Podcast: Understanding rewarded user acquisition (with Tricia Han and Sampsa Jaatinen)

On this week’s episode of the podcast, I am joined by Tricia Han, CEO of Mistplay, and Sampsa Jaatinen, Chief Data and AI Officer at Mistplay, to explore the rapidly evolving world of rewarded user acquisition. We dive into how the rewarded model has matured from a niche Android-focused strategy into a primary growth engine for mobile gaming across both major platforms. Among other things, we discuss:

• Why rewarded user acquisition has moved from a niche tactic to a cornerstone of modern mobile gaming growth strategies
• How the shift in Apple’s App Store policies regarding incentivized installs has created a new frontier for iOS developers
• Whether the rich behavioral data sets generated by rewarded platforms provide a significant competitive advantage over traditional ad networks
• What role machine learning and reinforcement learning play in optimizing the timing and nature of user rewards and recommendations
• If the play-and-earn philosophy can be successfully exported to non-gaming industries like retail, finance, and quick-service restaurants
• How the blurring lines between mobile and console gaming will influence the way platforms compete for limited user attention
• When the industry will fully realize the potential of direct-to-consumer web shops coupled with highly personalized reward mechanisms

Thanks to the sponsors of this week’s episode of the Mobile Dev Memo podcast:

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Interested in sponsoring the Mobile Dev Memo podcast? Contact Mobile Dev Memo advertising.

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Transcript

Eric Seufert: Welcome to the Mobile Dev Memo podcast. This is your host, Eric Seufert, and I am joined today by Tricia Han and Sampsa Jaatinen. Tricia, Sampsa, welcome.

Tricia Han: Thanks, Eric. It’s great to be here.

Sampsa Jaatinen: Hey, Eric. Good to be here. Thank you for the invite.

ES: You’re very welcome. Sampsa, I’ve known you for an eternity. Tricia, we met more recently. I’m very excited to talk about Mistplay today and the rewarded UA space more generally. It’s a really fascinating space that I’ve wanted to do a podcast episode on for some time. Before we dive into that, maybe you both could introduce yourselves. Tricia, we’ll start with you.

TH: Absolutely. I’m Tricia Han, the CEO of Mistplay. Eric, probably the reason you and I haven’t necessarily met before this is I actually don’t come from a traditional gaming background, but I’ve spent a lot of time in mobile apps. I’ve been in consumer tech for over 20 years. My very first startup was actually a company that built mobile apps and a mobile platform. It was pre-iPhone and it was so early that at the time I actually built a mobile ad-serving platform because it didn’t exist. That’s how long ago this was.

I’ve always really loved mobile apps. Most recently, I was the CEO of a company called MyFitnessPal. It is a large-scale mobile app for tracking fitness and nutrition. The reason I mention it is, one, it’s mobile and has a lot of the same dynamics as mobile games. What’s really interesting about it is that it’s a business that’s based on data, on user engagement, and monetization of that. There are a lot of behavioral mechanics that come into play because it’s really about getting to good health. I bring a lot of that over with me and I’m really excited to see how much is transferable to the mobile gaming environment.

ES: Given the success of Mistplay, apparently a lot is transferable. Great, thank you. Sampsa?

SJ: Yeah, I’m Sampsa and I’ve been in the mobile advertising space for a long time. I joined Unity in 2014 through the Applifier acquisition. I started the data science, machine learning, and analytics teams for Unity Ads and spent more than a decade building the Unity Ads network. More recently, last fall, I joined Mistplay. I joined the rewarded space as Chief Data and AI Officer.

TH: And he’s still here, so that’s a good sign.

ES: All right, I would just love to start with Mistplay. Anybody in mobile gaming is familiar with Mistplay. It’s grown at an incredible clip over the last couple of years and it’s become a major share taker of mobile UA budgets. I could imagine that people outside of mobile gaming and just in the broader digital advertising space may be less familiar. Maybe we could start with an overview of Mistplay’s business and the rewarded UA model.

TH: Sure, that’s a great place to start. For those who may not know Mistplay, we’re often called the OG of the rewarded space and specifically in terms of rewarded user acquisition. Mistplay actually was one of the pioneers in the play-and-earn space, starting about 10 years ago out of Montreal, Canada. The way that rewarded works today is it’s really about value exchange. I think the simplest way to talk about it is by using the analogy to loyalty programs and specifically like points programs and airline programs.

There’s a real value exchange between your user, your customer, your brand, and there needs to be some sort of equal exchange for the two to work together. The way it works in rewarded is that you have your advertiser who is your game advertiser. They’re spending ad dollars, giving access to their game, and what they’re getting in exchange are qualified users. The users are giving their time, playing the game, and getting some rewards.

We also have another part of the ecosystem here, host apps. What they’re doing is they’re supplying their audience of players and what they’re getting in exchange is engagement of the audience and monetization. All of this activity happens on the ecosystem or the platform of Mistplay, where we are enabling the matching of these players, whether they’re coming in directly through the Mistplay app or through our partner host apps, and matching those up accordingly with game advertisers. We enable along the way the lifetime of the user, engagement, and recommendations.

ES: I would want to anchor the discussion to ATT. I think ATT was probably a major catalyst for Mistplay’s growth. Please disabuse me of that misapprehension if I’m wrong, but maybe we could talk about how Mistplay’s business has evolved over time and how it’s evolved since ATT and how that changed the dynamics of UA generally for mobile games.

TH: It’s obviously a really important topic. We might see it slightly differently. ATT was not the reason necessarily that propelled Mistplay forward. That being said, it certainly was a factor in where Mistplay started. Android and companies that were Android-first were really beneficiaries of ATT going into place just because they were able to still attract players. The really good ones who were able to scale was with a strong opt-in incentive.

It was easier to grow and scale on Android first. That being said, the landscape has changed a little bit. ATT was not the reason that Mistplay was not on iOS. It actually was because for a long time the Apple ecosystem had guidelines that restricted what they called incentivized installs. They actually changed that last year and that actually opened up the market for a lot of rewarded apps to now be able to be live on Apple, in full compliance, and really start to find those players for rewarded advertisers.

ES: Historically we had the Tapjoys of the world that could only operate on Android under the restrictions of the App Store developer policy. Mistplay was historically very strong on Android. You’ve now rolled out Mistplay for iPhone and you acquired MyChips. What are the unique hurdles that you’re seeing scaling the rewarded ecosystem in iOS under this different set of rules on Apple?

TH: Apple is just a different ecosystem than Google Play with different rules. Not bad, just different. It’s really important to understand what Apple cares about. They care a lot about privacy and data and they care a lot about opt-in consent. Luckily for Mistplay, that’s always been part of our model and our mechanism.

Consumers are willing to trade off information for either less friction or for some value on the other side and I think that’s what rewarded really taps into. We’ve always asked for consent for users to be able to understand what games they might like to play and how they play it. This is where rewarded is really different from your traditional install campaigns. What rewarded and what Mistplay has done in particular, and where they’ve been a pioneer, is that after getting the consent from the user, we are getting a lot of post-install behavioral data from users. What they’re downloading, but also what they’re playing, how long they’re playing, what they might be spending in IAP or IAA, and when they’re churning. Also, what are the things that might motivate them as well as the rewards that are interesting to them. That’s actually a really big difference between rewarded and what I might call a traditional ad network type of model.

Back to the iOS thing, what’s been really important is that we are in full compliance and that we’re getting that user to actively say, yes, I want this and I give my consent to opt into this platform because I know very clearly what’s on the other side, what the reward is for me, it feels fair, and it feels like a good exchange.

ES: To your point, that tradeoff can be a lot more abstract or nebulous just with a standard ad network. Sampsa, I’d love to get your thoughts on the operating environment. You joined Mistplay before it started operating on iOS. I’d love to hear what your experience has been seeing that come to life and the different operating norms and realities for a rewarded UA network.

SJ: That is definitely one of the things that I find very interesting. It was a very interesting change for me from coming from the traditional ad network which is two-sided marketplace to something that feels like three-sided marketplace where the consumer, the actual user and the person who plays the games, is also taken into account as a party who has needs or motivations. It’s a meaningful change.

It looks to me like because of this relationship that we have with the consumers and the ability to ask for their consent and the ability to offer something really meaningful back so that people understand what they are giving and what they are getting against that consent and the data that they allow us to collect, the difference between the two environments seems smaller than for the traditional ad network. This is something that at Unity, and I believe this is true for all the ad networks where the consent mechanism is completely different and we do know the difference in value for machine learning when people either can be followed across the applications versus not. Being able to have that consent makes both of the environments to feel a little bit more similar in our case than for the traditional ad networks.

ES: Were there any sort of scale challenges that you didn’t expect coming into Mistplay from the more traditional ad network space or opportunities that surprised you?

SJ: Not really surprises because this was known to me, but there is a massive difference in the owned and operated inventory, the volume of the data when we specifically talk about machine learning. The volumes of the data that we are talking is obviously completely different than what the data volumes at Unity we are talking about, multiple orders of magnitude difference. Eric, you know machine learning well enough that you know more is more. More data is always better for the model accuracy, but we have enough. We have enough to be able to do the most things.

We have enough to be able to improve. We have enough of users to be able to really make meaningful machine learning. As I said, the data that we have is richer, it’s better. We have better behavioral signals. We have a better understanding of the users in the system. None of these were surprises. Maybe I’ll share the funny thing that always when you go to new place, people who work there think that they have a lot of data. When I was at Unity I thought we have a lot of data and then if someone joins from Meta, they laugh at us because they understand that the data difference is multiple orders of magnitude difference.

ES: Tricia, going back to you, walk me through the acquisition of MyChips. Maybe explain what that was and how it fits into the broader strategy.

TH: Ultimately, when it comes to businesses like ours, it’s actually fairly simple. Our customer is the advertiser and there’s really just two things that they need. They need ROAS and they need ROAS at scale. We had as Mistplay done a really good job over the course of our history, having our own first-party host-installed data, but we knew that we could take all of the learning that we had and figure out how to apply that for the benefit of larger scale and for these other applications to build this larger network. We could take all of that, feed it back to Sampsa and his data science team, and figure out how do we do this on behalf of our advertisers and within the environment of these host apps.

We met the MAF team, thought they were fantastic. They’d really built scale with quality as well as they were really strong in markets where we’re also strong. They’re quite strong in APAC and in Europe. We’re quite strong in North America and Europe. Between what they’d built and what we knew what we could apply specifically from the AI machine learning perspective, all of a sudden we have something that’s much more interesting on behalf of our advertisers, which is again network of scale with a lot more data that we can run through the models so that we can do a much better job of matching people, of finding people with the right intent at the right price and right scale through our models.

ES: A good segue from that is the audience network. You launched an audience network in May. Talk me through that, the strategic impetus, how it’s going, what that provides.

TH: It’s going really well. We are deep in, well, let me just say that Sampsa and team actually have some real intriguing data from models that are coming out soon and this is the basis of a lot of what we’ve built by putting all of these data pieces together. We’ve got a bunch of exciting launches that are actually in progress and globally. What we’re able to provide to our advertisers is quality, scale, less friction. That was the whole impetus of building this Mistplay Audience Network.

I talk to a lot of customers. They’re of course working with a lot of rewarded channels. That being said, every environment, every ecosystem works a little bit differently. Of course, it takes some time to learn what works in each of these systems and what are the signals that not only do you put in but can you get out of them. Our job was really like how do we deliver more scale at the right price in such a way that our advertisers could really have a unified platform and experience, one button so to speak to deploy their spend to get what they needed.

ES: I remember we were speaking a couple months ago, you mentioned you had a big announcement in May and that was the MAU moment, so that was that in retrospect.

TH: MAU was really exciting for us. It’s where we announced that we had joined forces with MAF and the MyChips product, as well as that we were rolling out the Mistplay Audience Network. So far the reception has been really strong. We’ve been really excited by not only what we’ve been able to do in the short term but also the future strategic opportunity here.

ES: MAU seems to be having a renaissance.

TH: It was really, really great. And you know one thing I’ll add, what’s interesting is I will say that rewarded as a category I think is also helping to fuel some of the energy around MAU. The only reason I say that is we were talking about it internally. Because Mistplay was one of the very early entrants here, we as a company used to go to MAU and you would see just a handful of rewarded booths on the floor. If you went this year, it was really remarkable to see how much of the floor was actually devoted to rewarded. I think that’s just a sign that there’s a lot of excitement around the category. I think it’s because it’s really delivering something new and different, but more importantly it’s also more proven now for a lot of advertisers. So you really see that.

ES: When we spoke the first time, I made the case that I thought rewarded was, if not the principal factor, certainly a major contributing factor to mobile gaming’s rebound back to growth. If you just look at the share of spend for a lot of advertisers, I mean that must be true. There was just this big hole in UA budgets that got filled.

TH: Absolutely right. Yes. We definitely have clients where 30% of their mobile spend is now in rewarded. I saw a stat just the other day, some other industry stat that there are some advertisers who are spending as much as 60 to 70% of their spend on rewarded, which is really remarkable if you think where it was five years ago. It was probably like 1 to 2% of their total spend. I think you are seeing this acceleration in the category. A lot of that has to do with how rewarded is different and it goes back to that post-install data and the ability to influence behavior for deeper gameplay, for longer engagement, which is quite unique to this specific category of UA.

ES: You just get a richer view of the consumer and you can do a lot more optimization as a result. I want to talk about that because legacy offer walls were kind of seen to deliver low-quality traffic and high levels of churn. How does your AI engine change the quality and retention of players compared to legacy rewarded ad units? Sampsa, how does that multiple orders of magnitude really contribute to better cohorts and better retention?

SJ: Before I start answering that question, I might get excited about this because machine learning and these kind of things are my jam. I have a threefold simplification that I want to use for this particular case. One is intention matters, second the games matter, and then the timing matters.

When contrasting against the legacy offer walls, I think there’s a little bit of a problematic setup or challenging setup that is influencing or impacting how well the offer walls work for something like this. If you have a offer wall offering in your game, you give rewards that expects the person to return to your game. It’s almost like you are offering a side quest to go to play some other game for a little, but the reward that you get is really currency in that first game. That reward is completely meaningless unless you really return to that game and keep on playing. There’s limited amount of time people can put in the games, so it’s always competition of that attention.

That’s what I mean by the intention. We don’t have that because we don’t expect people to come and spend their time and money in Mistplay, they just swing by while they are going somewhere else to have fun.

But that’s how we get to the machine learning. Of course, the AI engine that we are building is based on those two other principles where one is we know that the game itself matters. You can sometimes see simplifications that people talk about game categories, but people inside the gaming industry are very proud about their products. We know that games are highly specialized creations. So it’s very important to be able to make recommendations for people specifically on things that they like. This is where the behavioral signals, people’s actions both in the Mistplay application and the other games that they play, meet the actual machine learning. This is where rubber meets the road and we can make those recommendations that are great for people. We want to incentivize something that people are inclined to do anyway. That’s usually where it works the best. Trying to incentivize or reward people doing something that’s completely unnatural for them, playing games that they hate, that would be very expensive and it doesn’t help anyone.

So the recommendations just knowing the games, knowing the people, and being able to make that match. Then I’ll mention a little bit about the rewarding as well because that’s what I mean by the timing matters as well. Because this is important for the client performance. We don’t want to take people out of the games that they enjoy. If someone is really having time of their life with a game that they recently installed, they are engaged, they are spending money, it’s not really in our interest to try to get that person to install some other game. We would only try to incentivize people moving around when the time is right.

That’s why I say that it’s this kind of a trio of things when it comes to the AI engine. Knowing what to recommend, knowing when to try to make people to do something. And that is very well aligned with the longer-term performance of the user acquisition as well. When we see that someone is engaged, that’s the behavior that we want to reinforce. When we know that they are about to find something else or need something else, then it’s our time to take an opposite stance and act.

ES: I think structurally with games, one thing that is underappreciated is the opacity for the user when they are engaged in a game because the game that a person’s playing and maybe is monetizing in is unlikely to show them ads. A lot of game developers do that. They’ll shut ads off for someone if they even seem likely to make a purchase. You wouldn’t want to divert them elsewhere. Having that touchpoint with people while they’re engaged in another game is unique.

If you think about the visibility you have into a user when they click and install a game, often times that visibility drops to zero for some very extended amount of time because they’re playing the game. People usually play one game at a time. If they’re engaged in that game, they’re probably not seeing any ads and so they just don’t pop up in the bid stream even if there is a MAID available. You’ve got the O and O inventory, so they’re coming back and you’re seeing them even if they are engaged in another game.

SJ: That is correct. We see them every now and then because they want to come back and pick up their rewards, but also because we built the economies for the games. We see how people reach these milestones that we set in the games that we reward them against. So we have that window on really what’s happening with them, with the users, when they are playing the game.

ES: You would know this having worked in the space for some time. But that was one of the impediments to doing anything other than contextual ads going back years. If your only visibility is in games, if a user’s playing a game, they’re engaged, they’re likely to monetize, they’re not seeing any ads. So you have no visibility. You see the click and the install and then maybe they pop up again in a year when they are back in the market for another game. That really only left contextual advertising. You didn’t really have a rich behavioral data set on the person. Even if you could have that, you just didn’t because they would disappear for long stretches of time while they were engaged in another game that didn’t want to show ads to them. Am I characterizing that correctly?

SJ: You are and of course that goes back even more strongly with ATT that you mentioned because when people pop back up somewhere else, you wouldn’t even know if they are the same or different person. But that’s true. We have a system where people have reason to stay in our ecosystem. We have that visibility without being in competition with our clients because we are not game. We don’t want the same thing from the users that go through our system than what our clients want.

ES: Your loyalty play initiative aims to bring the play-and-earn philosophy to non-gaming apps. Which industries outside of mobile gaming are showing the highest demand for rewarded user acquisition?

TH: We see really good demand in a bunch of industries. I’ll say I think what’s really interesting about loyalty play and in particular, we also acquired a company called Connected Rewards. Connected Rewards had done a really good job specifically going into categories like fuel and convenience and QSR, and of course things like fintech and commerce are really good opportunities for this kind of rewarded UA.

In particular, I’ll just call out like for example we work with companies as big as Chevron. I don’t think that’s one that you would naturally think of for a gaming reward. But I think what the folks at Chevron realized was how do you introduce an experience that is already something that people are actively doing that they like to do and how do you then, is there some opportunity for positive brand association and engagement with the brand even if it’s not exactly what the brand is known for.

What I can tell you is like for our fuel category and our convenience store category, we are seeing up to like a 44% faster return trip rate for customers who downloaded games as part of this loyalty program. In terms of for example even restaurant, restaurant’s another interesting one. It’s sort of like quick-serve. We work with companies like Checkers and Rally’s and what they told us is and what we’ve been able to measure is that we saw a 54% engagement from lapsed users once we introduced this program and kind of let them know that this was an opportunity.

Ad networks can deliver somebody to the restaurant, but what we can do is not only do we deliver you but we can also help incentivize the ordering of the appetizer and the main course because we might give you a free dessert. It’s really interesting and it’s happening in real time and it’s sort of blending sort of this online and offline experience, which is the way that most people operate anyway.

ES: Have you seen uptake for just other non-gaming app categories?

TH: Commerce, of course, always strong, fintech strong, but these are all evolving. What’s really interesting about them especially for game companies is that we are now able to give them access to new inventories of players that they didn’t necessarily have before. It’s just slightly different than what you might get through traditional channels.

ES: My sense is like if you think about the kind of tailwinds for mobile gaming, that’s a big one, just injecting more varied demand into the IAA economy which should drive CPMs up. And then the other is the fallout from the Epic v. Google and Epic v. Apple lawsuits where link-out is permissible and you’re seeing a surge in D2C revenue. I see them both as very meaningful and I see them in concert to be extraordinarily meaningful. You could imagine 30 to 50% revenue opportunity with very little fundamental work needed. It’s really just stuff that’s plug and play.

TH: I agree. I agree with you. Again, the industry is so innovative. It’s going to keep finding the next level of experience for users, for the overall ecosystem, to continue to deliver interesting experiences, monetize better yield overall. This is what gets me super excited about the space and the industry is that just as you said, we’re seeing new announcements every week, every month. It certainly keeps us on our toes, keeps us continuing to innovate and grow and really think about how do we best serve the advertiser. It might be through integrations with web shops, for example, or thinking about our own models and how do we evolve those to really make sure that we’re on the cutting edge.

ES: I called out rewarded in my 2025 predictions. I called out rewarded, I said that’s one of the reasons that we’ve seen mobile gaming return to growth. Reward is just driving more growth than people recognize and when you pair that with the ability to then you have incremental ad spend on a channel that delivers demonstrable ROAS plus then you’re able to I think reducing the commission on the D2C stuff is interesting and certainly there’s a benefit to that. My sense is like the real value is the personalization. So when you know just a third-party web shop is far easier to personalize than anything that you can offer in the App Store just because of all the constraints around registering the SKUs and that kind of thing. So my sense is like those two things in combination present a real tailwind for mobile gaming and I think there’s real reason to be excited about the category.

How do you apply the personalization with the rewards? How are you utilizing machine learning in the back end to ensure that players are seeing the most relevant things?

SJ: It is definitely critical part of the AI engine that we are building. There’s the recommendations as that we touched already and the rewarding. Just to give a little bit of the basics, there’s two different type of rewards that people can accumulate in the Mistplay environment. It’s the units and the gems. Units are the basic currency that you can accumulate just by playing the games. It’s tied to the time spent or the milestones reached in the game and then there’s a element of personalization that goes together with that.

The gems are tied to they are the secondary special currency that is related to making IAP purchases. But there are different surfaces where that change how those units are accumulated. There are different live op tasks, there are different type of special tasks that people can engage with. And all of these surfaces are something that we can control in terms of there’s of course the base accumulation of the rewards tied to those achievements and the gameplay progression, but we can always use machine learning to adjust how fast those milestones are achieved or what is the actual outcome of those milestones. We can expose these to people ahead of time so that they see the carrot in front of them.

And then of course all of these live ops and tasks are something that we fully control so that we can have a system where we adjust what do we reward people for. And this goes back to that question of do we want to make sure that they feel like they are rewarded for meaningful things, they get rewards for doing the things that they feel like they should be rewarded and then the useful like the meaningful outcomes for the advertisers as well.

We see this as two different types of problems. We do predict things, we do predict those things like install likelihoods, we do predict churn likelihood. we want to understand when the engagement in a specific game is declining, what are those culmination points and trying to understand them so that we know how to react. But we also see this as a closed control feedback problem. So we look at the rewarding per se itself quite a bit as a reinforcement learning problem. Because predictions are something where we just predict what happens if we don’t do anything.

And then the reinforcement learning helps us to understand what happens if we start taking actions and choosing those actions. What happens if we reward this person? What happens if we don’t? What happens if we reward them to do A versus B? So we are building this optimization system, this AI engine that combines all of these predictions and this ability for us to choose different actions and optimizing them given the personal attributes of the person, what they are doing. Again, that’s why I said that the timing matters. Where are they in their journey with the game? Where are they in their journey with Mistplay? What is meaningful for them right now?

Combining all of these things, we are building this engine that’s capable of making these personalized assessments, but also taking those personalized actions, which is super important for us and super powerful for making sure that we can guide people to do what we think is best for them as well.

TH: Maybe I could just overlay the qualitative aspect of this. Eric, I mean you’re seeing what we’re seeing in the industry, which is a growth in the category and some of that is I think consumer led. They’re really savvy. And I think a lot of consumers these days, they’re used to again credit cards with points, loyalty programs for all of their favorite places, whether that be the movie theater or their favorite restaurant or their favorite shop. And so many of our consumers, they’re like, well, I’m doing something that I enjoy anyway, I’d like to get it’s fun that I also get a reward for it. That’s like one interesting thing.

When I think back to even working for for in the health side, there is a lot to, there’s a lot we see in the data and then there’s a lot we try and understand for our players in terms of what does motivate them. Why are they here? And I think it’s what gaming companies know really, really well. There are rewards, there’s also just the social element, there’s competition, and there are a lot of other factors and so that I think has to go into the personalization as well. We spend a lot of time thinking about the segmentation, what really is important for each of these players and what are they looking to get out of it because it’s really different as you can imagine.

And all in all I think we are going through maturation of this industry as well because all the big ad networks have built their AI engines, they’ve seen the benefits, the industry has seen the power of these things. So of course we believe that this is something that’s going to be true for rewarded space as well and obviously we want to be the OGs for building the AI engines for these purposes as well.

ES: I think the point about consumer expectation of just loyalty programs, reward programs is a really salient one. I’m a consumer, I’m spending on a consumer product, I expect to get some kind of benefits of participation over time and that does track with my usage and that does seem like yeah, that’s pretty pervasive across the consumer economy why does it not exist in the app economy.

TH: And you know to your point about there are that there is more opportunity beyond just the major platforms. Another thing that we a lot of times hear from our users and from people in the industry is like the reason they like rewarded and they like Mistplay, there is an element of discovery too. It’s really hard sometimes in the App Stores to find games that you’ll like. We know that they can be gamed. This is kind of a more natural organic way to find and discover games that you might really enjoy. It’s hard, there’s so much noise out there.

ES: Yeah, and you know there were I don’t know how many attempts at like TikTok for games discovery. You get an app or like Tinder, I’ve seen a bunch of these where you hop on and you swipe left or right. I don’t know which corresponds to liking or disliking. But there were these attempts at like motivating greater discovery through like these kind of gamified aspects and it turns out, well, what you really need to do is give someone something. Like that just there needs to be incentivized in some way and just having another surface area for discovering a game is probably not that compelling unless they get something in return.

TH: Yeah, but what we’re finding is you can’t do this manually and you can’t do it with heuristics. And this is why you need the advanced machine learning and the AI to do this at scale in a personalized way to be effective.

ES: So I’m cognizant of the time. I do want to touch on the unit economics of this model. Maybe you could walk me through how the unit economics for rewarded UA differ from traditional in-game app install campaigns. We talk about the data flow, the ability to do personalization. But talk to me like how do the unit economics change when you’re introducing the rewarded aspect and the deeper connectivity.

TH: Well, this is actually where the industry is headed already. So the old model was like the UA channel got paid on the install and the user experience is totally separate. And these days, I think what we all see is that what matters more is like the overall progression. Like Day 7 matters, Day 30 matters, beyond that matters a lot because again in order for the game maker of course to make back their ad spend and to grow their business, they need to see that engagement, that longer-term engagement from players based on their own model.

For us, what Mistplay does is that you know we are in effect sharing the ad revenue that we’re getting from our game players with our players some portion of that as well so that they also benefit. So that’s where rewarded is a little bit different and becomes sort of win-win-win for the advertiser, for the player, and then of course even for the host app as well. They participate in that in the overall unit economics.

ES: Okay and then I think like a good place to end is how do you see the rewarded UA space evolving in the mid-term and maybe I could also just ask for your perspective on how you see mobile gaming evolving in the mid-term. What do you see coming next for rewarded and more broadly the mobile gaming ecosystem?

TH: For the mobile gaming ecosystem, we see rewarded continuing to grow and continuing to be a much larger part of the overall marketing stack. Again you know we’ve seen it over the last five years even where it was single digits as a portion of the overall UA space and it’s now double digits and just continuing to grow. So we’re really excited about it. That’s what we see for the space overall.

And in terms of mobile games, I will say like one thing that I think that the industry is a little bit concerned about actually is AI and is there a lot of slop out there because people are able to create a lot of content and games very, very quickly. It’s something that we also think about a lot in terms of how do you make sure that the games have to be quality back to Sampsa’s point in order to find its audience.

And so for us, what that means is actually we’re often curating the games even on our platform because we want to make sure that they make sense for our players, that they’re actually going to enjoy them and like them and that there’s a really good model behind it. It’s something that we think about a lot, we talk to a lot of our advertisers about and obviously to our players about.

SJ: Yeah, my thought about the industry is what I already mentioned. I think we are going through a very rapid maturation of especially the data and the technologies behind these AI engines and the whole industry.

My non-advertising take here that I would like to share is that I feel like sometimes like this is from the game more like a gaming, I’m a huge gamer still. I play on all sorts of platforms. And I feel like there is at least a little bit of an attempt to blur the lines between mobile gaming and console gaming because looking at something like Steam Deck, I don’t know whether that’s PC gaming or mobile gaming. It blurs the line, it’s something that you can carry around so maybe that becomes a little bit of a competition for what we traditionally mean by mobile gaming. Who knows. I don’t know it’s hard to say whether there’s going to be other games like that, of course mostly Steam games I would think are more hardcore than majority of the mobile games. But I think that’s an interesting thing to look at.

ES: Tricia, Sampsa, I appreciate your time today. I appreciate you both sharing your wisdom. How can people learn more about Mistplay? How can they engage with Mistplay?

TH: Well, thanks for having us on again, Eric. They can find us at Mistplay.com, they can download the iOS or Android app on Google Play or the iOS Store and or we actually again are working with a lot of other host apps and they can also interact with Mistplay there. Probably harder to find, but lots and lots of places.

ES: Or they can come say hi at MAU next year.

TH: Or they can come say hi at MAU next year. Yes. We’re a very global company, so we’re also at ChinaJoy, Tokyo Game Show, and a lot of different places around Europe as well.

ES: Great. Well, thank you both so much. I appreciate your time. Take care.

TH: Thanks, Eric.

SJ: Thank you, Eric.