← The Synopsis
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- [00:00]
Drew Cohen
Foreign.
- [00:07]
Alex
Welcome to the Synopsys, a business and investing podcast for professional, amateur and all investors. I'm going to get that consistent one day, just not this time. And today we have another installment in our dialogue series. We're talking about some fun stuff, but before we get into that, Drew, how you feeling today?
- [00:25]
Drew Cohen
I'm feeling good. We just released our Ferrari report the other day, which is a company, at least last time chucked, is not having any AI AI risk. So you should definitely subscribe and read that one. The stock's down 35% from peak still, though at around 32 times trailing earnings.
- [00:40]
Alex
And bitcoin is down. So all the stodgy, quality investors, you know, who are following Buffett's, you know, advice to not buy commodities of any type or, you know, are very excited about that.
- [00:51]
Drew Cohen
And I, and I won't talk about the smile on Alex's face as he says bitcoin is down as he thinks about how the opportunity cost of owning it has continued to fallen. And he's quite happy about that.
- [01:01]
Alex
Yes, Drew, you are right. I do get a little upset every time I see bitcoin go up and I am mad. I read all of Buffett's investors letters. Sometimes I just want to speculate. You know, I gotta, I gotta resist the urge. I gotta resist the powerful urge. But today we're talking about another trade. And again, I think we covered a lot of this in the core weave episode, but there seems to be a little bit of an, we'll call an unwinding of the AI honeymoon period, perhaps. You saw Amazon. Well, Google announced, I think 160 billion in CapEx spending to only be absolutely trounced by Amazon who wanted just one up Google. I don't know if Jeff Bezos and Larry Page and Sergey Brin are just kind of in this battle. No one's in. But now Jeff's going to spend 200 billion in capex on Amazon. I know next quarter Mark Zuckerberg is going to think they're behind and up it again. I'm sure it seems to just be, I don't know, a measuring of who's got a bigger wallet. But the market did not like that. They didn't like it one bit.
- [01:55]
Drew Cohen
No. And it's very interesting that now the market's kind of reacting negatively to all of this AI spend, whereas I feel like a little bit earlier is kind of reacting positively to that. And so maybe this is a little bit of a shift in sentiment or investors just following on this week's sell off.
- [02:11]
Alex
Yeah, Great point because earlier in the week it was anthropic had released an AI model and I think it was the legal copilot that everyone had decided was going to be so powerful that any software business is now completely irrelevant. So I think there was a sell off in even a lot of like some of, I think Apollo and some of the private equity firms that had either equity or credit exposure to a lot of these software companies or other Expedia, maybe the AI travel bot. Again, there seemed to just be a thing where software is dead. And now today we're seeing that, well, we're spending too much on AI so we're, we're going a little see sawing here.
- [02:43]
Drew Cohen
It's pretty great because it's like AI is going to kill the software companies or the software engineers or it's killing the software users because now people aren't using software. So it's like it's just destructing everything. It's very much a case. And you see this like with Constellation Software, a lot of these software companies really where people aren't really thinking first, they're just kind of shooting from their hip and selling everything and then they're going to figure out what works and doesn't. And I can understand a little bit if you're just scared and you never really knew what you owned in the first place that that's your reaction. But typically not the way an investor should really kind of own their positions. You should kind of be able to articulate the actual threat which you don't really see too much.
- [03:22]
Alex
You know, I'm going to play devil's advocate here for a second because I do think that these two seemingly juxtaposed events can actually follow some type of logic. So watch me here. Drew's probably going to try to destroy it. But this is where I'm going with is yes, there can be a thesis that software companies are dead and that AI agents or something of that nature. And again we're going to get into the code writing thing. Can anyone just spin up a new Salesforce with their AI agent that is, you know, super tailored to their business and now Salesforce is irrelevant. Okay, that can be a concern which leads that sale off. And then secondarily there can be a concern that yes, these things are going to be great, but $200 billion in capex spending is going to need a lot of money coming back to justify that spend. So I could see how yes, it's going to change a lot of things, but we're spending too much money on it. I could see how those both could exist.
- [04:09]
Drew Cohen
You could almost also just say the more money they spend on it, the cheaper it gets and so the more likely it is to become commoditized because you have even more access to these AI models at cheaper prices. And so now you're getting even a higher proliferation of that. And so maybe it's becoming even more competitive versus if there was a bottleneck on how much AI you could really use because of the capacity constraints. But there's so many different like layers
- [04:33]
Alex
and there are no winners. I mean, I guess there's no winners in this scenario because you got Google spending too much money on this. And then the software companies aren't doing well because the AI bots are kind of have been over invested in. I guess Nvidia could be doing well, but then you could say, well, they're pulling forward too much demand right now. So this isn't kind of something you
- [04:48]
Drew Cohen
can, if you go back to kind of like the, the capital returns argument where as soon as there's an excess of supply because you can never really estimate demand that much, but you could follow supply and as soon as supply exceeds demand you're going to start to get pricing pressure and all of this. And it seems like they're almost purposefully trying to find that frontier because they find that the risk of underserving this market is too great of a risk to not play in it, that they rather overshoot all of this. And so all of this CapEx spending there, it's going to continue to increase until they go too far. And then what that means for the actual business aspect of it, the pricing pressure and all that is very much an open question because these could be assets that don't get great returns on them. And at least my understanding of these GPU first data center architectures is it's different than the CPU first, the kind of other architectures they have going on in their cloud business. And so, you know, maybe everyone is using AI and it does find usage, but maybe it doesn't. Or even if it does find usage, the price people pay for that drops a lot because these are assets that have already been deployed and they would rather sell them at a lower price than have them sit vacant. And so that is also going to be kind of an interesting factor thrown in here.
- [05:55]
Alex
Yeah, and again, I do think it's a lot of multi level thinking in kind of an uncertain world right now, to say the least.
- [06:01]
Drew Cohen
Yeah. And this is why I don't think it's a Good idea to invest this way because within two minutes we've already been able to argue both sides of the argument and there's no real certainty in either way in how it develops. Does all of this CapEx spend get, you know, this great sort of return? Because AI is so prominent, it does end up kind of killing a lot of these businesses or at least finding new use cases. And really is this great dominant thing. And by the way, 200 billion in capex isn't enough because of how much efficiency and productivity is ultimately going to be produced for all this. And so that's one argument or the other argument is you're overshooting it and you're going too far. And the actual use cases of AI and business improvements where you actually see a return on that have been pretty limited overall. Besides, maybe, you know, meta is kind of a good exception to that. But in terms of needing something to justify what are we talking about? You know, over half a trillion dollars of capex spend and, you know, it's going to take several years for that to ramp up for it to actually be in a position where it can produce returns. And by then, you know, what do you need to produce on that 100, 200 billion plus in revenue from that? So there's also, you know, some uncertainty they'll be able to do that as well as, you know, who ultimately is going to be benefiting the most from AI. Is AI going to become modularized? I think it's pretty possible that it does. If you're thinking about where it sits in the value chain. It's of course providing a tremendous amount of value. But is it something that they're going to be able to capture that value and defend it, or are there going to be open source models or alternatives that are good enough? Well, as of right now, you know, it seems like there's multiple models that are, you know, within a few months of each other. You know, Google just recently kind of surpassed OpenAI, at least that's what people are saying, although there's some dispute on exactly what metrics. And so all of this just brings to question, you know, what are the business models here and who ultimately is going to have a defensible advantage? Because whenever we talk about what is a great company, it's very simple, right? You have to create value, you have to capture a portion of that value and then you have to protect it. No doubt AI is creating value, how good it's going to be at capturing a portion of that value less clear. And then ultimately whether or not it's going to be able to protect that is also very unclear. So all of these are very open questions. I think, you know, it's going to make more sense when we talk about specific businesses and then you could actually do the analysis rather than just kind of talking so, so broadly. But I think there is reason to certainly suspect that a lot of businesses will be challenged. But I also think the reasons why they'll be challenged are not kind of the thing you may think from a very high level, 30,000 foot view.
- [08:17]
Alex
Yeah, I like it. There's very reasonable arguments on both sides of the, of the coin here. And speaking of kind of some casualties of this war right here, which is Constellation Software, which again we've covered extensively. It was one our first company updates and one of the first reports Speedwell Research put out. Constellation is down about 50%. They wiped out about half of Constellation's market value. On the thesis that. And again, Constellation is not shy or discreet about the fact that there's high switching costs. The software is usually not great. It's good enough. And people are usually too lazy to retrain staff or do something of that nature or rip out a software that works. It's not changing anybody's life, but it gets them what they need to be done. It's critical. And you can raise prices and keep people stagnant without providing too much customer support. And again, that business model seems to the naysayers to be crumbling because now I could have an AI agent or I can spin up the software super cheaply. And why would anyone, you know, pay fees for a mediocre software in this world of AI abundance? And that seems to be the thesis driving it down. And again, I know like we don't like to assign too much narrative to stock movements, but I do think that that's more or less the logic here. Right?
- [09:25]
Drew Cohen
Yeah, I think it very much is the case of people just seeing how impressive AI is and they're seeing it enter more and more areas and they're just extrapolating there, thinking that the ultimate conclusion is it's going to be able to do everything, including building an entire, you know, software product, which it's already able to do to a certain extent. But the thing here is that a few things. So one, it's ultimately where the competitive advantages actually lie and where the moats lie. And just because you have a product, it doesn't mean that you have a business. And I'll go so far as to say there's a lot of times you could actually have a superior product, but it is not successful because there's a lot of other elements of a business that are important. You know, there's distribution, there's getting your product out there, there's support for the product, there's upkeep of the product. There's a slew of things that all circle around the idea of just getting a product. And a lot of these VMS businesses, you're talking about companies that are not big, they're started very often with one software engineer, two software engineers who coded the entire product so it was already, you know, a relatively trivial product to make. It wasn't something that required a whole team, you know, of a hundred engineers that were super complicated. In fact, they usually get the criticism that their software is very slow, outdated and all that. And people still don't switch. And it's not because it's imposs to find someone else to make a similar product. It's not. And the kind of fear now is that people in house, within the company themselves will go and look at their software provider and say, I'm going to actually just replace you instead of paying you. Now, I think this is, you know, wrong for many reasons. First and foremost, very often it's the company themselves that actually help create the product alongside Constellation Software. So that's one thing. Two, the actual expenses involved in the software, it's not so high that this becomes the main sort of focus. Three, you're going to need something that works 100% of the time because again, this is mission critical. And so any sort of errors whatsoever in the code you're creating and your whole business is lost. You lose revenue, you lose customers. Why would you make that? It's such a bad asymmetric bet that I just, I don't understand why people think that you're going to be a business owner that, you know, has, you know, $5 million in revenue and bet the entire thing on trying to save, you know, a couple grand a month, if even that in software costs. It just doesn't make a lot of sense to me. And so maybe AI does get so good to the point in many years from now. It certain not there at any point today or in the recent future where it's making zero mistakes because these business owners that own these VMS companies are not sophisticated enough to go into a code and check, you know, the AI to see what was wrong. And so it has to work 100% of the time and be perfect. And we know we're not there yet. And maybe we do get there in several years from now. But even then there's still a risk of something always going wrong and them having no idea what to do. And then it just really just doesn't seem like that's something they're going to be willing to do in terms of like a risk reward proposition. You know, you save a little bit of cost but risk your entire business going down. And that's not to mention the fact that during the transition you potentially also, you know, have issues with data migration and all that and errors where there's downtime and then you also lose revenue. Then you also have to retrain your entire employee base on new software. Then there's also all of the integrations where you have to hope that this, you know, new AI created software that you created yourself just works with everything. It just, to me it kind of sounds a little bit like the difference between someone who's actually run a business and thinks about investing from a business perspective versus someone who's kind of just this very high level financial analyst, if you will, who just thinks of all these highfalutin ideas. And it has never actually had to put anything into practice and see how often things really go wrong when you do that.
- [12:57]
Alex
Oh, tell us how you really feel. Tell us how you really feel. Well, how about this? I like, I like letting you argue with yourself. I mean, I don't think that it's an outrageous thesis that. And again, I think it just becomes the uncertainty, right. Which again, you talk about Constellation and the terminal value of their business is very predicated on them being to reinvest capital at these high rates of return in the software world. Right.
- [13:18]
Drew Cohen
So again, well, because you're talking about terminal value, if we rewind a year and a half, two years ago, the most common criticism we would get is that, you know, these VMS companies, they don't grow, they're in all these slow industries. It's very common for the end markets for the companies to go out of business. You know, they had some businesses where they owned software for linear TVs and for like radio stations. And so that's not a growing market that's eventually going to continue to shrink at least. So the thinking was. And so, you know, a lot of these businesses they own, they don't have any terminal value. They're not going to be worth anything in seven years or something from now. And the pushback I would give on that is that could very well be true. Except ultimately, in order for you to make money, it doesn't matter whether or not it grows indefinitely. What matters is how much cash you pull out before the business this life ends. And if you're paying a low enough price, the return you could get is really high. And by the way, this circles back to same discussion or, you know, argument I'm having with coupang with people who commonly say, well, the Korean tam isn't big enough. And I would have to push back and say it doesn't matter how much the growth opportunities are. If you're paying a low enough price for a business because most your return is coming from existing cash flows, it doesn't need to come from growth. If we think about any sort of business, you know, you're getting two general sources of return, the existing cash flows and the potential future cash flows. Okay, if you don't think there's a lot of growth, then the cash flows today have to support evaluation, which just means you have to pay a lower price in order to get your return. And that's not something that should be that complicated. But people commonly kind of confuse these ideas where they think of the actual return a business generates as being conflated with its growth. It's not. These are two separate things. And so in terms of the terminal value question that you're asking me here, a lot of these companies were never thought to have much growth and be around that long. And so if this is something that's going to take, take, you know, five, 10 years before it's good, a lot of these companies were assumed to kind of already be bleeding down kind of by then. And so in terms of the future reinvestment opportunity, yes, that's true. You still do need future investment opportunities. But if it does become this situation where all of these VMS companies are pressured that much, they just won't deploy more capital into that area and they would have to look elsewhere. And okay, that would definitely be a negative because they have this whole apparatus that's built up on finding these software companies and it's pretty hard to do. On the other hand though, you know, they could always reinvest something elsewhere. And so they have been looking into other areas. But that's not to say believe the fact that these VMS companies are going anywhere. I think that we're always very quick to think how much things change and you know, we kind of surprised how slowly they usually do. You know, look at the transition to cloud. You know, it's still all these companies still have on prem solutions and people are still migrating over the cloud. And that's been something that's been going on for what, the better part of 15 years now. And so it's not like these things just happen overnight. And these are even amongst, amongst, you know, more sophisticated companies as well. You're not talking about, you know, a random dentist office in the backwoods of
- [16:09]
Alex
Arkansas, you know, and it's conversations like these that I'm just grateful for. Companies like Floor and Decor, even though it's been a dog for about five years now. But I'd say that it's so much easier to wrap your head around. Will people need cheap flooring with large selection in 10 years from now? Versus how is Constellation going to interplay with AI agents? It just, just again, I understand that the certainty and you talk about like the band of outcomes for Constellation, I would agree with the investing community that that band has gotten there. There's a negative outcome for Constellation. Again, it's not, I don't know what probability you assign this is when it comes to risk and return, but I would say that distribution of outcomes has gotten wider and I think that left tail has gotten a little fatter. Like I do think that there's a higher risk for Constellation in this, you know, AI agentic software world. I don't know when that risk is, but I could see the argument like I don't think it's a completely out of left field ridiculous argument. I think there's good counters to it. But I'd agree that there's some repricing that might have needed to be done. Or do you disagree with that?
- [17:11]
Drew Cohen
It's always tricky when you're talking about a tail risk because how do you price a tail risk? Because it either happens or it doesn't. And it's very hard to actually get a probability of it. Of course, if it does end up happening, it's a largely adverse event. And it's a little hard to think in Constellation's case exactly what that adverse event is. Because even if AI does get so good it can on the fly create perfect software, I still don't see how that's getting distributed. I still don't see how you're actually getting it in the hands of someone. Unless the idea is that everyone has this AI agent on their computer that's so good that they could just tell them what to do. And it just does everything automatically and never makes any mistakes ever.
- [17:49]
Alex
And then in that world it's kind of like I don't know where humanity is in that world.
- [17:53]
Drew Cohen
Yeah, so and so, if that's what you're talking about, it's just so hard to say because I just don't buy that. I just don't believe that's going to happen. And if it does, I don't think it's going to happen in, in a couple years time, in 5 years time or 10 years time. I think there's still going to be a lot of errors in AI for a while. I think that it's still going to not be something you're going to want to rely your entire business on where if it makes a mistake, you're out of business because you literally have no idea how to fix it. And I just. And then you have no one to call too. And I just, I don't know that. I just believe that circumstance. But you're right. Great. Is it. There's some risk of that happening. And I think a lot of times as investors, it's honestly when these tail risk events pop up where you kind of have the biggest opportunity, you know, you think about some of the biggest bets that Warren Buffett made. You know, he's talking about buying the Washington Post during kind of the Watergate scandal. And if, for those that don't remember at the time, it was either the Justice Department, I believe, was taking action against the Washington Post because they leaked the story, they said they kind of had information they shouldn't have had, et cetera, and there was some question as to whether or not they could litigate them out of business. Right. You know, you're talking about the US Government and of course there's a free speech issue there. But they also did get access to information and publish stuff that maybe they shouldn't have. And who decides whether they should or shouldn't? It is the government themselves. And so this is all to just say that at that time when Warren Buffett took a big stake in the Washington Post, there was a big existential risk around whether or not they would survive. And I think that is what is really missed very often is that it wasn't this case where it was like, oh, it's trading at this super low earnings multiple and there's no reason why it's trading this cheap and I'm gonna just go ahead and own it. And you know, the market is stupid. Like, no, there's a very big risk that was a tail risk that existed and the market maybe has trouble kind of pricing these tail risks a lot of times. And so maybe they get overweighted a lot because they're so salient and because we know that, you know, as, as people were loss averse and if something has a very kind of obvious big negative downside. We want to tend to avoid that maybe for good reason, but at least in the case of investing, when it has a very small chance actually occurring and you could create sort of a portfolio of bets like this, I think that could be an opportunity. And you know, that's kind of what Warren Buffett did, is he made that decision. He didn't say there's no reason, you know, the Washington Post is that cheap. Despite what he might have said in, you know, books or what people would have said about him, there was a risk that they went, you know, out of business. And you could have said, wow, dude, you really bought the Washington Post while like the US government was busy like litigating it out of existence.
- [20:17]
Alex
Yeah, I agree, I agree. I mean, that is when the best returns are made. But of course, you know, you and I talk about this all the time, which is a company's not down 50% for no reason, you know, and that's, that's the always challenging thing about an investor. And again, that's nice when you have a really in depth understanding of the thesis and you can have a resilient perspective on the business and, and its competitive advantages. I do think that this is kind of where technology companies do become challenging, especially in an environment. I'm going to say every environment feels like it's fast changing. Right. So I'm not going to say we're in a unique period in time. You know, this time's different. AI is different. I'm sure people felt like this in the dot com bubble. They felt like this kind of during the smartphone revolution. And there was always kind of a technological upheaval that is shifting business models because of course it's a dynamic environment and being able to shift through the winners is what makes a good investor versus a bad investor. Right. But I think we can kind of wrap up our discussion here on the AI eating the software and move on to the second part of our discussion. Any kind of closing thoughts here before we talk about another software that you could make the argument AI is going to take over that too. We'll see.
- [21:20]
Drew Cohen
It's not down that much for no reason. And I don't think people are wrong to try to, to, you know, consider different possibilities and all that. But I think the general reaction, the market is that it doesn't really try to investigate as much as it first tries to discriminate against every potential business that carries this risk. And it's not like it is treating all of these businesses separately. Like Constellation Software versus, you know, a different company like Adobe, which, you know, we just did a YouTube video on. And so it's. They're different scenarios. So it doesn't make sense to me that every single software company is down that much. And so that's what I mean by where I say it's not being that discriminatory because certainly I think some actual software businesses are going to benefit. They'll be able to use AI to create better products, maybe fire some of their software engineers, become more efficient businesses, and they'll still own the distribution and advantage with the customer, and then they'll still be able to provide them support whenever there's issues and all that. And there's an aspect of all this, too, that the sequencing of all of this matters. If AI was really, really good and awesome today, that it could make perfect software, then maybe you could replace your software offering. But it's not at that point. And so long as you still need someone to get that other 5%, if AI does the first 95%, you're stuck with the software company. And so as long as you're stuck with the software company, they're going to be the ones that are offering you that. And so then you're, you know, more likely to kind of just be stuck on them because you're still using them even in this AI world. And, you know, they have all your data there, the integrations and all that. They'll continue to improve it, they'll service you when there's issues and all that. So it's not that there's no risk, it's just that the market doesn't know how to price the risk. And I think that that's the advantage is the investors. You find the opportunities where you think the risk is misprice. You think people are worried too much about something that can't happen. But I also always say this, that the key to investing is not arguing against risk. It's not like you find an investment opportunity and you say it has no risk. The risk always exists. What you do is you accept that the risk exists because you believe you're being compensated for it. And the idea is that if I have 20 of these bets, I think maybe no more than one or two of them are going to go against me. And since I'm being more than compensated for that risk, risk, that's going to be a good outcome. And I think of this, you know, honestly, a little bit like Evolution stock. It's not like the risk of Asia, you know, the black market There, gray market there, all that was unknown and you know, potential issues with more regulation and then people decided to play in unregulated markets rather than regulated markets. All of those risks exist. They were all there. You know, when we first talked about evolution, it's just that, you know, kind of the worst case or near worst case scenario ended up happening to them all at the same time across multiple different domains. And so, so as an investor, if you did invest, you accepted those risks exist and it's unfortunate that the business went through what it went through. But it's not like you just say, I don't think those things are ever possible. You just thought, you know, at the multiple you were paying that it was more than priced in. And maybe now it's really more than priced in. That's, that's for you to decide. But that's kind of my thought process on the risk. So yes, there is some more risk, but it's ultimately an issue of what is the right way to price that.
- [24:16]
Alex
Yeah, no, no, well said. And again, I think that's the fun of investing, right? You're in quite an uncertain world and you're going to find out if you're right sooner than later. You're going to get feedback. So I think we can kind of transition this discussion here into the dating app video, which you had, which is again, ostensibly should be a pretty simple business. You have kind of these runaway apps that have one majority of the market. We're talking Tinder, Hinge, Bumble, I can't even name many others than that. And they have, you know, a lot of supply, right? They got guys, they got girls, they seem to be the most popular apps. And theoretically you should just be taking a percentage of the transactions. Your cost should be pretty low. Low. These are high value engagements, right? People are very focused on finding a significant other. Now of course, with the half a trillion of AI, perhaps we all end updating robots in the future because I don't know, maybe it's just easier that way. I don't know how that's all going to shake out. Again, you could make an AI argument there a little more far fetched, but again, you're right, maybe an AI robot can actually find, you know, learn who you are, learn who someone else is and then you get even a better match. I don't know. I mean that could happen. But ignoring that reality, why is Match Group, which is the large publicly traded company, and then you have Bumble, which is the other standalone kind of large, large scale dating player. Why are These like remarkably large, great high margin businesses. I mean, it seems like you have a service that again, you're delivering software, you're delivering a high need, which is someone's looking for a significant other and that's a very valuable service. And yet these businesses have really not done so hot. And so maybe we could talk about first of all the dynamics of dating apps. And I think you really do a great job of fleshing out a rule of thumb here, which is I think you call the point of monetization and how the dating apps kind of have a struggle with that, which is also something we can learn about other businesses. But I'll let you kind of take it from there. Why are dating apps not as great of businesses as you think they would be?
- [26:03]
Drew Cohen
Yeah. So the answer, in short, is going to be point of monetization and consistency. These are two aspects that don't just apply to Match Groups Group, they apply to a lot of other businesses. But I really like, to be honest, these kind of like mediocre businesses and looking at them because I feel like you learn the most as an investor because you get kind of a counterfactual of why a business isn't working and that really allows you to learn more. And so that's a pretty good opportunity to kind of come up with these new lessons. And so right before I get into what I mean by that, just kind of setting the stage, you're looking at Match Group, they have three and a half billion dollars in revenue. You know, they're growing revenue 0.2%. So really not much at all. They own a bunch of different apps. They, they own Tinder, they own Hinge, they have a bunch local ones and ethnic specific ones. So a whole family of different apps, all of like the Legacy, OkCupid, Match.com the old ones they own as well. You know, they have 25% margins, which you'd kind of think it'd be better for an Internet company. 73% gross margins. And you know, right now if you're looking at just Match Group, that trades at a multiple of about 13 times earnings, that's forward earnings or 15 times trailing. And so really, you know, they're pretty cheap for an app that kind of is dominant in the dating market. And you would think that this would be a really important market and a better business because there's a lot of people that are single that are trying to find someone else. And it's a very high value service for you to be able to find someone else's potential mate. And so why do you struggle so much to monetize that? And the reason why is twofold. So the first thing is that it's gonna be a very inconsistent value prop they have. And we've talked a lot about value props before on the podcast and the idea there is what are you actually offering users? The problem is the thing users want is of course to get a chance date or to find a spouse or something. But that's not something the dating app can sell. So instead what the dating app sells is the best sort of stand in thing they can for that, which is something like, hey, we'll, you know, let you like more profiles, we'll boost your profile to more people, we'll let you send a rose, we'll let you send, you know, a message before you like them, we'll let you, you know, hide your age. All sorts of random things they, they try to come up with because they can't actually do the thing that people want, which is to help them find something, someone. And so the second part of that is at the point you are monetizing, you don't actually know what you're getting, right? Because this value prop is so shaky. And you know, to be honest, a lot of times it's just the best looking person is going to get the most matches. It doesn't matter how much they pay. And in fact, even if you pay more money, it doesn't do that much because it doesn't make you more attractive to other people. Maybe it could get you shown in front of more people, but it doesn't mean that they're going to like you at a higher rate. And so that's kind of the issue. And so when you are monetizing this, what you are trying to do is you're trying to convince people, hey, I'm going to help you get, you know, a spouse, get a date or something like that. But in reality, in their experience that they're having, they know that they can't help that much with it. So they kind of become very hesitant to spend money because there's this element of kind of unpredictability in what they're getting. Whereas in contrast, if you pay for almost any other service, very often it's very consistent what you're getting. If you go to Netflix, you're paying, you know, 20 bucks. It's very consistent. Consistent what you're going to get, you're going to get the whole library of Netflix. If all of a sudden you paid that money and then it was really crappy streaming quality And a bunch of shows just immediately got pulled off. And this happened to every, you know, month that you signed up or something, you would kind of be done with that service. And so that is the experience a lot of people have on Match Group is it's very inconsistent. And if you look at a company like Chipotle and why they're going through so many issues right now, it has to do ultimately with the inconsistency of their product. People are going to the Chipotle and they're saying, hey, you know, why isn't the food ready? Or, you're giving me small portions all the time. And then other times you give me big portions, and it's just an inconsistent value prop. I don't know what I'm getting. And then I get a bad value prop sometimes, and I churn. So that is the key issue the dating apps face. They can't offer a consistent value prop, and then they also can't monetize it at the time where you actually know what you're getting. So the second aspect of all this would be these would be totally different businesses, incredibly lucrative businesses, if they, instead of taking the money before you found your person, took the money after you found your person. If there was a way to say, hey, if you find me a spouse, I'll give you $100,000. You know, there's a lot of rich people that pay a lot of money to find their spouse, but you can't monetize it that way. There's just no good way to do that. And so that is the other issue, because the value of finding someone their spouse is extremely high. But the value of putting just a random person in front of someone to start a conversation is very, very low. And so they instead are monetizing the aspect of just throwing someone right in front of you to start a message instead of monetizing the actual, you know, marriage or something like that, because they can't. You can't monetize that that way. And so that is kind of in a crux. The issues of the business model, why they have very high churn, why people are very reluctant to pay for the services, why you might pay once, be disappointed, and then stop paying.
- [30:54]
Alex
You know, I got to say, you spoke with a certain kind of ferocity when you were mentioning the Chipotle inconsistency. And I feel like that may have struck a tone for you personally. And you mentioned in the video, too. So clearly you've given a lot of thought to your portions you've been receiving
- [31:08]
Drew Cohen
at Chipotle, you know, no comment. But they could definitely improve a lot here, especially if you do the online orders. There's no reason that it should be, like, significantly less than when. When you're there in person. And if, by the way, if you find someone and you just talk to them a little bit, you're nice to them, that's like a way you could increase your portions to size, like, 50%. So I don't know. I'm probably the worst customer.
- [31:32]
Alex
You know what it is? It's just when you're not looking them straight in the face, they can kind of. You know, you're kind of an anonymous person to them, right? When you're looking at them, you're like, you're screwing me in real time right now. I see what you're doing. No, but it is. It is a great point, which is, again, it's kind of that disconnect between what is the actual service you want delivered and how are they being monetized. And I also feel in dating apps, there's some dynamics, mix of. You know, I think women feel that they're less likely to pay for some of these things. Maybe that's statistically inaccurate. But, I mean, I don't know if they have, like, statistics on women versus men paying.
- [32:04]
Drew Cohen
Yeah, they do. And they are less likely. I don't have the exact numbers in front of me, but you're right, they are.
- [32:08]
Alex
And again, and that adds up because I do feel like, you know, there's kind of a stigma in society. You know, women get in for free and men are the ones who pay. So. And I could. I could kind of see. So you're not monetizing half of the. Half of the base. Super well. And then again, on the. On the men's side, you're right. It's. For some reason, I just feel that there's a situation where you don't want to pay for the service. I don't know what it is. It's also some type of. I don't know if there's a stigma or there's. It just feels like maybe you guys feel like you're cheating sometimes. But I do feel that anecdotally amongst my friends. Yeah, there's not a big pay to play on the dating services.
- [32:39]
Drew Cohen
Well, I think ultimately it's just because you don't get that much for paying. It's, again, it's like, it's. What is the value prop. Like, you know, you could get on it for free. The things they'll monetize is they'll, you know, either let you, like more people people, they'll let you, like, send a rose, they'll let you hide your age, they'll let you change your location. Things that just people don't care about.
- [32:59]
Alex
They don't really do the sort of thing. Hide your. I pay to hide your. Yeah, yeah, listen, I mean, someone, someone came up with that. Some type of person found a way to monetize that. So, again, I, I think it's an interesting one. And again, what is a perfect world here, right? No one would pay for this, but it's almost like a success fee. You use the app and if you, you have a dating person, then you pay ten grand. But no one's going to do that, right?
- [33:21]
Drew Cohen
That's why. Well, you. Yeah, I mean, but that's like why Met was so successful. It's. You're. You're paying on success metrics, right? If there's some way you could do something like that, then it would, you know, be a lot more interesting in terms of monetization. I don't really see how you do that even contractually, and I don't see how you'd enforce that.
- [33:38]
Alex
Yeah, no way.
- [33:38]
Drew Cohen
That's.
- [33:39]
Alex
And that's the problem. Right? That's the crux of the issue, which is the success metric cannot be monetized. It's the pathway to the success, which is attempting to be monetized. But you could have a lot of success without paying for anything. And it is funny, you're right where, you know, you pay 20 bucks for Netflix, but people don't want to pay 20 bucks for an increased probability of, like, finding their wife. It's just, it's just kind of situation.
- [33:58]
Drew Cohen
Right. And which is exactly the point though, I want to make by this idea, the point of monetization, just to make it clear, is that the closer you are to the actual creation of value in a consistent and reliable way, the more you will be able to charge for that. And so that is why where you are in the sort of customer journey, the closer you are to actually the creation of value, if you're monetizing at that point, it will be a lot of higher. You know, again, the example of meta, if you're able to actually monetize a sale and okay, we're going to keep showing you the return on ad spend and we're showing you this number and we're basically monetizing your sales. That's a, that's a great way to actually do that. Same thing with, you know, Google search Keywords, anything where you're actually monetizing the creation of value, it becomes very kind of obvious why you're paying the people for the service. And there's a little bit of that too in the investment management industry. If you're able to say, you know, I made you X money, it's very easy. Easy to then be able to say, that's why my fee is going to be this percent. Yeah.
- [34:52]
Alex
And again, it's just kind of an interesting paradigm about how, you know, I don't know if this is a venture based. If I was kind of like a venture capitalist. I'm looking at monetization models or even kind of public companies. And I know you looked at one of the dating acts kind of in a pre IPO phase. I think it was bumble. And again, it's an interesting perspective where maybe you have a rule of thumb. And again, we had. I think one of our investing mistakes was rules of thumbs can be wrong, of course, because you never know. But, but it does seem like intuitively this makes a lot of sense and there are a lot of examples of this kind of bearing out. And it's just kind of an interesting framework. Did you write a memo on this or is this just kind of a. You ever do like a monetization? I'm sure there's like many examples of this throughout business history.
- [35:28]
Drew Cohen
Yeah, I need to do a memo on this. It's been brewing for a while, but that's why I released the video first. I've been pretty behind on the memos, but it is a really important concept because it exists in a lot of businesses and I don't think it gets that much attention as kind of something that, that could set apart, you know, a good and bad business. Especially the case where you are, and I like the way you said it, you know, you're paying for like an increase of probability. That, that's a really. That's not something people really want to pay a lot of money for. It's like gambling.
- [35:56]
Alex
Yeah, you're right.
- [35:57]
Drew Cohen
Yeah.
- [35:57]
Alex
Like imagine meta, like, well, increase your chance of a conversion. No, it's like, no, when they convert on this, you get to pay. I mean, same with Google. I mean, that's why these are such amazing businesses. Right.
- [36:06]
Drew Cohen
And that's also why, you know, brand advertising was never nearly as big as digital advertising. Advertising, as soon as digital advertising became a thing that's, you know, overtaken the market. Because with brand advertising, like traditional, you know, billboards and all that, it's, oh, well, you know, in theory, we're increasing top of mind awareness, but you really don't know for sure. And you do it long enough and you could kind of measure and track, but it's just much more satisfying knowing, you know, I gave someone X dollars, I got Y dollars back. Let's just keep doing that.
- [36:32]
Alex
Yeah, no, and it's, it's such a unique insight and I think a good way of framing it. And you know, you're looking at two business here. We looked at Uber, I think, a couple weeks ago. Why was that kind of an intuitively good business that struggled? And hey, why is this an intuitively good business that continues to struggle? I mean, let's look at the future of this company. Do you feel that there's any way to turn this around? I mean, for the match group, you know, I don't know how they've been performing recently. I mean, what, what's something that you would see that, hey, maybe they've turned the leaf on this? Or do you think it's just a perpetual issue?
- [37:01]
Drew Cohen
It's again, I mean, here's the thing, like, it's a real problem that needs to be solved, like helping, you know, single people find each other other. And it's something there's a lot of money to be made in, if you could figure it out. But this format that it exists, it just doesn't seem to be the best format to do it. It certainly works for a lot of people and it's good enough for some, but it's just not successful enough. And in terms of the actual monetization model, it has all the issues we talk about. And so I think if there's another way you can monetize something more directly where maybe the, the principal thing is about just like meeting people not even in a romantic setting, and there's more engagement. And you know, I just kind of think back to this old behav psychology book I read by Dan Arlay where he talks about how he has these two people in an experiment play with these just dots, these red dots and a blue dot, and they chase each other. And it's a really simple bad game. But just by even playing this like, bad game with each other, it increased each other's affinities for one another before they actually even knew who they were. And so the idea there is that by like playing some sort of game together, you're building camaraderie or some sort of substance, some sort of similarities with some someone else, that you can do that before you even know who they are. And Then once you learn who they are, that's when all your judgments and biases come in. But if you have that sort of background of interacting with them before, you're more likely to overcome it. And I think part of the problem too, with just this format is it's very easy with all the biases everyone brings in and all that, to just look at a photo and go, nope, next. And there's like endless photos, endless people, and just keep going. And it, it's just not, it's not a way you very naturally would kind of date someone. Whereas, you know, there's lots of times you get to know someone, you know, they, you know, maybe you didn't think much of them until you heard XYZ about them or you, you know, laughed with them and then you felt differently. So it needs to be some sort of way where you create this behavior kind of thing first and earlier, kind of in the journey, rather than, you know, your interaction being like, you know, a random comment someone sends you on it. That's, that's just kind of my opinion and take on it, because that was my takeaway from that behavioral psychology study that Dan Arlie did. But it's a tough business model as it stands, and they could do a lot of things like this, you know, games and all that. Just, I don't know, the existing format just doesn't seem that popular with people.
- [39:09]
Alex
You're right. It's kind of a funny point. And you're kind of like, oh, I'm on this date, but let's see what the app has to offer tonight. I could see how it kind of becomes a perpetual situation where you kind of never know what's. Never know what's next.
- [39:23]
Drew Cohen
Yep. And then you get to the end of it sometimes, which friends have reported to me on, you get to the
- [39:30]
Alex
end of the hinge likes or the end of the hinge swipes. You've gone through every person in the
- [39:34]
Drew Cohen
city and then you're onto the AI
- [39:36]
Alex
robot, then you're, you're onto the AI bot. There you go. Well, I think we can end it on the AI dating robot apps here. And what's in the pipeline for the Synopsys listeners.
- [39:47]
Drew Cohen
So there's going to be a lot more kind of dialogues out there. I'm also going to be doing more of these monologues on the business updates because we're still running through a lot of our updates. And right now Speedwall Research is working on the Adobe Research Report. And the way we kind of came about that decision was after doing the video and the five Minute Money on Adobe which allowed me to like look at a lot of different stocks. We looked at you know Uber Core Weave, Netflix, you know Nova, Nortis, Cadence, a bunch of different names. It allowed me to kind of see what could be the most interesting and I decided Adobe would be a pretty interesting one. I could see a lot of the kind of risk factors and all that weighing in there that I wanted to dive in more to see how formidable they were or not. So Adobe is the research report where working on now again we just did Ferrari we did Shift War before that and so a lot's going on. Go to speedwell research.com to get all of that and check out our YouTube for more videos more of these stock breakdown videos we've been doing. It will be linked below and then to get the 5 Minute Money newsletter go to Drew Cohen money.com But for now until next time.
- [40:44]
Alex
Until next time.