In this episode of the Naavik Gaming podcast, host Niko Vuori interviews Justin Stolzenberg, co-founder of Metica, a startup aiming to revolutionize gaming analytics through AI-driven insights and personalized experiences.
Founded by ex-King and ex-Apple employees, Metica’s approach is a unique combination of King’s iterative, hyper-data-driven approach and Apple’s high-polish culture. The company recently announced their $9 million seed round. The episode covers the challenges of launching in the saturated analytics market, and how Metica differentiates itself by focusing on actionable insights rather than just data collection. The conversation also explores the role of AI and machine learning in gaming, the importance of personalization, and the future aspirations of Metica in the gaming industry.
We’d also like to thank Heroic Labs for making this episode possible! Thousands of studios have trusted Heroic Labs to help them focus on their games and not worry about gametech or scaling for success. To learn more and reach out, visit https://heroiclabs.com/?utm_source=Naavik&utm_medium=CPC&utm_campaign=Podcast
This transcript is machine-generated, and we apologize for any errors.
Niko: Hello and welcome to the Naavik Gaming Podcast. I'm your host, Niko Vuori, and today we are shining a light on Metica, a startup that's looking to reshape how developers build, analyze, and grow their games. Metica recently announced a 9 million seed round. And if you've only skimmed the headlines, you might think another analytics tool, but the Metica team is positioning.
The company is something far more ambitious, one that blends cutting edge analytics, AI driven insights, and developer friendly platforms and workflows into a unified platform in a world where data is everything. Metica aims to help creators navigate the complexities of user acquisition, monetization, and retention while still living room for the creative spark that makes games truly great.
So, today, I'm joined by Justin Stolzenberg, one of Metica's co-founders. Today's conversation will cover Justin's background, how Metica came to be, the origin story, and why analytics needs a next generation approach in the age of AI. So let's dive in. Justin, welcome to the pod.
Justin: Yeah, thank you. It's really nice to be here and looking forward to our conversation.
Niko: Wonderful. All right. Well, with that, let's dive straight in. So we always start with the background of the founders and the founding team on the ha moment for the foundation of a company. So why don't we start with your background, Justin, as well as your co-founders? I know there's some really interesting backgrounds from Apple and King kind of blending data driven approach with like this, you know, the Apple ethos of beauty and design, and then how Metica itself came to be.
Justin: Yeah. So my own background is as a game operator. I got into the industry by complete coincidence, that doesn't matter here, in 2002, and then back in the day in Germany, uh, browser games were becoming a thing. We had a couple of, you know, and I found my way through monetization, analytics, performance, marketing into various publishing roles.
I co founded two companies. Yeah. And the last 11 years have been focused on mobile with companies like Flag games and Phoenix games where I was a founder as well. Now Metica, I would say, at its core, has been around for probably 15 years plus, because it's almost the same team that created two prior startups.
And as you already mentioned, then transitioned through acquisition first into King and later, the second startup, into Apple, but the core mission was always centered around creating growth for game developers through messaging, through personalization and, more and more, more and more modern takes on segmentation.
Niko: Got it. Got it. Okay, and so when did Metica itself actually get founded? It sounds like the team has been together, you know, for many years now. But how about the company itself? When did you guys found the company? I know you just announced the seed round, but sometimes these things get announced much later than they actually happened.
Justin: Yeah, two years ago. And the first probably one and a half years was built on, was focused on building the platform, kind of creating the underlying engine and division. Our approach is very much centered on learning from customers. And so while building out our core team already laced with potential customers and really iterated a couple of times.
Um, and the last nine months were focused on first use cases and working on scaling the platform, scaling the customer base.
Niko: Got it. Okay. Now I mentioned the, in the intro as well, I, and I did not at all mean to be derogatory because analytics is the, you know, the lifeblood of, of almost every startup these days, you know. Without data, you're nothing.
You don't know what you're. You don't know what you don't know, right? So it's really critical. So, but at the same time, the analytic space in gaming in particular is quite saturated, has been quite saturated for a long time. Yes, new startups pop up. For example, in our company, we're using post hug for the first time.
We used amplitude in the past. We've used a mixed panel, like all kinds of things that Zynga when I Analytics tools actually weren't very common. Early Zynga, you know, Zynga famously built their own stack called Z track. But, but today, fast forward to today, it's, it's pretty well saturated, lots of tools that track user funnels, LTV, you know, retention engagement, specifically for, for gaming.
So what gap are you guys going after here? You and your co founders that's kind of positioning Metica for the next level solution. Obviously you raised 9 million seed round. We're going to get to that in a second. So clearly your investors believe pretty heavily in what your vision is. So tell us about what that vision is and what gaps are you filling in the market?
Justin: Yeah. If I made it, we look at a different part of the analytics stack. We don't want to be yet another dashboard because you're right. There are many, many really good solutions for that already. But if you're a product manager, and as I said, I worked in that space for many years, it is then still quite a big task to take those insights and, or take, take that's Data, take the pure observation, generate actual insights, and then take action.
And Metica focuses on shortcutting that part of the equation. We're basically taking the raw data game feed, enriching that with data that we can take from the networks and from the app stores to have additional information where a user comes from, et cetera. And then basically provide the game with segmentation on steroids. So really action oriented. What player should see an ad or an IP offer? What level of difficulty should a player experience? What life operations events should be delivered? And all, looking not at this, this classical rule tree that many of us PMs have constructed our life.
But truly personalizing and most importantly, learning on an ongoing basis. So it's a, an action company. More than analytics company, I would say.
Niko: Interesting. Okay. And what kinds of developers are you targeting with your solution? What you're describing sounds amazing, but you know, early stage games company that has a small number of users, you know, that's Segmentation overkill, you know, trying to figure out, plus you need the features to say, okay, I'm going to serve you an ad and I'm going to serve you an IAP offer that's 50 percent off and I'm going to serve you an IAP offer that's 100%.
Like, yes, that's the holy grail of personalization. Every game company seeks that, but usually when they get to scale. So, you know, is it fair to say you're targeting later stage, companies, gaming, gaming studios, or is your solution something that can scale down essentially? I don't mean down, but, you know, scale to an earlier stage company without feeling like it's overkill, without feeling like it's too much.
Justin: I think you're hitting on a key point because all things, AI, machine learning, whatever you want to call it, certainly need a certain number of statistics. And if you're in soft launch, you're buying 500 users a day, then let's not talk about personalization. I think the sweet spot for us, of course, we work with a couple of very large customers, but the sweet spot for us, the game is almost ready to scale maybe has already 30, or so, but it's looking for a 10 X, 20 X or so growth.
What very often happens probably you, as well as I did many times as you. Spent a lot of time in that time period to try and find the optimal treatments. You set up many, many A B tests and these rule based segmentations, and you tweak everything, but in reality, if you 10x your traffic after all, you would have to go back and retest everything.
And there, a lot of time is wasted. A lot of energy is wasted on what we call one size fits non treatments that come out of such AP tests cascades. So really looking to address is that when developers see a, a fundamental product market fit, To help them accelerate through, instead of setting up many, many tests and then choosing one or two variants, how about your instrument, a machine that can deliver variants intelligently over time and so scale comes as a, a kind of byproduct to some degree it is a requirement for certain use cases. We always recommend developers not to start with. Crazy late game IP personalization theory, because for that you need a lot of traffic, but if you look at some of the use cases I mentioned earlier, difficulty, you have so many gameplay sessions, you easily reach the statistics, even with a game that has 30, in a kind of early launch phase.
Niko: Got it. Got it. Okay. All AI and machine learning part here. Now, obviously, we all know AI is. You know, all you got to do is put AI in your pitch deck and you've got yourself, you know, a nice seed round led by Andreessen or, you know, some other top firm. And you know, 80, maybe 80 percent of that is, is hype. 20 percent is absolutely, you know, absolutely cutting edge stuff and it's going to change our lives in many ways. So let's talk about what you guys are doing specifically with AI. What are you doing with AI machine learning? How does it work under the hood to deliver all this personalization and this kind of smart learning, I guess, algorithms that are helping to guide the user into the right direction, the right difficulty, the right IAP package, the right at the right time.
Justin: Yeah. Kind of goes back to the journey of our core team. I mentioned earlier that our first son and that was in the, was just taking off. And after a few years there, it hit its peak. It was something like 250 million DAU. And at that time, heavily segmented the permutations multiplied to tens of thousands of different segments that in the end, nobody could manage anymore.
Nobody knew what it delivered to anybody and probably a singer in your experience.
Niko: Yeah.
Justin: What we learned there is how powerful, but also how unscalable manual segmentation, rule based segmentation would be. And fortunately, just a few years before that, on the advertising side, Yahoo and, I believe two years later, Google published papers on a new approach to eventually recommendations or segmentation systems.
And that is the same approach we use as well. It's a family of, um, of techniques called contextual multi armed bandits that you could basically describe as an, as an online learning system. So it, takes into account not only kind of static inputs, like what the user acquisition source, the user comes from or how much memory their device has, but constantly retrains and constantly reacts to gameplay patterns.
Of course, purchase patterns is somebody actually watching ads or not. What is the CPM that you get for their? That takes these many, many, many permutations and then derives a personal preference from it. Now, it's not something that we invented. We just apply it. And the team did this at incredible scale during the time at Apple.
But it's a very, very proven approach that, to our knowledge, in gaming, almost nobody is using at the moment.
Niko: Interesting. Interesting. Can you repeat that multi armed bandit thing? Because that's a phrase I'm going to try and remember for the rest of this episode.
Justin: It's the contextual multi armed bandit.
Niko: Contextual multi armed bandit. All right. That's a phrase I've never heard before. I've heard of the one armed bandit and I worked in social casino slots for a long time and we actually had a company acquired there. So I, I know what a one armed bandit is, but I did not want to know what a contextual multi armed bandit is.
Tell us a little bit more about what it actually does. Cause I'm super curious about, about that aspect. If it's unique to gaming and to segmentation, definitely curious to hear a little bit more about that. Go under the hood one level deeper.
Justin: Yeah. So we also have technical people in the team that are way better at explaining that than I am.
Niko: That's why I'm not technical either. And I think most of our audience isn't super technical, you know, executives. So, so explain it like a five year old, right. Which is where my level probably is right now.
Justin: It's basically, um, a system that can estimate probabilities of a certain variant achieving a certain outcome.
And so that's the, at its core purpose of a multi armed bandit. So like in your slot machine, that's, I believe, actually where the picture comes from. It has multiple arms.
Niko: Yeah. It has multiple arms. Yeah.
Justin: Learns over time. And the piece that, makes it really interesting for these use cases here is the contextual aspect, because it learns not one set of probabilities across its variants.
But it learns this for every player context, their context here, as I said, continue Incorporating things that a player comes with. If I install on my fancy new iPhone 16, then a lot of people and a lot of segmentation trees will place me into the high value bucket. But our contextual multi armed bandit can then very quickly learn that I'm super stingy, or I'm just not interested in paying because I visit the shop 25 times.
And the only thing I ever do is claim the free packages. Human would really struggle to reflect that quickly enough in a rule based segmentation tree. But that's where machine learning excels if you have significant statistics. So fundamentally how it works is that each variant is assigned a probability.
In a certain context, this machine retrains in our case once per day with all the latest data and can be created in less than 200 milliseconds to return any form of decision that you want can be the difficulty can be the price of an offer. Show an ad, show an offer, can be related to engagement at Live Ops as well.
Niko: I mean, this, honestly, this sounds very exciting to me. I'm going to have to hit you up afterwards to see if Metica is a good fit for what I'm doing at this moment in time. But I mean, that's literally the holy grail, you know, what game developers are trying to get to. It's been, like, ever since my early Zynga days, like, we talked about personalization.
We talked about segmentation. We did a lot of A B testing, obviously, but it was very manual, like you describe, and I think it still is to this day fairly manual. Like, yes, there's more tools. There's more analytics packages that can help you parse the data, but you still need a human being to have a thesis around, like, Okay, I wonder what happens if X, Y and Z person is put into this bucket or versus that bucket.
So this is this is very fascinating to me. Kind of a Not just an intellectual level or as a podcast host level, but as an actual developer myself, okay. And if I'm one of them you may.
Justin: Because you're, you're, I think hitting on the key point, a lot of. Energy for product managers is spent on kind of monkey work.
And what we want is to elevate and kind of free up all that, capability and focus on the actually interesting things like what are interesting variants. It's, I think it's similar to how creative testing and the workflows of UA managers have changed and not by coincidence, because Google and Facebook and all these other networks are using the same family of algorithms for their creative optimism.
That's where it actually comes from, as I mentioned earlier. So instead of minuscule campaign setups nowadays, you have a lot of free time that then as a manager, you can spend on coming up with crazy new creative idea. Completely different audience strategies, et cetera, and that's. Basically what we envision for the end up as well.
Niko: Fascinating. Really fascinating. Okay. One of the things that I found really interesting about the background of the founding team is this, you know, King meets Apple culture. King, of course, famous for being, you know, hyper data driven, obviously massive scale in terms of, you know, gamers like candy crush, what did you say?
Quarter billion DAU. At peak, or was it even higher? I can't even remember what those numbers like crazy numbers, right? And very iterative and, you know, level after level after level, like, you know, hyper optimized. And then Apple. Yes, they obviously have that as well these days, but they're more famous for the high polish.
Like, we'll take our time. Like, you know, we know what the customer wants before the customer wants it. Like we will, we will decide what the iPhone looks like. And, you know, not Apple. Yeah. The market research or anything like that. Um, so I'm curious to hear how, how do those two cultures mesh at Metica? You know, which obviously you're an analytics platform.
So yes, I get the King part. Where does the Apple high polish, high vision, high conviction, you know, culture come in.
Justin: I like to think that our platform is beautifully designed and quality standards as well. And so far, that's the customer feedback as well. But it's really probably important to differentiate between apple hardware, and that's where the issue about comes from a little bit.
And apple server for our team. So I don't think it's my place to speak about the differences very much, so I'd rather kind of focus on the similarity a little bit because there's a very consistent learning from both of these places. And that's the, the building for scale aspect and I would really say that in gaming, because nobody, even the most experienced game makers, nobody can predict zeitgeist and know whether a game you kind of have to be ready.
And that's fundamentally what we want to bring to game developers instrumented in a way that if you hit 250, you will, we, we will be capable of going all the way with you and delivering the same kind of real time decision engine that, that you have, if you have 50 KDAU, when you start your journey with us.
So engineering quality and engineering for scale is very much at the core and having solutions that scale both in terms of processes and the underlying engine.
Niko: And I'm pretty sure my next question was worth heading into this. I'm pretty sure that, you know, raising a nine million seed round, it helps to have King and Apple and a prior acquisition, prior acquisitions under your belt.
But nonetheless, you know, nine million seed round for, you know, what is and again, I mean this in the nicest possible way, because I'm super fascinated. And yet another air quotes here. If you're listening and not watching on YouTube, yet another analytics tool or analytics platform must have been at least a little bit challenging.
Can you tell us a little bit about the kind of the fundraising journey? What are those funds going to? Um, you know, how are you going to scale? Where are you at right now as a company in terms of size and whatever you're comfortable sharing?
Justin: , So I think next to the it? Technical approach that we take that unlocks a lot of scalability and a lot of value previously achieved by in house built solutions.
The second thing that is quite unique to us that we look at only in game optimization, but holistically at, today we have the in app personalization side and we have a targetable signal that we give back to Facebook and Google on the same data feed. I'm so already serving both use acquisition teams and monetization teams and that allows us to have a very different footprint inside gaming organizations compared to kind of single purpose or more narrow analytics suites or I'm not ready to talk about just yet what we're going to do beyond that, but basically doubles down on this thesis that growth needs to quickly that you need to, as we call it, basically close the growth loop.
The more higher your scalability, the better users you bring, the better your kind of continuous optimization, like our ambition is not to be an analytics tool, but to, to basically own the category of AI driven growth for gaming.
Niko: Like the sound of that growth, growth is on my mind as well. I'm my own company here.
So you've been in kind of stealth you're, I'm almost certain you're not going to share the names of the companies that you're working with but I'm gonna ask anyway, I wouldn't be doing my job otherwise. What are you doing right now in terms of testing, right? Like you're clearly coming out here fairly confident, you know, want to make some news.
You put out your press release and last month, I think, or just like a few weeks ago announcing that I million rays. And of course, you've been around for a couple of years. So typically, as a founder myself, that that tells me that you're, you're fairly confident you're ready to kind of come and do the next phase or the next step.
What have you been doing up until this point? Who have you been working with any names? You can share scale of the companies that you're working with that you can share. And what have you learned during this period over the last couple of years of testing the product?
Justin: Yeah, we're still very careful in terms of not giving away too much because we feel it's an extremely exciting opportunity.
And we have a particular angle that we. that we don't feel ready to give away just yet. Majority of the time since founding the company was really focused at scalability into the underlying engine. And then, as I mentioned earlier, the last nine months, uh, we spent on applying the technology.
There are a couple of challenges that I absolutely happily share, that we, that we discussed. Way, unfortunately, so for the most part, and that's particularly related to kind of learning personalization to some degree. The, the simplest thing as a product manager, if you set up, set up any test, you have your high level monitoring and you look at it probably too frequently.
But in the end, you don't need to upfront think a lot. Yeah. About constraining the metric set that you look at, you can do that afterwards. Whereas if you want to use a real time learning system, you need to be with the metric you put in. It's again, like, like in marketing, if you tell Facebook, you will get installs.
Whereas if you tell it you want value, you get value. And those users are completely different. And so in the same way, a contextual multi armed bandit is a system that You need to think carefully what to optimize for. I think one extreme example of our favorite use cases is personalizing the duration between interstitials.
Because that's something that has a very, very large impact on retention, engagement, and monetization. But at the same time, it's completely different depending on the type of player. Now, if you optimize for playtime, if you tell the machine, go optimize for playtime because you think that there will be Predictable rate of ad revenue if the user just plays more than most likely the outcome you get is that few interstitials will be shown and that might hurt ad revenue and so you need to construct.
Metrics that balance these things and our system allows you to have primary, to take into account monetization and retention engagement. So it sounds extremely simple, but you can go incredibly wrong by defining the wrong success metric. So it was one very big learning and we messed up a couple of times.
Another typical pattern that we learned about is around wanting too much, because it sounds so tempting once you have this machine to go ultra granular with something like fully bundles, where every single offer that is shown has different pieces of content and completely different prices.
But that has many, many issues. First of all, it requires quite a lot of work to instrument your game in a way that it can actually deliver such content fully dynamic second that requires tons of users, certainly more than 50 KDA. And third, it can also create a weird user experience if nothing is consistent anymore.
And so what we learned is that it's much more useful to start step by step. Um, don't expect that your game is right away kind of personalization ready, but take use cases, ideally experiments that. If you already ran in the past, but just with one of our pilot customers completed a re-instrumentation of something they tested in a traditional way earlier, where they had looked at the balance between IAP and rewarded video, and in their test yielded a negative 15 percent revenue effect now rerunning pretty much the same setup, but allowing the system to decide which of the answer to which player, we now yielded a plus 12%. And why is that nice? Not only because the revenue difference, but most importantly, the concept was already really well understood. It was instrumented everywhere. And so it's a, it's an easy thing to implement. And so I think really the category of personalization needs to be learned to some degree.
And that's the phase we're in. Want to spend a lot of time on understanding which use cases work and how do they work to then be able to. Help developers kind of phase in or, or ramp up into this experience and not be burned by wanting too much and then burning out too quickly.
Niko: Hmm, interesting.
Are there, I mean, to the extent that you can share, and, and again, I, I, I'm getting the sense that I may not get the answer to this, but, you know, how many pilot customers. Are you working with? Are there particular genres that are working particularly well? I mean, you've obviously mentioned rewarded video I. P. ads. It sounds to me if I'm reading between the lines, these might be kind of casual puzzle-ish kind of games. I may even surmise that given your king background, maybe king might be a pilot customer again. You're not going to confirm or deny. And if you're watching on YouTube, Justin is keeping a very poker face here. But I, I'm just curious because one of the things that I, and the reason I bring this up is because from personal experience, like there are certain genres of games, like Zynga poker. I was the GM of Zynga poker and I was the GM of frontier. Well, two very different games.
One is a narrative driven kind of a story, you know, buildables game. You know, invest express is what we used to call it there. And then Zynga poker is poker, right? Like, and, and there are two very different games. They both had big scale. They both made lots of money. And we both, you know, on both of them, we ran lots and lots of AB tests, but it was way easier to do it on Zynga poker because like the mechanics of poker are really straightforward.
Whereas when you introduce a quest versus a buildable versus like a consumable versus in aesthetic item in Frontierville, like they all have very different behaviors, right? And so the reason I'm asking this question is because are there genres that are just working phenomenally well? And then others where you're like, Oh, we're not there yet.
And did you choose them by design? Right? So to the extent you can share, I do think our, our, our listeners and our audience is You know, they're, they're quite sophisticated. They're games professionals. They're going to be really interested to know, like, is this for them? Or is this like a one size fits all kind of thing?
My guess is it's not the latter, but my guess is that it could be more than just, just a single category of, of gaming.
Justin: So we spend a couple of different, we have clients in social casino with one client in the kind of strategy space a couple of deeper puzzle games and the kind of merge merge type games.
But then the majority of our use cases at the moment is on the casual partial spectrum. So, sorting style. Yes, it's absolutely easier because there is, for example, and you scale it up and down instead of having to personalize a complete loop, which just requires more, more effort. But to me, it's really about gradually ramping up.
So we typically start with use cases that are straightforward. For example, if there are five different rewarded video placements in the game, well, toggle each one separately. Or allow each one of them separately to be toggled, and that can have a double digit impact on your total revenue because you'll reduce the cannibalization risk, and at the same time can allow players who really want to watch rewarded videos to watch more.
And everything that touches economy and that core gameplay experience requires additional design. Here, Metica is basically a platform that is as good as the use cases that you design on top of them. And I will be honest, I think it takes a while for a game team to get used to what is a useful kind of level of personalization.
So I think monetization use cases are 90 percent of the time the right starting point that graduated, starting with a difficulty use case, but that was because they were instrumented already to scale difficulty with one parameter, basically, and those read great. But everything else starts with monetization and then goes further into engagement and truly personalizes the experience.
Niko: Fascinating. Fascinating. Okay. And that sounds like the right place to start. Obviously, intuitive. That's like, okay, monetization, you know, price points, you know, how often you show ads, things like that. Like, sounds like again, air quotes here and.
Easier place to start than, than gameplay. You've mentioned one developer that's kind of graduated from one use case to another. , Where do you see it going? Like, can you see Metica being a part of your actual, you know, game design process, you know, beyond just like the monetization, the pricing, the interstitials and how frequently things happen, , is it, is it more of a, it sounds like it's more of a revenue PM tool at the moment than a game designer tool, but can you see it going in that direction or am I, am I misreading the road map here?
Justin: No, I can totally see it go in that direction. I believe it will go there with kind of enough experience, enough education, and enough trust and that trust we need to earn. I believe it's much, much easier to earn it with kind of well understood monetization use cases. We, as I mentioned, I have only been working with customers for the last approximately nine months, and so that graduation needs time, but we go into that direction now with our customers, where the basic value proposition for a game designer is how much easier it is to get experimentation right, because you don't need to set up an A B test that wastes a lot of your traffic.
You have much, much quicker turnaround time. So how about you design the boundaries and then throw in four different variants? Of, for example, a life operations event. So yeah, absolutely. I think there's opportunity for modern analytics minded designers to embrace this and multiply their ability to get it right for many different audiences inside their game.
Niko: Yeah. Fascinating. Okay. And a similar question, then it sounds like you're exclusively on mobile right now. Is that correct?
Justin: Mobile games almost. We also have a client who uses us on Roblox because the integration can also be done through the back end. It's a rest API based data integration and use case integration.
But the majority of use cases resonates with mobile developers. And that's also where it happens.
Niko: So that makes sense. So follow on questions to that then is, is are you planning or are you thinking about the road map looking in like PC console, VR, AR web three? Like, you know, there's a gaming happens a lot of places and a lot of form factors, a lot of devices.
Obviously mobile is huge and you know, you've probably got a lot of, a lot of potential customers there before you start to need to think about these other platforms. But curious to hear whether that's part of the original vision. Yeah. You know, do you see yourselves going cross platform, and are there any things that might prevent you from doing so, given, you know, how you guys are set up?
Justin: I think culturally, mobile and PC is closest to, to our vision of how experimentation and personalization, should be part of the game creation process but in terms of a transition from browser to mobile gaming a decade ago, there is a lot that both sides of the aisle could learn in that time period.
And there are still browser games around. And a lot of people are talking about the kind of return of browser games. And I believe in a very similar way, the next generation of console developers, will look to embrace a lot of learnings from, uh, free to play, maybe from PC mobile on how to build engaged communities, how to live operate games.
And an approach to analytics will be very much part of that. I think technically we're ready for that. The biggest roadblock is you. Culture and what is acceptable for players it could very well be that the backlash of hyper personalizing a PC game is much more drastic compared to those of the community aspect because people are more aware.
People are on Reddit on their second screen all the time and then it's beautiful, but it's not necessarily a blocker in terms of experimentation.
Niko: Yeah, that makes sense. I mean, if you're, you know, a creator, influencer, you're streaming, you know, on twitch or whatever, and you're having a very different experience to somebody else's streaming at the same time, like, hey, what's going on here?
Like that thing cost me twice as much as it cost you. Like, I mean, even at the Zynga days, like even pre streaming, like there was nothing like that. But people would complain in the forums like, hey, I saw like you got that item for that much like I paid this much, right? So yeah, that's the risk.
And the challenge, of course, of personalization is, you know, you're seen as a greedy developer, right? And, you know, nobody wants to be seen as a greedy developer. Everybody wants to be seen as a great, you know, game creator. One of the, one of the things that I've seen throughout my career and, and I'm a, before we started talking, I told you like I've been, you know, in the space for a long time and I'm a data driven PM from back in the day at Zynga and been an early adopter of new analytics tools and platforms along the way, you know, Z track at Zynga before many of these tools existed, you know, mix panel at the next one. Then we were earlier consumers of amplitude, which of course grew really big. And now we're on post hoc, which again is a relatively new external and all of them have like different angles that they go for, but what they all have in common is once they take off in the developer community, they really take off, right?
It's, it's hard to imagine a world where a game dev, you know, circa 2013, 14 would have adopted anything other than amplitude, like unless they were a mixed panel. Legacy customer, right? So where I'm going with this is like, you need that developer community, right? You need that word of mouth. You need those developers to be telling each other like, Hey, have you heard of Metica?
Like, oh, my God, like they're a game changer. And then when you're a new developer and you're picking your your stack, right? And you're picking your analytics partner, your tools. They're like, you're gonna go with it. Yeah. Whatever everybody else is telling you to go with, right? So what are you doing in that space?
How are you building that developer community? How are you building that word of mouth? How are you building that trust that Metica is the next gen analytics platform when there are so many to choose from, right? So curious to hear your thoughts on how you're tackling that side is one thing to build a great, beautiful, wonderful product that does really cool things.
But it's another to then build that developer trust and community around it.
Justin: Yeah, definitely. I think that's the underlying motivation why we Spend so much time in, as you call it, a kind of stealth mode where we work with real life customers, but speak very much about because we want to really make sure that we produce great material for people to, to follow in those foot tracks steps.
I think fundamentally. For the majority of the market tools like what Metica enables, are out of reach. And of course, King and Zynga have built these kind of infrastructure platforms and the biggest players in the world have some of that. But if you look at where a lot of the growth comes from on the game creation side, but very few companies are thinking about publishing infrastructure and these kinds of things.
And so what we want to Get right is to not only go out there and say, Hey, look, here's a platform that can do all of these things, but also, how you apply it for certain types of games, if it context, and that requires kind of building out this repository of use case, not only one or two use cases that work that we then.
Publish in great detail. Norwegian is then to basically do a world tour and people and level the playing field to some degree globally.
Niko: What are your next steps again? Going back to the fact that you know, you've just done some, you're on this podcast. You just did your press release around your seed round.
Obviously, you've been on the market for longer than that where do you go next from here? What's, what's the next 1224 months look like in terms of the road map?
Justin: Yeah, we're currently building out, our core team. So scaling talent definitely the, the biggest thread in 2025. Then there's a big initiative that we look to add on the user acquisition side mid of the year, which I'm not ready to announce today but we should announce that in early May, probably.
I would say that the second half is when we switch into fully public mode and really talk about the other things that have worked and how have they worked, what kind of developers can benefit in what way and look for aggressive market footprint.
Niko: All right. Well, I'm excited to see that.
So I know we need to be respectful of your time. You've got kids to get into bed. And so I want to make sure that you do that. I got kids of my own and I, when they stay up late, then the rest of the week sucks. So I know where you're at. But we do have one final question. We ask all of our guests, which is what three games are you playing right now or are you most excited by,
Justin: I think it will fall short because there are you. Yeah. Probably only two games that I play seriously at the moment. One is Civilization VII, because it's—
Niko: No way. Finally, I cannot believe I'm a massive Civilization fan. And that's literally the only thing that I'm like, truly obsessed by right now.
This is VII. And I know, and by the way, I'm a little disappointed in some aspects of it, but sorry, I hate you're the first guest in the three years of doing this, who like literally led with civilization, like, hello, you're my favorite guest.
Justin: All right. Shampoo. So I think, Civilization is my go to game whenever I'm traveling at my laptop and, we'll fight until, until the power gives out.
And then I play color with sword, which is one of these super casual, super relaxing puzzle games. That this whole category, but this one in particular by a company called Bernie games has reached a quality level and it's balancing is look and feel. It's really a different level of quality compared to what a lot of people called inferior products.
And I think very much the market has. Shifted in such a way that this kind of developer making smaller games that are incredibly polished and incredibly well balanced, that's where a lot of growth happens at the moment.
Niko: Yeah, yeah, couldn't agree with you more. Yeah, I'm a very similar gaming pattern.
Actually. It's like I go super deep on Civ VII, Football Managers. Another one of mine. I grew up playing that since 1992. They didn't release one this year, which was super sad, for the first time ever, and then on the flip side, so like super hardcore strategy, like spreadsheet kind of games, you know? And then on the flip side, like I, pick up like random mobile games, you know, like super casual, just like so I can mindlessly flip through them.
And then, of course, all the New York Times games. So anyway, those, those are my kind of go to's all right, well, listen, Justin, it has been an absolute pleasure having on the on the pod. It's been a really interesting, genuinely interesting. I'm very interested in following up afterwards to see we're too early with our company for, you know, the scale that you're talking about, but definitely very interested to just stay in touch and see if Metica is a solution that we could Lean into as well. So thank you for coming on the pod.
Justin: Great. Thank you for having me.
Niko: Awesome. And then, as a final note here, I have some personal news to share. This is my final episode as your host for Naavik. It has been an incredible journey these past three years that I've been hosting this segment of the pod. I've loved sharing all these insights from across the ever evolving landscape of gaming. I've loved meeting so many ambitious founders, innovators who are working in the nooks and crannies of the industry, trying to create new things, trying to make the space better for, for everyone. And it's been a privilege to meet so many of you and share your stories on this podcast.
The reason I'm retiring my podcast mic and headphones is not because I don't love talking to all these amazing people, but because I'm a founder myself and I'm at a point now where the day to day demands of my job have gotten to a point that I need to dedicate all of my time to them. So I wanted to say a quick heartfelt thanks to our Aaron and Manyu, who are the founders of Naavik for giving me the opportunity and trust me with the mic having no experience whatsoever three years ago, huge gratitude as well to my co-host Alex and David, my web three partner in crime, Devin and to the entire production team that edits and produces the show week in, week out. You're the reason this podcast keeps running so smoothly, and it has been a real joy to work with each and every single one of you. And to all of you listening, thank you for joining me on this ride. Thank you for joining Naavik on this ride. Your feedback, questions, encouragement have fueled countless conversations on this podcast and have been the inspiration for many, many episodes.
I'm excited to see where the Naavik Gaming Podcast heads next. So in true Naavik fashion, stay curious, keep on gaming and keep asking the tough questions. It's been a genuine honor. Signing off one last time. I'm Niko Vuori. See you out there in the gaming universe. Don't be a stranger.
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Again, that is www.naavik.co. Thanks for listening and we'll catch you in the next episode.
