The Art of Scaling Games: When to scale your game?

Speaker 1 Essentially, once you plug all of that core data in, we'll just tell you like where are you in terms of fundability, and then we'll break it down in terms of like why, why, what, what, what key indicators tell us, give us confidence.

Speaker 1 This is one that's unreleased.

Speaker 1 This is a debut for the Two and a Half Gamers podcast, but our benchmarking, our benchmarking tool.

Speaker 1 So, like I said, we've got a bunch of, I think right now, maybe like over

Speaker 1 over 200 or 300 cores for 2024 that we've looked at, like across all these different games.

Speaker 1 It's 4 a.m. and we're rolling the dice.
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Speaker 1 We're the two and a half gamers, the midnight crew, talking UA adverts and game design too. Mateish, Felix, Shaku, bringing the insight.
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Speaker 1 Uh-huh.

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Speaker 2 Hello, everybody. Welcome to our special episode.
My name is Matteja Antaric.

Speaker 1 I'm Felix Brauberg.

Speaker 2 And we are your hosts. And we have a special guest, Ritsky from PVX Partners.
Welcome to the show. Can you give us a little bit of introduction about yourself and the company?

Speaker 2 And then we're going to talk about

Speaker 2 what is the topic.

Speaker 1 Yeah, sure. Hi, Matteje Felix.

Speaker 1 It's really great to be on the show. As Matteje mentioned before, my name is Ritsky.
I recently founded, along with my two co-founders, a company called PBX Partners.

Speaker 1 It's a platform trying to help gaming and consumer companies scale. Our flagship product is a credit line that helps developers fund their marketing

Speaker 1 in a way that is very flexible to help them scale and is also risk participative in the downside case where everything goes wrong and the campaign fails. So

Speaker 1 I've spent the last 12 years working in a mixture of marketing and finance roles, most recently at the Indian real money gaming company called Mobile Perimeter League or MPL, where I focused on international growth and corporate development.

Speaker 1 Actually, Matie, I think we met for the first time when I was working there, and we were doing diligence on a potential target together. So it's good to have it come full circle.

Speaker 1 Exactly.

Speaker 2 Nice. Okay.
Good. So before we go into the topic, okay, let's talk about it.
The topic is when to scale your game or when is it the right time to scale your game?

Speaker 2 Because this topic and this question comes up a lot in the different discussions we talk about it on the podcast when we're reviewing uh different games

Speaker 2 and uh i well i have an answer which is a little bit vague but kind of works because i i was i am in the gaming industry for 11 years i kind of when i see the data i know

Speaker 2 what to expect let's say and i'm looking at different kpis but what are the kpis you are looking at ritsuki and how are you kind of working with different companies because i mean it's a i i assume it's a very long and an interesting process

Speaker 1 yeah for sure no i'm happy to opine on this and i know that you and everyone has like you know the key sanity metrics that they they focus on to to kind of give them conviction um to to scale up um i think the way that i will be presenting here is more

Speaker 1 you can call it like high-level picture.

Speaker 1 But I think it's a really important view for any decision maker or capital allocator of the business to understand very intimately before they go and ramp up and spend millions of dollars on U8, right?

Speaker 1 So I can get to how we work in a little bit later. Yeah.
But

Speaker 1 I actually did put together a few simple slides if you don't mind

Speaker 1 going through them.

Speaker 2 Yes, that would be awesome. Because we like visuals, and visuals is that's important and uh people love it as well.

Speaker 1 Yeah, let's let's get you some visuals.

Speaker 2 Nice.

Speaker 1 Let me know if you can see it.

Speaker 2 Yes, all good. We see, we see, we see.
Perfect. This is awesome.

Speaker 1 Yeah. So

Speaker 1 like I said, I prefaced this. This is a high-level, high-level picture.
And

Speaker 1 I hope it's not too basic, but

Speaker 1 we'll ask questions.

Speaker 2 Okay.

Speaker 1 Okay. So

Speaker 1 I thought it would be be good to bring up a familiar case study that you guys covered recently in hexasort by magic tab great episode by the way um so i'm using at magic's you know revenue trend chart here to illustrate the ramp up uh in daily iap revenues but on the episode felix you discovered or you you kind of like brought brought up that calculated

Speaker 1 Yeah, you calculated, you calculated that it was actually like only 30% of the total revenue was being generated by the IAP.

Speaker 1 So that was kind of like the mind-blowing moment where I was like, okay, these these guys are killing it.

Speaker 1 And so

Speaker 1 I think I'm taking a rough estimate of 30% IAP across the timeline. Probably not accurate, but let's just for simplicity's sake, they started off.

Speaker 1 Like the only way to see this is that it's a banger, right?

Speaker 1 So in January 2024, they started with like $10,000 of revenue a day and then ramping up for the next three quarters to half a million dollars a day. And I think looking back,

Speaker 1 like looking back, it's pretty obvious to highlight that this is what everyone wants. But in order to produce this outcome,

Speaker 1 you really need to be in a ready state all the way back in January 2024 to have built the conviction and be financially prepared to scale it in this way.

Speaker 1 So I think another way to frame the question of the day is really, how can you build conviction and be financially prepared to scale your game?

Speaker 2 Yeah, nobody is ready.

Speaker 2 Well, not nobody, but a lot of companies are not ready. And there's, oh, let's scale.

Speaker 2 I had this situation when we discussed, let's scale because it looks great in terms of the ROI, in terms of the numbers,

Speaker 2 CPIs, whatever else.

Speaker 2 And then we start scaling. And then after six months, like, hey, well, we need to scale down because our cash flow is almost dead.

Speaker 2 We don't have money for salaries afterwards.

Speaker 1 I mean,

Speaker 1 the question is, right? Like, everyone can scale, but the issue is scaling profitably, right? Like, that's the problem, right? Like I could scale anything, but you know, if I had a billion dollars.

Speaker 1 Actually, you'd be surprised at how many companies we see that actually are scaling, but then like really shouldn't be scaling at that point in time.

Speaker 1 Or maybe they got a little bit too excited by the early metrics and then they've like rolled that back. But it's really important to kind of look at like

Speaker 1 a common set of metrics that everyone can kind of universally accept as, okay, this is us doing the right thing versus not.

Speaker 1 And obviously it starts with the soft launch, right? When you're in that soft launch phase,

Speaker 1 you know,

Speaker 1 in mobile gaming in particular, you're fortunate enough to have the ability to track, test, and iterate the game like quite quickly.

Speaker 1 So it makes complete sense to take advantage of that and soft launch and then test your acquisition and monetization metrics well before you go out and burn a bunch of money.

Speaker 1 And the goal here, I think, I would argue, is to be able to track your cohort performance and achieve profitability and consistency.

Speaker 1 So during that soft launch period, like your operational team should have quite a long list of like checklists that they should be validating.

Speaker 1 I'm sure you could do a whole podcast on this entire topic.

Speaker 1 But essentially, you've got all the standard sanity checks around economy balancing, retention and monetization benchmarking, like UA marketability testing.

Speaker 1 I'm not an admona expert, Felix, but like I assume you'd look at like viewer rates and like completion rates and impressions per dow

Speaker 1 impressions per dow and ad viewer rates those are the ones yeah yeah so all of these are super critical and you should definitely do the honorable thing in making sure you go through this in like a meticulous manner um but like the outcome we're looking for if all of this goes swimmingly is cohort profitability and consistency like i mentioned

Speaker 1 um

Speaker 2 and here most companies fail because there's like oh wait we don't need to be in soft lunch for six to nine months. Everything is working.
It's like, yeah, well, okay.

Speaker 2 But I would like to see how the courts

Speaker 2 improve over time and progress over time. And

Speaker 2 to have that, I'm then afterwards, I'm able to build a global launch strategy or global launch plan, how much money we want to spend.

Speaker 2 Because then everybody's like, well, tell me what's what should be the payback period we should aim for. I was like, I mean, come on, guys.
Like, this is a discussion

Speaker 2 you should have. And then we look at the data and then we say, oh, look, okay, my bank account looks like this.
We need to get the money back sooner.

Speaker 2 Okay, based on that, I'm able to build a global launch strategy and how much money we should spend.

Speaker 2 Because if like that LTV evolution tells a lot, and if you don't have those cohorts, at least like you are, I mean, five to ten, that's that's ideal scenario.

Speaker 2 You know, companies are not that patient in soft lunch to have this.

Speaker 2 So, yeah, but but yeah, for the soft launch that's um that's um the kind of where should companies are uh aim for

Speaker 1 yeah i think there's a couple things i would also highlight in that soft launch period which are like super critical like one is getting your instrumentation right like ensuring that when you're looking when every like your marketing team your product team the business and management team are looking at the metrics they're looking at the same metrics and that's actually this the source of truth you don't want to be looking at your mediation dashboard or your like your facebook ads manager

Speaker 1 dashboard, and then it's actually the wrong thing.

Speaker 1 And you're optimizing towards different metrics. I think that's super critical.
The other thing is that I think

Speaker 1 if you have enough budget and the luxury of testing, you should test quite broad in like different geos, different channels, and a breadth of creatives as well.

Speaker 1 Because that'll give you a sense of how scalable this can be

Speaker 1 in the immediate next steps. And

Speaker 1 then try to get some benchmarks, I think, is also another one, right? Like back at MPL,

Speaker 1 I would be calling my relationship manager at Meta and like Google and

Speaker 1 trying to get a sense of where the CACs are at.

Speaker 1 And then Sensor Tower for some of the monetization and retention metrics, right?

Speaker 2 Yeah, absolutely.

Speaker 1 Yeah.

Speaker 1 So I wanted to dive into a little bit of the basics,

Speaker 1 if I may,

Speaker 1 and clarify what I mean by cohort profitability.

Speaker 1 So like, if if you take an arbitrary period of time, like a month or week or day, and tagged all of the new users during that period and then measured the lifetime value generated over those users over time, you'll have a bunch of cohorts that you can track and compare.

Speaker 1 And the way that we would recommend recording the value that's generated by them is essentially trying to get as close to cash as you can.

Speaker 1 So whatever the users pay or what you're getting through your IAA revenue minus the processing fees, like platform fees on Google, Apple, Stripe, RevenueCat, wherever you're getting your revenue.

Speaker 1 And then you take this as your net revenue and then

Speaker 1 blend across organic and paid users and then divide it by your marketing dollars.

Speaker 1 I would even argue throw in like the creative costs to the relevant campaigns on there as well, just to make sure you have like a really like fair, conservative number here.

Speaker 1 But essentially, you know, once you do this over time, if your cohort is good, it'll reach 100% net ROAS. And that effectively means you've paid back your marketing investment.
And then the other.

Speaker 1 Just to stop here for a question. Like, Matte, since I work on the admon side, like, out of the clients you've helped in the, what is it, 11 years, how many people actually do this?

Speaker 1 Well,

Speaker 2 not a lot.

Speaker 2 But then they quickly realize you can't look at cross-data because then, oh, wait a second, this is not exactly the money that

Speaker 2 comes to my bank account.

Speaker 2 So, the net raw, and it's easy to

Speaker 2 calculate this based on the platform fees, but then

Speaker 2 there is, like you said, like the cost of creative production, then there is a team, and then there is like a lot of different things.

Speaker 2 And suddenly, it's that you are very far from profitability, and then suddenly you're very surprised that the money that comes into the bank account is not enough.

Speaker 2 Yeah.

Speaker 1 Yeah. And you want to have the clearest picture of whether or not you're profitable or not.
So when you put a dollar in, you're going to get more than a dollar out, right?

Speaker 1 So that's what this curve represents. Once you hit 100% ROAS beyond that, that's your profit margin, right?

Speaker 1 And I think the fundamental thing to understand here is that if you knew for a fact, that your marketing dollars would return.

Speaker 1 Sorry, one other last aspect here is that if if you track this cohort over time and then you track your user your payer retention and that basically goes to zero at some point in time your users churn out completely this asymptotes like horizontally asymptotes towards a figure and we would call that a predicted terminal row as figure so it's important to like there are some tools that um that that can help you that can help you kind of predict this um i know matia you maybe use cohort um they're really good at this we have a tool as well But it's important to kind of estimate where this where this kind of lands up.

Speaker 1 But the fundamental thing to understand here is that if you knew for a fact that your marketing dollars would return a terminal ROAS number quite consistently, then you're essentially acquiring an asset.

Speaker 1 It's similar to like buying a government bond. It pays you an annuity.
like you're acquiring a group of users that will pay you over time and quite predictably.

Speaker 1 So the metagame that all of the the biggest consumer businesses play in corporate finance is stacking as many of these cohorts as possible for as long as possible. Like, that's the name of the game.

Speaker 1 And I think that's quite important to know. That sounds amazing.
What's the error margin on the predicted terminal, Roas?

Speaker 1 It really depends on how much data you have on it, right? Like, so it's

Speaker 1 the larger your sample size, the more you can do. I'll take you through kind of how we do it at PVX later on.
But essentially,

Speaker 1 if you have enough data that correlates to your game, like a certain version of your game,

Speaker 1 and also

Speaker 1 other games in your category or genre, you can kind of build a data science model that does this quite accurately. And if you can do it very accurately, it's very, very useful information.

Speaker 1 So if I asked it a different way, per $100,000 of UA spent, how much does the error margin of the predicted terminal row as decrease?

Speaker 1 That's a great question.

Speaker 1 I don't think it's based on how much you spend. It's based on how many sample sets of cohorts you have.
And there's a trick with this, right?

Speaker 1 The standard cohort kind of duration is a month. But you can technically slice this down to a week, weekly cohort, or a daily cohort, right?

Speaker 1 And suddenly, if you have three, if you've been doing it for a year and you're doing this on a daily basis, you have 365 daily cohorts. Yeah.

Speaker 1 And you can measure the variance and the statistical variance between them and get to a

Speaker 1 pretty accurate predicted terminal ROAS number, I would say. Okay.

Speaker 1 Yeah. Anyway,

Speaker 2 as complicated as it gets.

Speaker 2 This is the volume play, right? So you need to have a certain amount of data to be able to say statistically significantly, like, okay, this is what we are looking at, and this is the

Speaker 2 basically what you can expect, which is pretty normal.

Speaker 1 But PVX partner puts this money where its mouth is, right?

Speaker 1 So, I guess there's a user number or cohort number that you guys are looking for before you're like, hey, I'm quite confident that we're not going to have an error margin over X, basically.

Speaker 1 Yeah.

Speaker 1 So, typically, we like to see businesses with nine to 12 months of data, and we can be quite confident in that. But

Speaker 1 to give a slight correction, we are not in the business of predicting the predicted terminal ROAS because our business, we don't take the upside up all the way, all the way here.

Speaker 1 We just make our, we just, we're betting on you getting to 100% net ROAS and enough money beyond that to pay our interest.

Speaker 1 Right. So there's a margin of safety kind of element here.
Whether you get 180% ROAS versus 140% ROAS makes very little difference from our upside as a business,

Speaker 1 but it makes a lot of difference

Speaker 1 for the company. And we want to make sure that the company is trying to spend optimally so that they can make as much profit as possible.

Speaker 1 Yeah.

Speaker 1 So moving on, like the second thing, as I mentioned, is core profitability, but the other thing is consistency. And this is a really kind of like distilled way to look at it that you can eyeball.

Speaker 1 We're not looking. So the point here is that we're not looking for the latest and greatest cohort.

Speaker 1 We're trying to get comfort on how volatile the future cohort outcomes could be by looking back historically.

Speaker 1 So take, for example, on this left chart, this is one game one, and then the right chart is game two.

Speaker 1 Let's say this top curve is the latest cohort of game one. Like it's the highest profitable cohort amongst the two games.

Speaker 1 But I would much prefer, I would have more conviction in investing in if on the right chart, this top curve was the latest cohort, because there's a lot more consistency in this right chart versus on the left, right?

Speaker 1 So a lot of gaming companies that we deal with, they're like, I've got a banger cohort. I'm ready to scale.
But I would say, hold on one second.

Speaker 1 Let's see whether or not that plays out in a few more cohorts and then whether we can rely on that. Otherwise, it's just going to go wonky and you might lose a lot of money.

Speaker 2 Yeah, because this on the right-hand side is stability, basically. And

Speaker 2 this graph feels like the company or the game knows what they're doing.

Speaker 2 On the left-hand side, it's like, oh, well, we try a million different things and see what sticks. It's like

Speaker 2 it could be random. Also, one good cohort doesn't mean anything.
You need to have, yeah, like multiple

Speaker 2 good cohorts to be able to say, oh, wait a second,

Speaker 2 we have something here.

Speaker 1 How do you link this basically? I guess this question for you, Matte. Like, when you're doing UA and you're always like in our chat group saying, oh, yeah, look at this creative.

Speaker 1 We just got CPIs down by 50%.

Speaker 1 Well, if you have a banger creative, or if you start doing, you know, lying in the creatives,

Speaker 1 which helps a lot, right? How do you get that into this? Because that could drastically reduce it, but it could also be fake information or not repeatable.

Speaker 2 It's misleading.

Speaker 2 It's good for, let's say, five or six months at the best. And then then when the winner creative dies, then, well, you're on the square one, basically.

Speaker 2 So if you have a killer creative, that's a great start.

Speaker 2 But then you need to be able to produce multiple of these, which, yeah, which then is like, that's the pressure on the creative and the UA team to come up with all these ideas and test them. And

Speaker 2 before we scale, and that's what I'm always talking about in the reviews.

Speaker 2 you need to have the creative depth as well multiple different concepts that work across different channels I was in the position

Speaker 2 a few weeks ago, like where we discussed scaling on Applaw In or like starting Apple Win campaigns.

Speaker 2 For this, you can't have only one creative winner because then you start scaling, and then after three weeks, you will see the drop and the decrease in the performance

Speaker 2 and even the spend. So I was pushing for more testing on the creative side to be able to get at least three or four.

Speaker 2 So one works, and then you start refreshing to creatives and just putting this into the campaign. So you prolong the kind of the

Speaker 2 life cycle of the campaign. And that's really important.

Speaker 1 Yeah.

Speaker 1 And I would argue also that like you're

Speaker 1 like that winner or hero kind of campaign or creative, you should always be testing them like in parallel with other new concepts because then you'll identify better like the next one that's going to take over.

Speaker 1 Right. And I think a lot of folks are just super happy with their hero creative and they're like, I'm going to ride this out until it essentially dies.
And then you have no backup or lead lead in.

Speaker 1 It's like wishful thinking, right? Like, yeah.

Speaker 2 No, because people get excited and they're like, oh, wow, this is great. Now, now we should push.

Speaker 2 It's like, yeah, we can push, but not like 100% more or 10x more or whatever slowly, because you don't have the next winner, and we are not testing enough, we're not producing enough.

Speaker 2 So it's not the right time.

Speaker 2 Yeah.

Speaker 1 Another way to look at the consistency one is like if you have enough cohorts, you can take a look at this statistically.

Speaker 1 And essentially, if you take the predictable or the predicted terminal ROAS of each of your cohorts and plot them across a normal distribution curve, like if the curve fits pretty well within a given band of spends, then you might be able to build conviction by taking a look at what the net ROAS would be at negative two standard deviation.

Speaker 1 So back to statistics 101, essentially, at negative two standard deviations from the mean,

Speaker 1 essentially

Speaker 1 98%, if you were to produce another cohort, 98% of the time, it's going to be above the negative two standard deviation mark.

Speaker 1 So if your negative two standard deviation is already profitable, then the next one is probably profitable, right?

Speaker 1 And this is if you have the luxury of sample size.

Speaker 1 And oftentimes at the very beginning, you don't.

Speaker 1 But yeah,

Speaker 1 you can take a look at this

Speaker 1 year after and be like, yeah, I did a great job.

Speaker 1 So I guess the thing is,

Speaker 1 I would urge people to go and figure out how profitable and consistent your cohorts are and

Speaker 1 see how much value you would expect to accrue over the lifetime.

Speaker 1 And if you haven't reached 100% ROAS on any of your cohorts, I think you should be heads down and trying to figure out how to get there before scaling up. Yeah.

Speaker 2 I mean, if your cohorts are not profitable, then I'm not sure if you should spend that much money or money at all. That's like, that's

Speaker 2 the most important part.

Speaker 2 Yeah.

Speaker 1 But going back to like Hexasort,

Speaker 1 like at the inflection point prior to scaling up, essentially this is what they probably saw, right? They were just like, they were probably thinking, I've got good cohort metrics.

Speaker 1 They look consistent. I should try to put more money into this cash printing machine before

Speaker 1 a competitor builds something that will eat into my market share.

Speaker 1 Or CPMs inflate, maybe because of competition, or maybe because the platform itself is just inflating, and making it harder for me to defend my profit margins.

Speaker 1 So, my argument would be that if you've built conviction and

Speaker 1 you are able to try to scale, you should like now is better than later to do that.

Speaker 1 And

Speaker 1 yeah, you never know what else will happen. So, I think at this point, a team should suddenly be hyper-focused at, you know, how can I like like how can I scale further?

Speaker 1 And the first thing I think they're going to ask themselves is, how are they going to fund this growth?

Speaker 1 If

Speaker 1 they don't have it, right?

Speaker 1 Yeah.

Speaker 2 It's usually the UA managers are

Speaker 2 not there. They're like, oh, let's scale.
And then the C-level

Speaker 2 like the C-level people like always, oh, you know what?

Speaker 2 Let's check if we have enough money to actually scale.

Speaker 2 Sometimes people are not business-oriented enough to understand

Speaker 2 there is not an unlimited amount of money on your main account.

Speaker 1 Yeah. And I think it's worthwhile kind of like going in and trying to understand what are the actual sources of capital that are

Speaker 1 reasonable to kind of draw from. So I wanted to just do a very simple, simple kind of like walkthrough of like the common growth strategies to finance growth, right?

Speaker 1 So

Speaker 1 if you're a self-publishing game and you are showing awesome metrics, I would argue that you have three or four options.

Speaker 1 The first option is, like you mentioned,

Speaker 1 how much cash is in my bank and is in your balance sheet, right?

Speaker 1 And this is technically the lowest direct cost of capital.

Speaker 1 But the problem is, as you pointed out, as you you scale up, your payback periods are inevitably also going to be pushed back, right?

Speaker 1 If you're spending $100,000 a month today and you're getting three months' payback, you can anticipate that if you're spending a million dollars, it's going to be more than three months' payback.

Speaker 1 And what this means is that more and more of your

Speaker 1 equity or your balance sheet is going to be tied up in the marketing payback cycle.

Speaker 1 And the best case scenario here is that you do scale up to a million, $10 million a month, but you'll eventually reach a level of spending where it's completely depleted your bank account.

Speaker 1 And by the way, this also means less money for new product development, less money for hiring, less money for strategic initiatives.

Speaker 1 And that's not great for the long-term options for the company as well.

Speaker 2 Yeah, people still

Speaker 2 forget that you spend, the money comes into your account, let's say in three or six months. But then there is also another 45 days from getting the money from Apple and Google, which

Speaker 2 very few people count with. And that's the problematic part.

Speaker 1 Add revenue, net 30, net 60, depending on some networks. Exactly.

Speaker 2 So. Yeah.

Speaker 1 Yeah. There's definitely a working capital kind of like drag over there, but

Speaker 1 it's exacerbated when you're trying to spend double or triple the marketing dollars as well.

Speaker 1 And so a lot of people run to venture capital, right? That's the next one over here.

Speaker 1 And raising equity capital from VCs has a big pro in that the money is not guaranteed back to the investors.

Speaker 1 You take money from invest, from VC, they're not like asking for it back right away. There's no fixed repayment schedule.
It's highly flexible capital.

Speaker 1 And if you have good investors, you know, they might be able to help you in more ways than just capital, which they'll happily do because they're aligned with you on the equity side.

Speaker 1 Um, the issue with VC Capital is that it's dilutive, it's equity dilutive, which means that you now have less ownership in your company and you have new investors to report to. Yeah, um,

Speaker 2 yeah, aka selling your soul a little bit.

Speaker 1 Yeah, I've heard you refer to it that way, but uh, it's okay, selling your soul to people is yeah, that's fine. Yeah, that's fine.
I mean, make

Speaker 1 joking, yeah, I mean, there's also a risk to it, right? Like, if you look at, for example,

Speaker 1 Grand Games is a good example now. They spent six months raising their last round, right?

Speaker 1 And I know from speaking to a lot of CEOs that basically people in the industry took notice because basically their metrics were so good. That was like shooting off a flare gun.

Speaker 1 And I know a lot of companies that we've reviewed have taken a lot of creative liberties and inspiration from that game, right?

Speaker 1 So those six months probably cost it quite much in terms of competitors, I guess. Yeah.
Yeah. It takes time to raise equity capital.
Like, yeah.

Speaker 1 And if you really are gung-ho on doing that, my advice would be to preempt your investors and get them excited about your early metrics earlier on, right?

Speaker 1 Get them, get them, get them hooked before you really need to ramp up.

Speaker 2 Yeah, because that would be the right thing. Yeah, that's already too late to start ramp to start that discussion.

Speaker 2 Yeah.

Speaker 1 The next one is debt, right? So there are a lot of debt instruments, and I think it's

Speaker 1 and you that you can use to explore to fund growth.

Speaker 1 And the biggest, I know it's kind of like a bad word sometimes because a lot of people think of think of it as like kind of a bad thing.

Speaker 1 But I think the biggest benefit here is that debt is a capped instrument, right?

Speaker 1 Let's be clear. Like you don't have to give the lender such a significant amount of your...
of your upside like you would for an equity investor. And the price is agreed upon up front.

Speaker 1 It's usually transparent. Those are all great things, right?

Speaker 1 But the main issue with debt and why people don't really consider it, especially as I've seen in the

Speaker 1 in the

Speaker 1 gaming sector, is it has recourse.

Speaker 1 And what that means is that if you miss a payment, just like your mortgage, and you can go into default, which means they can take your company, like they can take your house or whatever you've decided to secure.

Speaker 1 And that's not like, is that a risk worth taking for you? Like, do you want to go there?

Speaker 1 But yeah, what are your thoughts on that? Well, probably also issuers or debt don't really know how the gaming industry works, right?

Speaker 1 Like having someone explain to them, that's sitting in an office, like, oh, yeah, we had a bad cohort and we changed our payback period from 90 to 180. They don't care.

Speaker 1 Yeah, no chance, no chance they'll understand.

Speaker 1 I don't think they understand what a cohort is, right? No, exactly. Exactly.

Speaker 1 No way.

Speaker 1 Watch any Sopranos episode for like, we'll go down the conversation.

Speaker 1 Yeah.

Speaker 1 But I think there's one thing with debt that a lot of people don't anticipate. A lot of founders don't anticipate the covenants.

Speaker 1 And so if you're not familiar with what covenants are, they're basically conditions or restrictions on the borrower that are designed to help the lender feel good about your financial standing.

Speaker 1 And the most common covenant is like an EBITDA covenant, which is like, hey, you, you can borrow this money, but your EBITDA cannot fall below a certain amount, which is completely paradoxical to the point of growth, right?

Speaker 1 Like going back to my first cohort profitability slide, like if you knew for a fact that your cohort would produce 200% ROAS in two years, who cares if you're

Speaker 1 negative EBITDA this year, if you're going to be 200% the next year, right?

Speaker 1 It's absolutely the right thing to do for the company because you're going to make more money than if you didn't spend that money.

Speaker 1 Sounds so European.

Speaker 1 Yeah, but the bank is not going to see it that way. They're going to see it as you're breaching EBITDA covenants and that

Speaker 1 means that you're not financially stable. And I'm going to pull the plug.

Speaker 1 And finally, we arrive at cohort financing, which is kind of definitely the one that people understand the least and is the least common, I would say.

Speaker 1 So basically, cohort financing is a form of credit that's generally only secured on your cohorts, the cohorts that are being financed.

Speaker 1 So, at PBX, we offer cohort financing for user acquisition. So, the way that it works is

Speaker 1 we would lend, say, like 50% of your marketing budget,

Speaker 1 your monthly marketing budget, and then we would take a 50% net revenue share from the ROAS that it produces until we get our money back and plus a little bit of interest.

Speaker 1 And because it's structured.

Speaker 1 So, okay.

Speaker 1 So, so the the way to think about it is it's about like 10 10 to 14 percent annualized cash cost so let's say if it was 12 for easy math annualized cash cost and your paybacks were three months it would be a three percent cost if it was six month payback it would be six percent cost it depends on how long the cohort actually lasts yeah

Speaker 2 So if yeah, if you make money in one month, it's one percent for you.

Speaker 1 Exactly. Okay.
Exactly. And I can lend you $10 million dollars and it'll be like that one percent

Speaker 2 yeah yeah but then you scale as you scale and we discussed this that yeah your payback prolongs

Speaker 2 and but you're scaling you're spending more money so i mean then you from you go from three months to six months and then you make six percent i mean that's kind of fair yeah i mean

Speaker 1 i guess what you're monetizing here is risk right but just uh for me to understand better like what's the average interest actual cost in percentage terms of your current clients?

Speaker 1 Because I guess it's different. That's more.

Speaker 1 I can give you an average, but it's not a really indicative number because it's I've got clients that pay back in two months, and I've got clients that pay back in 14 months.

Speaker 1 So if I average that out, it's kind of, and especially if you weight the amount of spends, it's going to come up to

Speaker 1 not a very

Speaker 1 curious if you want to shout it out.

Speaker 1 Like maybe five to seven percent, something like that. Yeah.

Speaker 2 Yeah, because look, so you work with different gaming companies and different games and very different uh payback periods.

Speaker 1 There you go, yeah.

Speaker 1 And and what this buys you,

Speaker 1 well, okay, one

Speaker 1 other important thing to say is because it's structured this way,

Speaker 1 it's a non-recourse instrument, which means if the cohort fails, like the cohort never reaches 100%, yeah, let's say it only reaches ever 80, I'm only going to get 50 of 80, yeah, right, and and the company doesn't owe me that remainder 20%.

Speaker 1 They just owe me whatever the cohort produces. So, in that way, we're taking risk alongside the company because

Speaker 1 we're in the cohorts with them.

Speaker 2 And that's why you don't work with everyone because

Speaker 2 you actually, you know, like you want to make money. I mean, you still need to pay bills and you still need to also pay yourself and

Speaker 2 everybody. It's just, that's what people

Speaker 2 don't really understand.

Speaker 1 Sounds like a really good deal because you know the us interest rate is what four and a half right now so if your average is six that's quite good

Speaker 1 yeah and this yeah so like again um if you were comparing us to a bank it's going to be at a premium the interest yeah but that bank is is a recourse product right this is an unsecured product that's that's why you pay that premium and the reason why we frame this as a scaling up product, like a product for a company who's ready to scale, is like a bank is not going going to touch you when you're trying to look for to double or triple your spends, right?

Speaker 1 They think that that's like too unstable. But we're we understand the cohort mass and we want to take that risk with you.

Speaker 1 Do you mind just asking a basic question here? Because you start to understand.

Speaker 1 Like, so basically, if the risk-free rate is four and a half and you're offering six, like, why not use invest it in treasury bonds?

Speaker 1 Take all the risk away.

Speaker 1 Um, well, to be to be to be honest, the fair that that four and a half percent is uh annualized apr right so if you were to annualize that you would compare that to a 12 or the 10 to 14 that i mentioned to you so it does come at a premium yeah doubles in the details there we go yeah

Speaker 1 yeah no i'm not i'm not trying to market myself to be the cheapest instrument but no

Speaker 1 that's that's the fair comparison yeah yeah

Speaker 2 but then for founder yeah there's also i'm i'm pretty sure yeah there's also not only pros but cons and i think what you mentioned is that you need to have a lot of data to be able to actually provide this type of financing.

Speaker 1 Yeah. Yeah.
So typically, like I mentioned, nine to 12 months of data is

Speaker 1 what our like sweet spot is. Yeah.
However, we are getting better

Speaker 1 at modeling early stage cohort, cohort, cohort. So basically, as our database scales, our underwriting database scales, we understand specific genres better.

Speaker 1 Like, for example, we have about like 30 or 40 merge games in our database, and

Speaker 1 I've taken a look at all of their historical core data.

Speaker 1 And

Speaker 1 you get a little bit better at predicting kind of what each one is. And we do like retrospective testing to see whether or not our predictions are correct.

Speaker 1 We're not like perfect there yet, but like, I mean, I wouldn't say that we're at a level where we're there's the confidence level is is high enough. Yeah.

Speaker 1 Like it should definitely be higher than 90% if I can't afford a loss. But

Speaker 1 we will get there as we get more and more data. And because of that, we are launching a new product.
It's called PBX Early, which basically

Speaker 1 can underwrite you with three months of data.

Speaker 1 With only three months of data. Yeah.
What's the ceiling usually in terms of financing that you can go up to or minimum? Because I guess you need to make it worth your time as well, right?

Speaker 1 Minimum and maximum. Yeah, we need to make it worth our time.
And we need the developer or the publisher to

Speaker 1 have tried enough kind of different kinds of campaigns and channels for us to understand the stability better. So typically it's around 150,000 US dollars per month in spends.

Speaker 1 The PDX early product is lower. It'll be like 50,000.

Speaker 1 But our flagship product is about 150,000 minimum spends. We have a very

Speaker 1 a very close relationship with our investor, which is General Catalyst. General Catalyst is a San Francisco-based

Speaker 1 VC fund. And

Speaker 1 we focus on,

Speaker 1 they invest in all sorts of businesses and they typically go for relatively large scale deals because it's a multi-billion dollar fund.

Speaker 1 But we focus, our sweet spot is really like anyone who's spending $2 million a month or less.

Speaker 1 So

Speaker 1 that's the starting range.

Speaker 1 But as they scale to $5 million a month, $10 million, $15 million a month, we collaborate with General Catalyst

Speaker 1 to facilitate them.

Speaker 1 So basically, sky's the limit.

Speaker 1 Yeah,

Speaker 1 they fund companies that are spending

Speaker 1 over

Speaker 1 $20 million a month easily.

Speaker 2 Yeah. Nice.

Speaker 1 Yeah, that's kind of all I had about

Speaker 1 when when i think it's it's appropriate to scale or when it's a good time to scale um but i think you you had also asked like what does the process look like or sorry

Speaker 2 question yes that what like what does the the process look like and how do you actually go from working with companies to

Speaker 2 to fund them and yeah like what are you looking at because

Speaker 2 that's the meat yeah

Speaker 1 yeah like me and me and mati come to you we we're two 20 year olds just out of university and we have a we have a merge game and we're excited.

Speaker 2 Yeah, but yeah, but we are spending 200k per day

Speaker 1 per day

Speaker 1 per month.

Speaker 2 Per day, that would be interesting.

Speaker 1 Yeah, no, so we have like a proprietary intelligence

Speaker 1 like database called Lambda.

Speaker 1 And essentially what this what this does is it basically what we just discussed in terms of cohorts, if you plug in your MMP, like if you use like AppShire or Singular or Adjust or whatever,

Speaker 1 or even if you want to plug in your historical transaction ledgers from an S3 bucket or a GCP bucket, we can import that data onto here and basically visualize all of the cohort information that you would ever want to see.

Speaker 1 So the cohort analysis is

Speaker 1 what we typically look at. So we would plot your data and we would...

Speaker 1 By the way, this is just composite data from a couple of companies that we've taken a look at, like maybe four or five.

Speaker 1 So the numbers might not make a lot of sense. But the curve essentially blurred out for the European users or watchers.

Speaker 1 Okay, okay.

Speaker 1 Okay.

Speaker 1 So this is this composite data shows that like all of these cohorts are kind of projecting towards profitability

Speaker 1 at different different

Speaker 1 payback rates, like between five to nine or eight months. And this is validated.
This is net ROAS. This is validated on their actual transactions and their marketing spends.

Speaker 1 You can see kind of the shorter lines over here are kind of degraded compared to like the longer lines, which means

Speaker 1 there's some cohort degradation and the payback periods are probably going to be longer.

Speaker 1 Another way to kind of look at this is on a month-on-month change basis. So this is basically incremental net ROAS per month.
So at month six, like this is around 10% incremental versus month five.

Speaker 1 And what this means is basically like this thing is printing money like every every month. It's returning 10% even after it pays back,

Speaker 1 which is which is a good sign for your kind of profit margins.

Speaker 1 And you'll see that this kind of asymptotes at a certain level, like usually,

Speaker 1 I mean, this is outstanding actually, but like usually we would say it's good if it if it's above 5% per month, at least for the first several months after they've paid back. Yeah.

Speaker 1 I'm not going to go into all of these details, but basically, this is the marketing spends against the payer CACs.

Speaker 1 Pretty simple graph.

Speaker 1 You know, these are the payback periods, and this is the statistical kind of deviate, like the standard deviations that I was just mentioning before.

Speaker 1 What this means is basically, like, at two standard deviations, it's like 9.5 months payback, which means if you were to do spend at a similar rate, and this had enough data in it,

Speaker 1 you can expect something below a

Speaker 1 9.5 payback period on your next one.

Speaker 1 We take a look at retention metrics. I'm not going to go through all of them, but it's basically like

Speaker 1 net revenue, payer retention, ARPU retention, transaction retention.

Speaker 1 We take a look at the CAC data.

Speaker 1 We look at correlations between

Speaker 1 if you spend more, what is your M1 M3 M6 ROAS look like? If this is relatively flat, that means that there's a lot of inelasticity in how much you can spend.

Speaker 1 So like the more more you spend, it doesn't really change this number, it's a great sign.

Speaker 1 And, but you should be looking at this, you know, ideally at a month six level.

Speaker 1 Um,

Speaker 1 we look at it on a channel basis. So, these are all of the channels on a row, like ROAS per channel.

Speaker 1 A huge grain of salt here, knowing that half of the shit is like iOS and like we don't know how they're attributing. And

Speaker 1 so, like, a huge grain of salt there, I'll admit. Um,

Speaker 1 But like other than channel data, this is interesting.

Speaker 1 If you trust, if I looked at the Android data on this and these were like quartile performance ranges, so like, for example, Adjo gets you like an M1 ROAS at 75th percent or the median at like 14%.

Speaker 1 And somehow Cash Kick is like way better. I don't know if this is actually

Speaker 1 real, really reliable, but it tells you like how the ranges of profitability for each of these on each channel.

Speaker 2 And I will stop you here. Uh both of these are different channels than let's say uploading integral and Facebook and and Google.
They're rewarded U UA channels.

Speaker 2 And obviously those are always higher ROAS on the first months, but then it depends on how it actually evolves over time because you have different rewards in these UA channels and then people churn and then suddenly your LTV projection doesn't really go anywhere.

Speaker 2 And they yeah, exactly makes sense as well. So, yeah, this is yeah, that's why I think what you said on the month six, Roz, and how everything evolves over time, that's really important.

Speaker 1 We see here clearly we're still waiting for Unity to roll out its new ML models.

Speaker 1 Yeah, yeah, yeah. This looks terrible.
I don't know.

Speaker 1 I think this is just dummy data. To be aware, they've announced that they're rolling it out soon.
So everything's good.

Speaker 2 But still, no, this is good because then you see the trends on the marketing channel, which is important. You need to get the context on that as well.
Okay, okay, nice.

Speaker 1 Yeah. And then the last, you get the revenue split

Speaker 1 per channel, which is pretty standard.

Speaker 1 But the revenue split by cohort is also quite interesting. So, like, what you want is what I said, like, you want to stack these cohorts as much as possible.

Speaker 1 So, these like tiny, you know, thin layers, over time, if you have great payer retention, they actually stick around for a long time.

Speaker 1 And then, and then you're able to kind of stack these like really great cohort towers. Um,

Speaker 1 And

Speaker 1 obviously, by platform and by

Speaker 1 monetization type and by geo.

Speaker 1 So, you get all this rich information. And, like I said, what this at least can help you do is try to build that conviction on the cohort, on the cohort analysis before you try to scale up.

Speaker 1 This is free, by the way. So,

Speaker 1 anyone can go and do this and use this.

Speaker 2 Okay, another you build a calculator as well, like how

Speaker 2 you can, I think it's on your website, right? How can you

Speaker 2 actually calculate if you are eligible for funding or like how your cohorts evolve over time? And you can do a lot of different activities on the website that you have there.

Speaker 1 Thank you. I appreciate you.
Might be the one of five people who has ever tried to do that. I really appreciate that.
I think my CPO also really appreciates that.

Speaker 1 But yeah, this is another way to kind of look at it. Essentially, once you plug all of that core data in, we'll just tell you, like, where are you in terms of fundability?

Speaker 1 And then we'll break it down in terms of like why, why, what, what key indicators tell us, give us confidence. This is one that's unreleased.

Speaker 1 This is a debut for the Two and a Half Gamers podcast, but our benchmarking, our benchmarking tool.

Speaker 1 So, like I said, we've got a bunch bunch of, I think right now, maybe like over

Speaker 1 200 or 300 cohorts for 2024 that we've looked at, like across all these different games. And so it's going to narrow down if you narrow it down by

Speaker 1 category and genre. But

Speaker 1 like, for example, this, again, this, this is. demo data, but like if you were to take this as true, your M1, this game compared to other, the game's genre, peer set

Speaker 1 and and category peer set is performing really badly in month month one rowas but for some reason over m3 m6 and m12 it gets better in terms of the percentile range so like the percentile is 61 at m12 but like 15 at m1

Speaker 1 so they must have some kind of retentive retentive capability uh which pushes them this way but Again,

Speaker 1 if I was the CEO of this business, you know, I wouldn't worry too much about the m1 it's a leading metric but what you really care about is that is that ladder ladder kind of like roaze

Speaker 2 yeah people always ask me oh you know these are the numbers is it good is it bad how do we compare against uh the other companies and i always say look

Speaker 2 You need to look at like here, like month one, three, six, twelve. I had um, we had a game, we worked with Yakou on on it, and it was great.
The first seven days with ROAS was like 70%.

Speaker 2 Wow, everybody was like, Oh my god, this is so good. But then the next 30%, it took us 11 months to actually get that back.

Speaker 1 So that's not good.

Speaker 2 Yeah, it's like, that's not really that great.

Speaker 2 So that's why you need more data points to be able to compare like where you stand.

Speaker 1 Actually, sounds like you need more interstitial ads, right?

Speaker 1 Yeah.

Speaker 2 Absolutely.

Speaker 1 Yeah, so I think like like right now we're still a very young company. The database is modest.

Speaker 1 But as we build out and take a look at more companies, this will be a much more rich kind of like source for you to compare against. It's not perfect.
I'm not purporting that, but like

Speaker 1 it's somewhere, right? Like

Speaker 1 I don't have to call my Facebook relationship manager as often if I had access to this

Speaker 1 data.

Speaker 1 You can also see it on a channel basis, again, with a grain of salt. Attribution last-click, seven-day attribution, most of them.
I don't know how it's being done on the SCAD network, to be honest.

Speaker 2 It's Wild West. It's Wild West, away.

Speaker 1 Yeah.

Speaker 1 And

Speaker 1 then some other metrics like payer retention, revenue retention, payback period. So you can really compare.

Speaker 1 Like a lot of people are like, hey, what is a good, you just asked me, like, what's the payback period that you really get? Like, I don't know. This one says six point, you know, median is six.
Yeah.

Speaker 1 Right. So it's a, it's, it's one data point to take a look at.
Um, so this hasn't been rolled out. We will roll it out soon.
Definitely let you know. Nice.
Um,

Speaker 1 and the last one, which uh is going to be rolled out, is basically if you plug your data in and you have limited data, we will pull together our data science model based on the other companies we've seen in your category and genre and your historical data most importantly and forecast uh what the next 12 months on each of these cohorts cohorts look like.

Speaker 1 Eventually, this can help you find that asymptote, that terminal ROAS, predicted ROAS asymptote.

Speaker 1 But as you mentioned, Felix, it takes, you know, the more data you have, the more accurate this will be.

Speaker 1 And this translates directly into your financials. And essentially, for a

Speaker 1 finance person, like at the end of the year, you know, December, they're like, okay, what's your budget? Mate,

Speaker 1 what's our marketing budget, everyone? If you put in your marketing budget, this will plan out the future cohorts, what they'll look like based on your historical performance.

Speaker 1 And you can tell that finance person,

Speaker 1 this is what the revenue every month is going to look like.

Speaker 1 And they can do that planning. So that's the tool that we're, again, this is all for free.

Speaker 1 We hope that it'll be useful. And

Speaker 1 yeah, hopefully we'll be able to see more profit more fundable cohorts. Nice.

Speaker 2 Okay, this, oh my God, this is great. So, how long does it take from, again, like from to go through all of this?

Speaker 2 Like Felix mentioned, we have a great game, we are spending some money, we plugged in the data, now we want to, we want to scale.

Speaker 1 Yeah,

Speaker 1 so if you if you wanted to get cohort financing from from us, yeah, um, this process takes 24 hours, like doing the underwriting and uh and actually spitting out whether you're fundable or not.

Speaker 1 It will, what you don't see over here is what's the price, how much you can, you, you

Speaker 1 we can extend to you in the facility, what's the financing period, and all of that. That will be out in 24, max 48 hours.
And typically after that, and let's say you were fine with

Speaker 1 those terms, usually an agreement will take a minimum two weeks.

Speaker 1 I'll give myself two weeks. And then that month itself, we can fund.
So if you wanted cohort funding, you could technically do it within the same month.

Speaker 2 Yeah, in 30 days.

Speaker 1 I mean, okay. And basically, you send the money in the bank, or does it have to be spent in some way, or is it just money in the bank?

Speaker 1 Money in the bank. Money in the bank.

Speaker 1 You tell me, I want,

Speaker 1 look, I'm spending a million dollars. Give me $500,000.
You get 50% of this. I transfer that directly into your bank.

Speaker 1 The next month, you ask me for another million dollars, but your previous, your first cohort owes me $100,000.

Speaker 1 Then I just net that off. So I send you $900,000 instead of a million.
So that's how how it'll work until, yeah.

Speaker 2 Ooh. Okay.
So

Speaker 2 yeah, nice. I mean, it's great.
So how

Speaker 2 people can contact you and say what we just said, like we have, we have a great game, but we need money.

Speaker 1 Yeah, yeah. I mean, first of all, if you're just more curious about the broad topics, and I'm happy to talk to you, you can just add me on LinkedIn.
I'm Ritzky from PBX.

Speaker 1 But if you're really keen on the financing, just go to our website, www.pvxpartners.com, and there should be a get terms button. And it'll take you through the process real quickly.

Speaker 2 Oh, man. Okay.
So

Speaker 2 we'll also add some notes into the description with the link to the pvxpartners.com as we usually do, and also link to your email and LinkedIn profile as well.

Speaker 1 And anyone who wants to email you, use the subject heading asymptote because we've messed it up. It's the word of the day.
We mentioned it the most.

Speaker 1 Well, I don't know. Like, the last episode I watched from you guys was like,

Speaker 1 why hexagons? Because they're bestagons or whatever.

Speaker 1 So, yeah.

Speaker 2 But

Speaker 1 everyone gets a new word for each episode.

Speaker 1 Exactly.

Speaker 2 Okay. Thanks, Ritski, for coming again.
Thank you very much, guys, for listening.

Speaker 2 If you have any questions, please comment under the YouTube video, it's gonna be uh the visuals there. Join the Slack channel and see you.
See you next time. Thank you very much.

Speaker 1 See you guys. Thanks again, guys.
Thank you.