and you guarantee they play the game for X amount of time? Like, is that how to think about it?
00:31:50 · Dan Novaes
[00:31:50] S0: Yeah, so basically, say a big game, let's just use Candy Crush as an example. Candy Crush will say, hey, I'm willing to pay $10 for a user to come into my product and it has to back out for them. Like, they have to see that their LTV is going to be higher than $10 or they're not going to pay that. And so what we'll do is we'll go to the consumer and it's like, hey, look, we'll pay you $5. We'll pay you per minute you play Candy Crush. So it's not like you're getting $5 on the download or else everyone's just going to download and stop right there and then you can create a habit off of that. If you get to these different milestones deeper and deeper in the funnel, so get to certain levels or in-app purchases, you may earn well beyond $10, right? Because you're a certain type of user. You're kind of like, you become like a more valuable user to that ecosystem. If they notice that you're not buying anything, then they're going to start showing you more advertising like most of these companies do. These users tend to be more ad tolerant, right? Because at the end of the day, they're getting some sort of reward for taking action. Those other advertisers could be other games. It could be CBG companies, whatever. I mean, at the end of the day, just because someone's budget conscious doesn't necessarily mean that they don't have any money. It just means that they're more thoughtful about how they have to spend. So anyways, that was the thesis of the model is like, we take a percentage of the revenue and then align incentives to a specific action that the user takes. So that was like how it all started, right? From an advertising standpoint.
00:33:03 · Pablo Srugo, Dan Novaes
[00:33:03] S1: It's just a pretty crazy loop. Like when you think about somebody that's going to get paid, but with games, I can see it, right? Because you pay somebody to play for a certain amount of time in the thesis and you show them ads when they play, you make money off them there. But the thesis is they become just a player. Like at some point, some percentage of them actually love the game. [00:33:19] S0: Yeah, the games are good. They're not like, you're not just showing like trash to them. And that's why the model works, right? And that's why the whole thesis is like, what are things that people are going to do anyways? [00:33:28] S1: So that's my question. Games is obvious, but what are some other things? Because you could imagine in some place where it's obviously going to break. Like go do this behavior, but you know, whatever. People don't like it. It's not habit for you. Just churn out and then nobody's, you know, just a clear loss. Like you might make money, but.
00:33:42 · Dan Novaes
[00:33:42] S0: Sure, sure. So, and yeah, and that's the constant game that you kind of have to like tweak on this. So news is another one. Like people are going to read the news, right? And then there's advertising that can occur in that. It could be also the offers that we talk about. Like, you know, you, when you start a three month, you may not be interested to start another three month thing to stars. Like I'm going to say stars because it's one that a lot of people aren't necessarily subscribed to. But if you're like, Hey, get 20 bucks to get a three month free trial to stars. You then test out stars and then you're like, Oh, you know what? Actually, yeah, there's some good movies here. Maybe I'm going to stay subscribed. I mean, it happens in almost any thing, right? It could be also like a bank, like think about like chime. Hey, connect your account and set up ACH, get 200 bucks. And so a portion of your paycheck is that you get a bonus. Are you going to delete that bank account? You know what I mean? So I think like, you know, we basically kind of think about all these various activities that those actions can take. But now what's happening and this is kind of like the manifestation of the company and growing is this idea of like data, right? And in the AI world, consented data is like, that is the new thing, right? It has to be consented because of all this regulatory framework that's happening. And so if you think about what's happening in the space, AI agents, right, are effectively going to be doing stuff for us, right? It's like, hey, go, I need to go buy this thing or I need to go take this action. These AI agents need to know how humans navigate through apps, for example, and games, right? Like a gaming agent that's like my little friend that plays for me while I'm sleeping needs to understand how these 3D worlds operate. And so what we're able to do is also now, and this is what we're starting to get on now, is basically reward consumers to basically show recordings of the content that they're engaging, whether that be on a TikTok or an Uber Eats or a game, and then we could essentially reward them for the time spent on things that they're doing. Meanwhile, take the recordings and then you basically provide that to the Frontier Labs and the Frontier Labs can then essentially create the next generation of gaming agents.
00:35:38 · Dan Novaes
And this is, that's a very specific example, but this is happening in wearables, right? The next, basically, Frontier Labs are trying to figure out when does someone go from being a healthy person to a person that's developing diabetes. And in order for them to do that, they need to get significant amounts of wearable data and general data from healthy humans and then essentially extrapolate that data and essentially, you can reward the consumer for doing that, right? And so I always go back to an example of like, I did my first marathon last year, right? And I started religiously using Strava. It took me nine months to pay the $70 that Strava charges for the Strava premium because I just didn't see the value in it. Eventually, I caved, but I can definitely afford it. A large percentage of people would not pay for that subscription. However, if Strava came out and was like, hey, if you give me your Apple health data, I will give you Strava premium for free for six months. That Apple health data anonymized, because it would be anonymized, it's probably worth about $20 or $30 on an annual basis. If you think about what Strava's actually earning in a six-month period minus App Store fees, it's about $20 or $30. And so the thesis is, you know, a certain percentage of people are never going to share that info, but a larger percentage of people will. And that's the whole back, go back to the whole theme where it all started with Slyker, Bearnap, all that stuff. People are willing to take action if you align incentive with them and you get their consent. And that's our whole business model, right? And now we're just doing it across a bunch of different apps and services that have product market fit that we can create incentive systems that allow the free users to provide insight and get rewards. And that could be in the format of money. It could also be in the format of free product, like the Strava example that I just gave.