S07, E24: Understanding rewarded user acquisition (with Tricia Han and Sampsa Jaatinen)

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Welcome to the Mobile Dev Memo podcast. This is your host, Eric Seufert, and I'm joined today by Trisha Han and Sams Yat in. Trisha, Sams, welcome.
Thanks, Eric. It's great to be here.

Hey, Eric. Good to be here. Thank you for the invite.
Well, you're very welcome, Sams. I've known you for eternity. Trisha, we met more recently. I'm very excited to talk about Mistplay today and the rewarded UA space more generally. It's really fascinating space that I've wanted to do a podcast episode on for some time. So, before we dive into that, maybe you both could introduce yourselves. So, Trisha, we'll start with you.
Absolutely. So, I'm Trisha Han. I'm the CEO of Mistplay. And Eric, probably the reason you and I have not 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. So, 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. But, it was pre-iPhone, and it was so early that at the time I actually built a mobile ad serving platform cuz it didn't exist. That's how long ago this was. But, have always really loved mobile apps. Most

recently, I was the CEO of a company called MyFitnessPal. And it is a large-scale mobile app for tracking fitness and nutrition. And the reason I mentioned it is one, it's mobile, it 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, monetization of that, and then there are a lot of behavioral mechanics that come into play as you can imagine because it's really about getting to good health. So, I bring a lot of that over with me and really excited to see how much is transferable actually to the mobile gaming environment.
Given the success of MISTPLAY, apparently a lot. A lot is transferable. Great, thank you. And Samsa?
Hey, yeah. I'm Samsa and I've been in mobile advertising space for a long time. I joined Unity 2014 through the Applifier acquisition. I started the data science machine learning analytics teams for Unity Ads and spent more than decade building the Unity Ads network. But now

more recently, last fall, I joined MISTPLAY. I joined the rewarded space as a chief data and AI officer.
And he's still here. So, that's a good sign.
[laughter]
Yeah. All right. So, I kind of we'd just love to start with anybody in mobile gaming is familiar with MISTPLAY. It's grown at a incredibly rapid clip over the last couple years and it's become like kind of a you know, a major share taker of mobile UA budgets. I can imagine that people maybe outside of mobile gaming and just in the broader digital advertising space maybe less familiar. So, maybe maybe we could just start with an overview of MISTPLAY's business and the rewarded UA model.
Sure. That's That's a great place to start. So, 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. And that's because Misplay actually was one of the pioneers in the play and earn space. They started about 10 years ago

in out of Montreal, Canada. And the way that rewarded works today is it really is about value exchange. And I think maybe the simplest way to talk about it is by using the analogy to loyalty programs and specifically like points programs and airline programs. And so there's a real value exchange between you've got your user, your customer, you've got your your brand and there needs to be some sort of equal exchange for the two to work together. So the way it works for in rewarded is that you have your advertiser who is your game advertiser. They're of course spending ad dollars, they're giving access to their game, and what they're getting in exchange are qualified users. The users, what they're giving, they're giving their time, they're playing the game, and they're getting some rewards. We also have another part of the ecosystem here, now host apps. What they're doing is they're often supplying their audience of players and what they're getting in exchange is engagement of the audience and monetization. And then all of this activity happens on the ecosystem or the platform of Misplay where we are

enabling the matching of these players, whether they're coming in directly through the Misplay app or through our partner host apps, and then matching those up accordingly with game advertisers. And then we enable along the way, sort of the lifetime of the of the user, engagement and recommendations.
Great. And I would want to anchor I think the discussion certainly like, you know, just the kind of growth profile I think would want to anchor that to ATT, right? So I think ATT was was probably a major catalyst for Misplay's growth and you know, please disabuse me of that misapprehension if if I'm wrong there, but but maybe we could just talk about how how Misplay's business has evolved over time and like how it has evolved since ATT and how that just changed the dynamics of UA generally for mobile games.
Yeah, it's obviously a really important topic. We might see it slightly differently. So, ATT was not the reason necessarily that propelled Misplay forward. That being said, it certainly

was a factor in where Misplay started. So, as you know, Eric, ATT what what ended up happening is that Android and companies who are Android first were really beneficiaries of that of ATT going into place just because they were able to still attract players, but the way that they did it or at least the really good ones who were able to scale was with a really a strong opt-in incentive. And so, 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 Misplay 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 to be live on Apple full compliance and really start to find those players for rewarded advertisers.

Right. So, I mean, I guess, you know, historically we had like the Tapjoy's of the world that kind of could only operate on Android under the sort of, you know, restrictions of the App Store developer policies. So, maybe we start there. So, Misplay was historically very strong on Android. So, you you've now rolled out Misplay for iPhone and then you acquired MyChips. What what are the unique hurdles that you're seeing scaling the rewarded ecosystem in iOS under under this kind of new set of rules this different set of rules on Apple?
Yeah, I mean, Apple is just a different ecosystem than Google Play with different rules, not bad, just different. And so, I think it's really important to understand what are the, you know, what does Apple care about? They care a lot about privacy and data, and they care, of course, a a about opt-in consent. Luckily for Misplay, that's always been part of our model and our mechanism. It's It's really interesting. Again, what you know, going back to this idea of value exchange, consumers, as we know, they're willing to trade off a lot of times information for either less friction or for some value on the other

side. And I think that's what Rewarded really taps into. And so, we've always asked for consent for users to be able to understand what game they might like to play and how they play it. And And you know, actually this might be an interesting thing just to talk about in general. This is actually where Rewarded is really different from, let's say, your traditional install campaigns. What Rewarded and what Misplay 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. Uh what they're downloading, but also what they're playing, how long they're playing, what they might be spending in IAP or IAA, when they're churning, for example. And also, what are the things that might motivate them, as well as the rewards that are interesting to them. And that That's actually a really big difference between, again, Rewarded and what I might call a traditional ad network type of model. And so, you know, back to the iOS thing, what's what's been really important is that we are in full compliance and that,

again, we're getting that user to actively say, "Yeah, I want this and I give my consent to to opt in to to this platform." Because I, again, 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.
Right. And to your point, you know, that trade-off can be a lot more abstract or nebulous just with a standard ad network. It's like, "Well, okay, I'll get maybe better ads." So, it's maybe less immediate of a benefit than these rewards that you get through, you know, rewarded UA. So, so I'm sorry. I actually I'd love to get your thoughts on the operating environment just cuz you know coming from Unity, you know, the sort of more traditional a more traditional gaming UA ad network ad network and moving over to Misplay. You joined Misplay before it started operating on iOS, right? I mean, you maybe like 6 months or a year before. I just love to hear like what what your experience has been like seeing that come to life and and and just the different operating norms, the different operating realities for like a rewarded

UA network.
Yeah, so that's 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 the actual user and the play person who plays the games is also taken into account as a party who has needs or motivations and things like that. So, it's a meaningful change. It's something that's very interesting. It looks to me like this the because of this relationship that we have with the consumers and the ability to ask for their consent, ability to offer something really meaningful back so that people understand what they are giving and what they are getting against that consent, that data that that they allow us to collect. The difference between the two environments seems smaller than than for the traditional ad network cuz this is

something that at Unity, for example, and I believe this is true for all the all the ad networks where the consent mechanism is completely different and we do know the difference in in value for machine learning when people either can be followed across the applications versus not. So, the 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.
Were there any sort of like scale challenges that you didn't expect coming into Misplay just having come from the more traditional ad network space or or opportunities, things that surprised you, things that you just couldn't have predicted?
Not really surprises cuz this was known to me, but there is a massive difference of course in the owner operated inventory. It's 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

that Unity we are talking about. Multiple orders of magnitude difference and 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 and as said of course 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. So the None of these were surprises. Maybe Maybe I'll share the funny thing that always when you go to a new place, no matter where you go, people who work there they they 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 cuz they understand that the data Again, the difference is difference is multiple orders of magnitude.

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Trish, just going back to you, just walk me through the acquisition of Mchimp. Maybe explain, you know, what that was and how it fits into the broader strategy.
So, you know, we know ultimately when it comes to businesses like ours, it's actually fairly simple, right? Our customer is the advertiser and there's really just two things that they need. They need ROAS and they need ROAS at scale. And we had, as Miss Layton a

really good job over the course of our history, you know, tens of millions of of downloads, hundreds of millions of reward points, many hundreds of millions of data points. But that being said, we knew that that we could take all of the learning that we had from having our own first-party post-install data and figure out how to apply that for the benefit of larger scale and for these other applications, you know, to build this larger network that we could take all of that, again, feed it back to Sams 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. So, we met the Mchimp team, thought they were fantastic. They really built scale with quality as well as they were really strong in markets where we're also strong, where we thought there was it was very complimentary. They're quite strong in APAC and in Europe. We're quite strong in North America and Europe. And between what they'd built and what we knew what we could apply

specifically from the AI machine learning perspective, that all of a sudden, we have something that's much more interesting for 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, much better job of matching people, of finding people the right intent at the right price, the right scale through our models.
Yeah, and I guess a good segue from that is is the audience network. So, so you launched an audience network in May. Maybe just talk me through that, the strategic impetus, how it's going, like what that provides.
It's going really well. We are deep in Well, let me just say that the Samsung team actually have some really intriguing data from models that'll be that are coming out soon, and this is the basis of a lot of of what we built by putting all of these data pieces together. We've got a bunch of exciting launches that are actually in progress and and globally. What we're able to provide to our advertisers is quality, scale, less friction. And that was the

whole impetus of building this Misplay audience network. You know, I talked 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 different, and of course it takes some time to learn what works in each of these systems, and what are the signals that that not only do you put in, but that can you get out of them. So, our job was really like, how do we deliver more scale at the right price, you know, 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.
Because I remember we were speaking, this was a couple months ago, you mentioned you had like a big announcement in May, and that was like the MAU moment. So, that was that. I I I'm just kind of putting that together now in retrospect.
That's right. MAU was really exciting for us. It's where we announced that we had joined forces with Math and the My Chips product, as well as that we were rolling out the Misplay audience network. And 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 kind of strategic opportunity here.
Yeah, MAU seems to be having like a renaissance. The last time I I think I went 3 years ago, and you know, it just it it because it was this independent show, and then it got acquired, and there was the thought, and I think, you know, this was defensible, that it was, you know, it was acquired by a public company, so they needed to boost the revenue, and there was kind of this noticeable increase in vendors, but everyone who went this year said it was fantastic. So, I'm I'm looking forward to hopefully going next year.
It was really, really great. And you know, one thing I'll add and 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. And the only reason I say that is is you know, we were talking about it internally, because Misplay was one of the very early entrance here, you know, we as a company used to go to MAU, and you would see just a handful of rewarded kind of booths on the floor.

And if you went this year, it was really remarkable to see that how much of the floor was actually devoted to rewarded, and I think that's just a sign that there's a lot of excitement around the category. And I think it's because it's it's really delivering something new and different, and but more importantly is also more proven now for a lot of advertisers. So, you really see that.
Yeah, well, I mean, you know, when we spoke the first time, I I made the case that I thought rewarded was, if, you know, if not the principal factor, certainly a major contributing factor to mobile gaming's rebound back to growth. And, you know, like if you just look at the share of spend for a lot of advertisers, I mean, that must be true. There's just this big hole in in UA budgets that got filled, right? There are, you know,
Absolutely right. Yes. We definitely have clients where 30% of their mobile spend is now in rewarded. And I saw a stat just the other day, some I think there was another industry stat that there are some some advertiser who who are spending as much as 60 to 70% of their spend on rewarded, which is really

remarkable if you think where it was, again, 5 years ago. It was probably like 1 to 2% of their total spend. And so, I think you are seeing this acceleration in the category. A A of that has to do with how rewarded it 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 the to this specific category of UA.
Yeah, yeah, I mean that's that's just connecting back to Samsa's multiple orders of magnitude comment. You just get so much richer. You you just get a richer view of the consumer and you can do a lot more optimization as a result. I actually want to talk I want to talk about that about that because, you know, legacy offer walls were kind of seen to be to deliver low quality traffic and, you know, high levels of churn, right? I mean that's that's just a, you know, I think that was like the kind of legacy view on on those channels. How does your AI engine So, you know, you've you've talked a lot about the AI engine publicly. How does that change the quality and and retention of players compared to you know, let's go like call it legacy

rewarded ad units. Like how Samsa, how does that multiple orders of magnitude really contribute to like, you know, better better cohorts and, you know, better retention?
Yeah, so before I start answering that question, I might get excited about this cuz machine learning and these kind of things are my my jam, so try to keep me contained if it looks like I'm going overboard, but I have a very simplified I like simplifying things as well. So, there's a there's 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. So, when trusting against 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. Cuz 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're offering like 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. And there's a limited amount of time people can put into games, so that it's always competition of that attention. So, that's what I mean by the intention. We don't have that cuz 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 is based on those two other principles, where one is we know that the game itself matters. There's 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 start to I'll I'll mention a little bit about the rewarding as well cuz that's what I mean by the timing matters, as well. Cuz 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 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. So, 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.

Yeah, and I think, you know, structurally with games, one thing that is under appreciated is the opacity for the user when they are engaged in a game because the game that a person's playing and and maybe is monetizing and is unlikely to show them ads, right? That's I mean, a lot of game developers do that. They'll shut ads off for someone if they even seem likely to make a purchase. Well, you wouldn't want to divert them elsewhere and so having that touch point with people while they're engaged in another game is unique because like I you know, I always talk about like you think about like the the visibility you have in your 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. And people usually play one game at a time. And so 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 a maid available,

right? And so I guess that's kind of the unique value prop here is like well you've got the you know like you you mentioned you've got the O&O inventory so they're coming back and you're seeing them even if they are engaged in another game and so you've got that sort of that through line of their behaviors.
That is correct. We see them every now and then cuz they want to come back and 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 on really what's happening with them with the users when they are playing the games.
You would know this I mean just having worked in the in the space for some time but like that that was one of the impediments to doing anything other than contextual ads you know going back you know years is that like if your 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 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 and so that really only left contextual advertising so game to game like building the associations across the game cuz you 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?
You are and of course that goes back even more strongly with ATT that you mentioned cuz when people pop back up somewhere you wouldn't even know if they are the same so now 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 cuz we don't we are not game. We don't want the same thing from the users that go through our system than what our clients want.
Okay, so 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?
We see really good demand in a bunch of industries. I'll say in I think what's really interesting about loyalty play and in particular, we also acquired a company called Connected Rewards. And Connected Rewards had done a really really specifically going into categories like fuel and convenience and QSR. And of course, things like fintech and commerce are are really good opportunities for this kind of rewarded UA. In particular, I would I'll I'll just call out like for example, we work with companies as big as as Chevron. And I don't think that's that's one that you would naturally think of for a gaming reward. But, you know, I think what the folks at Chevron realized was like, you know, back to what Sam said before, how do you introduce an experience that is already something that people are are actively doing that they like to do. And

how do you then is there some opportunity for brand positive brand association and engagement with the brand even if it's not exactly what the brand is known for. And 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. And in terms of for example, even restaurant restaurants another interesting one and 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 introduce this program and kind of let them know that this was an opportunity. And so, you know, again back to the analogy of like what's different between us and other types of ad networks. 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. Like it's very it's very interesting. It's happening 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.
Right and that that totally makes sense. Have you seen uptake for just other non-gaming app categories?
Yep. Yep. Commerce of course always strong. Fintech strong, but these are all evolving and I think 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.
Right. 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, you know, the IAA economy, which should drive CPMs up and you know, that's that's something that just you could turn on. And then the other is is and we're this is a little bit in flux and we're seeing this evolve kind of in

real time and it seems like there's, you know, some new announcement that's hard to parse every week, but it's the fallout from the Epic v Google and Epic v Apple lawsuits where, you know, linkout is permissible and, you know, you're seeing like a surge in D2C revenue. So it just it does feel like those are I think those kind of get both of those get kind of get dismissed as not being meaningful, but I see them both as very meaningful and I see them in concert to be extraordinarily meaningful. Like I mean that that seems like just across across both of those you can imagine I don't know, like 30 to 50% revenue opportunity with like very little fundamental work needed. I that's really just stuff that's like plug and play.
I I agree. I I with you. Again, the industry is so innovative and 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. And so, you know, this is

what gets me super excited about this space and the industry is that 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 think about how do we best serve the advertiser? And again, it might be through integrations with uh 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.
So, I called out rewarded and so every year I do, you know, predictions for mobile gaming and predictions more broadly for like mobile advertising. I called out rewarded in my 2025 predictions, so those are, you know, published on January 1st, 2025. So, this is going back, you know, 18 months. But, I called out rewarded. I said that's one of the reasons that we've seen mobile gaming return to growth. And I gave a presentation around that same time at PGC in London and I said, "Look, I think mobile gaming grows 5 to 10% this year." And it came in around like seven. And that was one of the big, you know, sort of components of the thesis is like 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 channel that on a channel that delivers demonstrable ROAS. Plus, then you're able to I think reducing the commission on the DTC stuff is interesting and certainly there's a benefit to that. But, my sense is like the real value and you know, Sam said this is kind of aligned with what we're talking about is the is the personalization. So, when, you know, just a a a third-party web a web-based an actual 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 the SKUs and and that kind of thing. So, my my sense is like those two things in combination present like a real tailwind for mobile gaming and and I think there's there's real reason to be excited about the category.
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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?
Yeah, 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 in this play environment. It's the It's the units and the gems. And units are the base 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 an element of personalization that goes together with that. The gems are tied to They are the secondary special currency that that is related to making IAP

purchases. It's But there are different surfaces where that changes how those units are accumulated. There are different level tasks. There are different type of special tasks that people can can engage with. And all of these surfaces is a something that we can control in terms of this of course the base accumulation of of the rewards tied to those those achievements and the gameplay progression, but we can always use machine learning to adjust how fast those milestones are achieved or what 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 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 should be rewarded and then the useful like the meaningful outcomes for the advertisers as well. So we see this as a two different types of problems. We do predict things. We do predict those those things like install likelihoods. We do predict churn likelihood. We want to understand when the engagement in the specific game is declining. What are those culmination points and trying to understand them so that we know how to react.
[gasps]
But we also see this as a closed control feedback problem. So we look at the rewarding per se itself by the beta as a reinforcement learning problem. Cuz 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? So, 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.
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 are 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." So, that's like one interesting thing. But, you know, when I think back to even working for for in the health side, there is a lot to, you know, 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. And that's what we spend a lot of time thinking about the segmentation, what what really is

important for each of these players, and and what are they looking to get out of it, cuz really different, as you can imagine.
And all in all, I think we are going through maturization 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 we believe that this is something that's going to be true for for rewarded space as well and obviously we want to be the OG's for building the AI engines for these purposes as well.
Yeah, I think the point about you know consumer expectation of just like loyalty programs reward programs is a is a really salient one. You know, if you think about a lot of the arguments in favor of like Web3 it was like well people want to have ownership of these assets that they're buying and I think that proved to like not really be that compelling but like maybe it you know, I'm I'm a consumer I'm spending money on a consumer product I expect to get some kind of benefits of participation over time and like that does sort of track with my you know, my usage right and that that that does seem like yeah,

that's that's pretty pervasive across the consumer economy. Why does it not exist in the app economy?
And you know, to your 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 like, you know, 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.
Yeah, and you know, there were I don't know how many attempts at like you know, TikTok for games discovery like you can have get an app and or like you know, Tinder I've seen a bunch of these where you hop on and you swipe left or right. Yeah, I don't know which I don't I never used Tinder. I don't know which corresponds to liking or disliking but but that there were these attempts at like incentivizing or like

of of 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 that just there needs to be incentivized in some way and and just having you know, another surface area for discovering a game is probably not that compelling unless they get something in return.
Yeah, but what I mean 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, the AI to do this at scale in a personalized way to be effective.
So I'm 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. So we we talk about the the sort of data flow, you know, you know, the ability to do personalization. But talk to me like how how do the unit economics change when you're when you're introducing the the rewarded aspect and and the deeper connectivity?
Well, this is actually where the industry is headed, I think already. So the old model was like the UA channel got paid on the install and right 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 seven matters, day 30 matters, beyond that matters a lot because again, in order for the game maker, of course, to make back their 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 Misplay does is that, you know, we are in effect sharing the ad revenue that we're getting from our game players with our players, right? Some portion of that as well. So 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.
Okay, and I think like it's a good place to end is is how do you see the rewarded UA space evolving in the mid-term? And maybe I could also, you know, just ask for your perspective on how you see mobile gaming evolving in the mid-term. Like what do you see coming next for rewarded and more broadly the mobile gaming ecosystem?

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 spend has now double-digits and 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 that I think that the industry is a little bit concerned about actually is AI, right? And is there a lot of slap out there because people are able to create a lot of content and games very very quickly. You know, it's something that we also think about a lot in terms of how do you make sure that that the games have to be quality back to Samsung's point in order to find its audience. And so, for us, what that means is actually we're often curating uh the games even on our platform because we want to make sure that they make sense for our players and they're actually going to enjoy them and like them and that there's a really good model behind it. You know, it's something that we think about a lot. We talk to a lot of

our our advertisers about and obviously to our players about.
Yeah, my my thought about the industry is what I already mentioned. I think we are going through a very rapid maturization of 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 more like a gaming I I'm a huge gamer still. I 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 and console gaming as looking at something like 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 I don't 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.
Treasure, Samsung, I appreciate your time today. I appreciate you both sharing your wisdom. How can people learn more about Misplay? How can they engage with Misplay?
Well, thanks for having us on again, Eric. They can find us at misplay.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 Misplay there. Probably harder find, but lots and lots of places.
Or they can come say hi to MAU x.
Or they can come say hi at MAU. Yes. We're a very global company, so we're also at ChinaJoy and Tokyo Game Show and a lot of different places around Europe as well.
Great. Well, thank you both so much. I appreciate your time. Take care.
Thanks, Eric.
Thank you, Eric.