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How a Single Paywall Experiment Generated $50M – Jeff Morris, Chapter One, Ex-Tinder
00:53:21
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- [00:01]
A
Welcome to the Sub Club Podcast, a show dedicated to the best practices for building and growing app businesses. We sit down with the entrepreneurs, investors and builders behind the most successful apps in the world to learn from their successes and failures. Sub Club is brought to you by RevenueCat. Thousands of the world's best apps trust RevenueCat to power in app purchases, manage customers, and grow revenue across iOS and Android and the web. You can learn more@revenuecat.com let's get into the show. Hello, I'm your host, David Barnard. My guest today is Jeff Morris, former VP of product at Tinder, now founder and general partner at Chapter One, the early stage venture firm for product obsessed founders. On the podcast I talked with Jeff about Tinder's $50 million paywall win, why now is such a great time to build apps, and how hard paywalls can mislead you about product market fit. Hey Jeff, thanks so much for joining me on the podcast today.
- [01:12]
B
Yeah, excited to be here.
- [01:14]
A
So you tweeted a few weeks ago a banger of a tweet. And immediately afterwards, like, I've got to get Jeff on the podcast. I think I had DM'd you in the past about coming on the podcast, but we finally made it happen and I wanted to kick it off with that tweet. So the tweet, I think to some people, might be a little controversial in 2025.
- [01:34]
B
Love that.
- [01:35]
A
So I won't steal your thunder. Why don't you just tell me about what you shared in the tweet and why you think those things and I'm sure I'll have a million follow up questions.
- [01:43]
B
Yeah, so I guess like a bit of background before I go into the tweet is I ran revenue at Tinder for four and a half years through kind of our hypergrowth years. And so I spent a lot of time thinking about monetization, subscriptions and revenue, obviously, and what worked at Tinder. And when we really started to kind of like turn on monetization didn't happen until years four or five into the product. And so we had built just a great product that had extreme product market fit. We had scaled the product to, you know, like 30 to 40 million monthly actives, but we didn't have a huge focus on monetization. I think the playbook, at least until, like call it AI native applications started to come to market, was to really spend time on getting the product right, starting with the just like the core engagement loops and then making sure that you had great retention to kind of earn the right to build a subscription business or monetize through in app purchases or advertising. I think there's a lot of external reasons why founders now are, are pushing monetization earlier. Market is so competitive and so the, I think the metrics that you need to raise capital change and so the revenue slopes are much more extreme. But you're seeing teams now focus on monetization really on day one, even within the first session. There's a part of it which is also like, hey, these businesses are, are really expensive to operate. And the model costs for compute and inference require early stage founders to push monetization earlier in the funnel. And what's really interesting too from that perspective is you're seeing a lot more testing within kind of like what models do you offer consumers within subscription tiers? So do you give users access to your best performing model that might cost more than other models, or can you convert them with lesser quality models that are cheaper? And so there's this whole new subscription playbook that I think frankly subscriptions were like. It was always hard to monetize a user base, but the packaging and cadence of a subscription roadmap I think was a bit easier when I was operating in 2015-2020. We now invest in a lot of applications and I meet with the teams and hear their list of kind of like challenges or concerns with monetization and the questions they're asking are just really different from what prior kind of platforms were thinking about. So whether it's mobile or kind of like B2B SaaS or anything bottoms up on kind of like productivity type of app. So yeah, and then the last comment I would say is just there's a lot of like celebrating around revenue today, like, which I would say maybe is a bit premature because you see either on Twitter or within pitch decks, like the front page is hey, we got from like 0 to 10 million in three months or six months or whatever it is. And then you kind of like look at the data room or start to unpack what the cohorts look like. And they're really new cohorts. So it's impressive that founders are reaching those revenue numbers so quickly. But the jury is often out as to whether the vibe revenue or real revenue. And so I think there's going to be a lot of things that happen in the next year, whether it's a company's coming back to fundraise where the numbers don't look quite as advertised.
- [05:18]
A
Yeah, and I think that's what really resonated with me about your tweet and kind of this whole idea is that focusing first on engagement and retention and then monetization, it's not always the way to go. But what's beautiful about that is that you don't get a false sense of product market fit. And that's what I do think. A lot of apps today that are launching with a hard paywall think they have product market fit because people are paying, but then they bleed customers out the back end and like retention is even worse. And so, I mean there's not. I don't think there's a right answer for the entire industry. But I do think more apps probably should be experimenting with freemium models early. Like some should be experimenting early if the costs just don't allow you to do that, if you haven't fundraised or whatever, maybe you just can't and maybe you need that revenue upfront. But for some businesses, they're maybe shooting themselves in the foot over monetizing because there's people who might get into your product and actually enjoy it and be that long term retaining cohort. But by monetizing up front, you kind of push them out and never get that chance to win them back. And then you get people who are willing to pay money to try it out, but then don't retain. And so you're getting a lot of mixed signals. Whereas if you can build from freemium from the start, with that focus on engagement and retention from the beginning, you're getting potentially getting better signals of like actual product market fit. Whereas with annual subscriptions you might not really understand just how bad your retention is until 12 months later. And there's hints of it. You can look at auto renew status and stuff like that. But any kind of additional advice or thoughts on like who should be trying that freemium model first versus maybe the apps that do work better with that flipped on its head. Monetization, engagement, retention, which seems like most apps are kind of doing that today.
- [07:21]
B
It'S very much depends on the category. If I was building an app today and I'd probably build more premium experiences that have, that don't sacrifice product quality if you were to monetize. So example being like there's a website builder I know well, they're more of an earlier stage company and it's a really popular product within its segment. But the challenge they had with freemium was just users. So if you build a website, whether it's on like a lovable or a bold, you obviously have like a fair amount of debugging that you have to do within any product that you create. And they actually couldn't afford to let their freemium users debug the initial builds. And so if you look at, like, Twitter for that product, people were really frustrated because they would have some idea, they'd prompt the app and then it would be buggy, and then they'd be kind of like pushed into some subscription to kind of make that happen. Like, there's not a payoff of a successful outcome before you're asking people to open up their credit cards. So I think for something like that, I would probably just say, hey, we want everybody who pays for the product to have, like, really have full access to the best working version of our product. And so you're kind of getting people who are trying to monetize before they have that. That like, magic moment with their customers, which, you know, like at Tinder, you wait for somebody to get a match and to have a conversation and to really believe in the product before you ask them to become a paying subscriber. And so I would almost focus less on total, like, subscription number in terms of users than. But really try and provide a great experience for those people who are willing to pay early on. I think you. I think you can still build, like, very successful, call it like whale driven products. These aren't even whales. They're just people who really have a high intent, like a. They have a problem that they really want you to solve rather than being like, you know, like a GA product that is suboptimal that people complain about on Twitter.
- [09:26]
A
Yeah. And I. You know, a really good example of this. People listening to this podcast probably don't. Not many listeners also listen to Ben Thompson. Um, but he's been talking a lot about how he thinks ChatGPT should monetize more via ads and probably should have from the beginning. And one of the points he's made that I think is really insightful is that most people who use ChatGPT have never gotten to experience thinking pro or deep research, because those aren't available on the free tier. And so they don't Even know what ChatGPT is even really capable of because they've never paid. And so it's kind of to your point. There is a little bit of a not chicken before the egg, but it's like you want your users to actually get the best possible experience to really understand what the product is. But that's attention, because how do you give that away for free or, you know, I mean, free trials kind of work. But then again, it's like not everybody wants to start a free trial and that kind of thing, but how do you, how do you get those users that best experience of the product to understand what it's even capable of so that they know what they're paying for before they Pay. And maybe ChatGPT is at a scale where it's okay and the revenue's grown tremendously, but it's a tough balance. I mean, what are your thoughts on like, how to balance that? Like putting good stuff behind the paywall but still providing the best possible experience?
- [10:55]
B
Yeah, it gets a. A really hard question. I think this is a version of the world that favors the founder or the company that can just raise a ton of capital and has, you know, like we saw this within ride sharing, right? And kind of think of as being a similar thing where if you were Uber or Lyft, you could subsidize the early cost, then become more efficient over time and you know, within kind of like AI applications. I think the same could be true where you're seeing startups really struggle to offer a great product because of the cost requirements as opposed to, you know, founder who can raise a lot more. So I can think of like a recent example where a founder raised, I think they raised like a $50 million Series A from a big firm and they have an identical product to a startup I know and they're able to just offer a better experience because they can either subsidize a freemium product or be more generous with a subscription tier within kind of like classic subscription products. If you're not building an AI, there's a whole different Playbooks. So I think it's probably good to look at the world between call like AI native compute intensive companies versus the rest. If you're building a Tinder or a Headspace or something similar, it's kind of like the classic playbook. And you don't have to worry as much about these new questions that I think founders are trying to figure out.
- [12:18]
A
Yeah, it is tough when things are expensive. And I'm curious your thoughts then on raising money as an app in 2025. Because, you know, as you said, if you can raise money and offer an even better free experience, build up the usage, build up the engagement, build up the product retention, and then monetize down the road. For some companies, that is the optimal path. But raising money in 2025 unless you're in hot AI startup is challenging. So what are your thoughts on what sorts of apps can and should raise in 2025 to run that playbook versus you know, a lot of the folks listening are the more bootstrapped and do have to make these really tough trade off decisions. I mean my, my weather app that I work on on the side, I have like really high data costs, like to get good weather data. It's very expensive, especially like animating the maps and stuff like that. So I, you know, I personally face this challenge and don't I have a hard paywall right now in my app specifically for the cost reason similar to a lot of these AI native apps. But yeah, how do you avoid that in 2025? Like how who can raise money and who should raise money to start with that kind of more freemium experience?
- [13:32]
B
Yeah, I think the venture market is treating non AI native apps as almost like a non investible category, which I think is pretty crazy because we all know that mobile usage and adoption is growing year over year. I think the knock on mobile apps is just people. There's a perception that people aren't downloading new apps with the same frequency as they did maybe in the, I don't know, the 2005-2020 period. I think now is a great time to build like a hyper premium mobile experience for every niche imaginable. The cost to build an application from an engineering perspective has gone down a lot and will continue to go down. And so probably my, my favorite example which most of your listeners maybe, maybe know of is like Flighty, I think has done an amazing job and their founder has been building that for probably almost 10 years at this point. But if you travel a lot and you are a business traveler, like Flighty is by far the best travel app. Right. That does have a hard paywall. I'm willing to pay, you know, 40 bucks a year expensive to your business or whatever it is because it's such a high utility product. If you're building something that's more, you know, like social or less clear on what problem it's solving, then you might have a harder time asking the user to do that. If you can't raise venture dollars, then you should be confident you're building a product that people will pay for and you should ask Bill to pay for it and see what the response is. And I'm a big fan of monetizing early.
- [15:14]
A
Yeah.
- [15:15]
B
In that sense, yeah.
- [15:17]
A
And you know, Flighty's an interesting example. It may have been that you used it at a time when it was a more of a hard paywall. But he was actually recently on the launched podcast, which is kind of a sister podcast to this and, and they have been experimenting and he was actually on Ben Thompson's podcast talking about this. And he has, he has experimented his way. And maybe this is one of those kind of examples too of like over time you do kind of find that right fit. But he has a really interesting model where now the first flight is completely free with all the pro features. And then if I remember correctly, some premium features then get locked after the first flight. And so it's this like he had to really experiment into this like hybrid thing. And so maybe that goes to our point is like there's not like a set rule. You need to like, you need to experiment and be willing to experiment and not just follow the patterns, but figure out what's right for your app. Is that he experimented his way into this like weird kind of freemium where he does.
- [16:20]
B
That's almost like a, like, almost like a trial to me. Yeah, freemium is like, in my mind, the definitions could be entirely different. Is like you can use the app in perpetuity, but there's just different value that the developer gives you for that experience. It's actually very possible that I did get that first flight free, but because the kind of like free version was so limited that it just pushed me right into the. The subscription.
- [16:51]
A
Yeah, that may be a good example for high cost apps though. Maybe, maybe that's the playbook to follow. Is to figure out a way to give a, a taste of that better experience even maybe without a free trial, but actually like some kind of usage limited time, limited. Maybe that's something ChatGPT has or should experiment with. Is giving, you know, one deep research a month so people can experience that. Like, I mean, deep research. Freaking incredible. I mean the stuff I throw in there and the responses I get back. I mean I use it almost on a daily basis. Things that I would otherwise spend an hour or two researching, I throw into deep research and get detailed notes and links. And I think a lot of people just don't even realize how good it is and it hallucinates way less because of how much it thinks. So maybe this is like a new playbook people should start experimenting with. Is finding ways to give, you know, one or two hints at that in the freemium experience to kind of offset the cost of it while still kind of giving that better experience.
- [17:52]
B
I think the truth is like most of the really fast growing AI products are putting out so many fires that monetization isn't like it's not as sophisticated as you think it is within those orgs. Yet. And so, like, we have a portfolio coming that's. I won't say the name, but they hit 50 million in AR within called a year with a prosumer product. And I called the CEO and I was like, hey, this is really interesting. Like, what are we doing on paywall optimizations and pricing? And I started to, like, put my revenue hat on. And he was like, what? Like, just like, what are you talking about? Like, we're. And I was like, holy crap. Like you hit, you know, 50 million without any experience. I'm sure if you gave myself or anyone who loves revenue, like just the keys to the application for a couple sprints, like, we could probably like double your revenue or do something that would really like, shock the team. And so it kind of like reminded me that the sophistication we got to at Tinder took us a long time. Like we. When we really built out the revenue team, it was 2016, about a year into my, my time at Tinder. And, you know, it's just like myself and caught like five or six engineers, right? You had like three iOS engineers and three Android engineers then leaving the company. It was, you know, I think I had like 40 plus engineers who were working on all parts of the revenue roadmap. I think that's kind of where a lot of these AI companies are in their product journey. So it's almost as we, as we say that a lot of them are trying to monetize really early and then they kind of do like this set it and forget it thing where they're not really refining that part of their product. So I think it can lead to, again, even more false positives or metrics that might not prove to be durable over time.
- [19:46]
A
Without revealing too much about that startup, can you share, like, what your first two experiments would be? I mean, did. Did you go through the product yourself and say, hey, here are the top two I would run?
- [19:56]
B
Yeah, I think it was mainly around kind of like packaging. And so they had a single subscription tier and these I found like our. My biggest unlock at Tinder was when I really started to think of the subscription tiers in terms of packages and all the way from the intra subscriber, who's probably younger and has less income and maybe isn't in the US to the largest whale you can imagine, someone who can spend $50,000 a year on a subscription product, which we had at Tinder. But you're building for such different customers. Right? But that just takes time to figure out because you're, you're not Only building kind of like new bundles, you're also building new features. And so you're trying to basically build very different experiences for users with different goals and expectations. And you could do that forever. Like that's why revenue teams are do what they do every day and then. And the other one that they hadn't done was just localization. So I think at, at Tinder, at least, like we had a really, really complicated pricing grid that was based on a ton of different factors, the most obvious being geography. Right. So knowing like our fastest growing markets were La Dam and India, but those markets had a very different willingness to pay to a North America or UK or something similar.
- [21:28]
A
So I wanted to, I did want to dig into pricing and packaging. So let's just move on to that topic in your work at Tinder, because we had Ravi Mehta on the podcast. So what's funny is like he got to build that really cool chart with like the, you know, higher price tier, the mid price tier, the low price tier, and then the consumable stacked on top and like how it perfectly fits the demand curve. But you were in the trenches like building that from the ground up. You know, he came along, he did help with that, but it's like he came along and a lot of that had been built. So I did want to dig into a little bit of like how that came about. Like what were the experiments, what were the conversations that led to the three tier system and the consumables on top of that. What was that process like to get there? And I guess maybe just you know, frame it in a way that listeners today can be thinking through, like, how do I get to that kind of multi product, how do I better package my offerings to fit those demand, that demand curve and the need of the users.
- [22:29]
B
I came in and was basically given a spreadsheet which had some really early versions of what our pricing was like for a single subscription tier. So it was Tinder plus at the time, nobody was price testing. Like that was just kind of what I think we would probably run like a, there was a data scientist or scientists who would run like really basic initial tests and that's where they landed. And it was kind of like, you know, set it and forget it. Where we really started to focus on pricing was as we started to saturate the US market and really started to focus on markets like India, as I mentioned, and Latam, which were growing but weren't necessarily the places where we were monetizing really well. And so I'd say, when should you start focusing on pricing, I would say really focus on your core markets. And for a US App developer, generally speaking, unless you're building a international specific app, like, that's going to be the North America audience. When we start to expand the tiers, like, generally speaking, the product leads you to premium features in terms of. You start to see what people are asking for and what they want you to build. And then the question as a product person is always, is that something we should monetize or give away for free? In the case of Tinder, which was specific to dating as a category, there was a certain element of, hey, we're building a network and ecosystem where if we give away everything for free, the application simply won't function. The kind of like, gameplay of the application starts to break down. And so we had to think a lot about, like, the second order impact of any feature and how, like, what percentage of the population do you actually want to give that away to? Because if you give everyone. I'll give like a real, really obvious example. Like we put a paywall on the number of swipes you could do on a daily basis because we found there were people who were just swiping their way through literally like their entire city in, you know, like a very small amount of sessions. And so. Or you had things like auto swipers. And so we put up that paywall to also to create a better ecosystem, but also turned out to be a great thing for monetization. So I think, I think a lot of it is in terms of, like, you should have like one or two things that you charge for early on and then really following the user and following your power users in terms of where they lead you for what they want you to build. And we always thought of these things as being like superpowers that you could give the user. And obviously not everybody can have the full access to those superpowers because then those features will become less valuable to the subscriber base.
- [25:07]
A
Yeah, that's fascinating. Yeah. Thinking of it as superpowers. What superpowers do I want to give my users and kind of following the product demand into building those features? Did y' all ever experiment during those years where you were like, hardcore, you know, optimizing the revenue of pulling features in and out? So would you, like, put something in the free tier? And they'd say, oh, wait, like, we really should have made that paid. How did you run those sorts of experiments? Because those are hard. And, you know, once somebody's gotten something for free, then putting it behind the Paywall is weird. And then, oh, I paid for that. Why is that now free? How did you run those kind of experiments?
- [25:47]
B
Yeah, I think we might have been a bit different from, like, normal companies, but the revenue roadmap and our products were very much built in, like, a different part of the Org. We were on the product team, but, like, when we developed a revenue feature, it was kind of thought of as being a part of the revenue product line that we. We actually didn't pull things in and out very often. There were some cases where we thought we could pull charge for something, and then we would look at the conversion data on that paywall and it just wasn't moving the needle. And so we would make it free, but we never. We never took something from that was free and made it a paid feature, as far as I remember. And I think in most cases, like, people overthink the, like, the user impact of a lot of these decisions where you can, like, if you make that decision to go free to pay, like, you can always reverse that decision. Or maybe you have, like, these moments of where the users are like, hey, like, I hate that you made this decision, but if you're solving a big enough problem, like, they're going to stick with your product, and so you just need to do so in a way that feels transparent and fair. Like, we always, like, overthought that things we were doing would have, like, a bigger, like, negative feedback than whether it's price or anything else. And we just always found that people were willing to stick with us as long as we gave them a core product that still provided value.
- [27:10]
A
Yeah. In our notes that we were working on ahead of the podcast, you wrote something about that I thought was really great. It was. We spent too much time building Excel features instead of testing ideas. And I assume that's what you meant. Like, you overthink things and run the models and price everything out and make assumptions and overthink instead of just getting out there and testing it. Is that what you're talking about?
- [27:35]
B
So we were a private company, and then we became a public company, and Tinder itself was the 90% of the revenue of that public company. And so it was actually a ton of pressure on us to perform every single quarter. So you basically had 12 weeks where you had to deliver some revenue growth, and if you didn't do that, literally, like, the stock price would go down. And everybody. Everyone was mad. Right. I think the Excel version of this was we just had more and more finance team members who wanted to help us forecast the impact of what we were doing. So then they could go to the next earnings call and give what would be a reliable forecast. But that created, I think, like, a bit of, like a Excel culture where the product team was forced to kind of like, spend a lot of time speculating on things that were hard to predict and so. Or we'd have things that would happen in the quarter that were small parts of our roadmaps going into the quarter that would work in a really big way that would make up for any kind of, like, inconsistent forecasting. So that was the biggest thing was we kind of. I think as your company gets bigger, the org gets bigger, you become a public company, the stakes get higher, and so you have to do things with more precision. And in some ways that can slow you down, for sure. Yeah.
- [28:59]
A
That's fascinating. We haven't had too many publicly traded companies on the podcast yet. Something I'm working on. I'm actually interviewing the chief product office for Duolingo is going to be an upcoming episode, so that'll be fun. But, yeah, imagine the pressure. Quarter after quarter. It's just a whole different ballgame than most people are used to. I did want to step back, and you kind of dropped a little something in there that I thought was really interesting. Is that because you were on the revenue team and the features were specifically designed for revenue, you said you would, like, test a paywall, and if those paywalls wouldn't convert, then you might make the feature free. So you were doing testing of, like, paid and then switching some of those to free. What would that look like? It would be like the paywall would very specifically highlight this new feature you built. And then if the conversion on those paywalls wasn't high, then you were assuming that that particular feature wasn't valuable enough to drive enough incremental revenue that then maybe it should just be pushed back into free. So that's how you were testing these things.
- [30:06]
B
Yeah. Like, pretty much every subscription feature had a paywall entry point that we had a dashboard we'd wake up to every day, and we could see the number of, obviously the number of clicks it got, and then look at the conversion rate and then map that to kind of like incremental revenue for the subscription product. And so you could see really quickly, like, which products were getting the most attention. And that could have been because, like, the paywall was position. Like, we always thought of this being like, real estate. And so you have a. A small canvas and a small amount of real estate. So maybe the problem is you don't, you're not showing the paywall in a aggressive enough way. Or it could simply be that people are topping the future and deciding that it's not valuable enough for them to pay for. I think the, what we kind of quickly learn is it's almost like like any like portfolio of companies or products. Like there's a power law to subscription features where one or two features are probably going to drive the majority of your new subscriptions and everything else is, is nice to have, but it's incremental. That could change. Like I'm seeing a lot more creativity with kind of like multi product revenue lines. And Ellicott, like Robinhood is a great example. It's not all subscription revenue, but I think they have 10 products that are independently generating like north of $100 million each. And so I look at that and. But at least when we were thinking about Tinder, it was a lot, a lot simpler. Like we had two to three power features that people really paid for and then we would try and design, you know, more features on top of those over time or new experiments. But it was pretty consistent. Yeah.
- [31:57]
A
One particular experiment that you mentioned was a single experiment that generated $50 million in revenue. Tell me about that one. I mean at Tinder scale, maybe that wasn't. And maybe you can fill in the details there, like how big the scale was. But tell me about that one experiment that generated $50 million.
- [32:18]
B
Yeah, so we probably in 2018, it was actually a really fortunate surprise, tested a toggle on the top of the application where you could enter a new subscription tier from the top nav bar and obviously like, you know, talk about real estate. That was a really premium piece of real estate within the product and people would tap on it and it was almost like, like we almost like discovered new real estate because the design team was really actually didn't want us to have that top navigation, which is always a tension by the way. Right. Like you have to have a beautiful product, but you also have to be creative in how you monetize. And so the really is like we always had a roadmap. It was like small, medium, large Excel experiments like everybody else. And I would probably say that was like a small to medium experiment. It was kind of a throwaway, a B test. And you wake up and you look at the dashboard I was talking about and you're like, wow, crap, this is, this thing is really working. And those moments are really fun. You can only like you get some of that when you're working at a Smaller company. I had the benefit and fully aware of how lucky I was to be working at scale with like 50 million monthly actives and a product that people were willing to pay for. So if you tried putting like a top knob into a meditation app, I'm not sure if it would convert as high as what we were doing. But the point is you should constantly be thinking about where users can access your premium features, where the paywalls are placed. And often I find people are just like, not thinking creatively enough. Like, you have a, maybe you have like something in the sun, like nav, like buried in your nav that people just can't access. And it always surprises me, like, I think, I think revenue team should be on the whole, like more, a bit more aggressive in terms of pricing and entry points because again, like, if your product's great, people are willing to kind of like go along for the ride.
- [34:19]
A
You brought up something in there that I wanted to talk about next anyway, and it is that like, balance the tension between creating a quality product and like caring about the users and the mission and things like that. But then also, you know, monetizing. And so it sounds like that $50 million paywall was attention in the company of the designers. Not wanting the top nav pitch. But how do you balance those things to keep the product quality up while still, you know, monetizing as effectively as you can and then in your, in your case, doing it while having quarterly pressure every 12 weeks to deliver?
- [34:58]
B
I think there was a great culture within our design team. We had a VP of design who understood that we were trying to design and build a beautiful product, but we also were trying to build a, a large business in the process. And so how, how we thought about it a lot was just like taking all the interactions and paywalls and putting as much love into those designs as we would any other product feature. And so I remember we, in 2017, we added like a animation to one of our paywalls. It's like this gold shimmer. It probably took a couple days of engineering time and, but people saw them and it, it was a well designed paywall. Right. Which I know is a. Not something that design teams want to focus on, but we were like, if we're going to show paywall, we want that to live up to the product, the core experience. And so we, we tended to like, over design the, the features that other people would spend less time on. And I think that at least showed the users that we cared about the experience. I see a lot of paywalls that look like they were designed and like by a pm and I just don't think that's how you maintain product quality. The other thing and I, I'll say like I've seen it more from a lot of products is, is you do start to get into the over optimization mode and you start to grind users and the product itself starts to feel almost like spammy where you have too many paywalls. And I think that just comes with a mature product that doesn't have enough pay room to kind of grow. And you know when you're a public company like you're, I think you can start to over monetize too. There's a trade off. I was lucky in my, in that role. I think I departed the company at the perfect time because we were still growing a lot and it wasn't kind of a more mature product. I don't think I would have been as good in like the current years at doing that job.
- [36:48]
A
Yeah, it does. It gets harder and harder as you mature, as the user base matures, as competition matures, as the industry matures around you. It does get harder. I did want to get to some of your more recent contrarian takes and one of them then is mobile isn't dead. And we've been hearing this since like I don't know, 2010. Mobile is dead. Mobile is dead. But you seem to think it's a great place to build today in 2025. Why do you think that?
- [37:14]
B
Every kind of platform shit has this like golden age where there's so much opportunity and white space within new categories that you can build and consumers almost like pull the product out of you. Right. And we saw that with mobile. Like I remember, I don't know in 2015 it's like you see a cool new product, an app and you're always willing to give that to go through the process of downloading and setting up. I think the people have become like a bit jaded on the consumer side as to try new products and a lot of the big categories have become obviously very mature products that are hard to disrupt. And so from a, I guess like an app developer perspective, I think there's been on the venture back startup side, less founders building like pure play mobile products over the past two to three years where I think there's a ton of opportunities. We have this new platform shift which is AI and so you can kind of reimagine new products I haven't seen personally and this is why I'm still bullish a ton of like net new, truly AI native products that are mobile first come to market. I think that's just because we're like now getting out of the infrastructure, build out to the application layer and the first part of the application. There was a lot of kind of like vertical AI, mostly web based products that obviously are doing well. And now I think we're finally entering the part of the market where founders will start to. There's enough infrastructure, there's enough kind of like experimentation. We'll start to see really cool either consumer products or mobile products for every category. So it could be things like, you know, commerce, travel, social, like you can kind of like canvas the app store the top categories and ask yourself like, okay, what if I redesign this product? Like what part of it could be net new if I did did it in more of like an AI native way. And so I think that's pretty cool. And I guess the last point is that we haven't gone out of this mobile design space where it's, or, sorry, the AI design space where it's like prompt to action. And so I think there's a lot of opportunity within the new wave of AI products, especially as we see like better memory and context, to reinvent a lot of mobile products that feel more personalized and feel more predictive of what we want to do as users.
- [39:38]
A
And I'll add to that too. I mean, 5 billion people a day are on their mobile phones around the world and they're more open than ever to pay for software. So it does feel like in addition to this platform opportunity where AI is coming in and allowing you to rethink things, you're able to rethink things in a very dynamic market. Sure it's competitive, sure it's hard, but when you succeed, it can succeed really big. And then you said very early in the podcast that there is an opportunity, and I totally agree with this, for apps now to be built in all these niches that maybe didn't make sense during the kind of quote unquote, golden age of apps a decade ago or whenever it was. So yeah, I mean, I'm sure you're being really bullish on the future and there's just so much opportunity in the space. What are your thoughts though on how AI might subsume apps and those opportunities? You know, flighty. An example, like at what point does ChatGPT have your calendar know when you're flying? Are they going to build this kind of stuff? Like what categories do you think are kind of more at risk of being subsumed by AI and then, you know, what areas do you think are safer to build in?
- [40:50]
B
Maybe, yeah, I think about it a lot. Like there's this belief that maybe in a future where AGI exists or, you know, advanced AI capabilities exist that there's like not going to be any interfaces. And I just think people love to be entertained. They like to be told what to do when they're using products and they like using products from people of strong opinions. And so if you are a designer or builder who has a point of view on what the product should look like and feel like, I fully believe that people still want to be, you know, showing a beautiful interface and a really efficient workflow and that we're not just going to have agents doing everything for us. I also think we're a very visual species. Like we when we're shopping or planning trips, like there's some things that you don't want to do in a interface that looks like a ID or developer environment. Like you again, like back to the entertainment idea. Like a part of this too is just like we love to have a sense of control and to kind of go on that journey. Whether you're buying a new pair of shoes or you're planning a summer trip. I also just think people might have more free time. And so again, what do you do when you have free time? You're probably going to be using your phone a lot more and doing things that are a lot more entertainment focused. And so I'm not at all worried about the end of apps. I think the bar for design and product will get higher and higher. And that's a great thing because you have, you're going to have a lot of this like AI driven product design and then you're going to have real professional design that rises above and there's a like a really clear zeitgeist right now which is like the anti slop zeitgeist and people wanting things to use things, whether it's in the physical world or digital world that are high quality and thoughtful and well designed. So I think if anything doubling down on product and design and user experience will separate people from kind of like the general purpose super apps. And sure, I could track my travel on ChatGPT, I could probably already do that. But Flighty is just such a compelling product that I'll stick with that.
- [43:13]
A
Relatedly, one of your other kind of contrarian takes is that there are more apps and companies than there are great ideas and that maybe more people should be working together instead of on separate apps and Maybe that's to this point it's like because the bar is raised. Instead of being a solo founder or just hacking it out by yourself, finding other top people to build with might help you achieve that level of quality.
- [43:38]
B
Yeah, I read this quote. It was like it's easier to raise money for a startup than to get like a engineering job at a top company these days. So there's a lot of company creation and there's a dispersion of talent that I didn't have, at least early in my career. I think the, you know, like, I remember the days when like the Snapchat team was so talent rich, like you know, top to bottom, it was almost like an all star team of mobile consumer talent. And I think now the incentive to start a company and to do things on your own has created a lot more companies than we need to exist. And I'm hopeful that people start to like, talent consolidates and we have really great smaller teams working together. You see a lot of the, a lot of the big, like the incumbents, The Facebooks, even OpenAI have really great talent across the board and they're just able to pay a lot more money obviously for that talent. I'm hopeful that we have like these groups of, you know, younger talented entrepreneurs who agree, like, hey, it's better if we're going at a problem and maybe you have a competitor going after the same problem, like maybe you should team up and do it together.
- [44:48]
A
Yeah, I think that's great advice. And it's tough because there's so many, I see so many developers, you know, get to, you know, 2K in MRR and 5K in MRR. And I do wonder if like a group of two or three of them or you know, somebody more product oriented, somebody more design oriented, somebody who's just like the hardcore developer, if as a team they could kind of break through that wall instead of everybody thinking they need to just do everything and be everything. So yeah, maybe, maybe that's a good challenge to folks listening to the podcast. Like if your side project hasn't taken off, maybe you need to collaborate more and find some, some talent to work with instead of thinking you have to do it all.
- [45:28]
B
I mean, it's definitely like I see these apps and these stories of people getting to a couple million subscription revenue as like a one or two person team. And it's really cool that that's a possibility. And so I think about that a lot, just personally, like, could I, you know, if I wasn't a vc, could I pull that off. And what would that be like? I think for me personally, like I want to do things at scale and so that went kind of like satisfy me. But I can see how that would be for a lot of people, like a really great career option. It just depends on the personality and kind of what you want to do with your career.
- [46:03]
A
Well, I think now's a good time to kick off the lightning round. I call it the lightning round, but you don't have to. We can have a discussion around these. It's kind of a loose thing I've started putting here. At the end of the podcast, the questions are more focused on operators, so I'll ask this in a different way for you, but the question is generally, what's your biggest win of the year? So for you maybe it's a portfolio company, a biggest win a portfolio company had or just something you think people could learn from that you saw in the past year?
- [46:31]
B
Yeah, I think for us on the investment side, we were pre seed investors in Supabase, which I think the company's done an incredible job of really leaning into what's happening in AI and becoming like the database of record for most major website builders. They've done so by being extremely developer driven. Like the speed at which they ship features, they ship a new feature every single day. And so they, I think they set the bar for what product velocity should look like and just appears like, like they won't slow down. Personally, I think the thing I've love doing is I've gone back to even as a vc, designing new products. And so we have a incubation which we'll be able to share next year, which was it has been a ton of fun to work on because it's been back in the Figma files and getting like really deep in product design, which as an investor helps me stay sharp. Like I don't know how I could do this job and not still build things and create things. And then we have another product that we're releasing in the next couple of weeks which is more like a venture scale product. That's just something that we're having a lot of fun building. So I think the lesson for me is like I like all my energy that I get is through building things and building products and investing. But I really need to build things to be happy as an investor too.
- [47:57]
A
That's fun and it's interesting you bought up Supabase. I do think this podcast is very focused on building consumer subscription businesses, but some folks in our audience might think about buildings of B2B. Like what, what things are you frustrated with in the experience or what holes are there? What gaps are there in the, in the experience of consumer developers? And where could you fill and Supabase? It's crazy how big they've grown and how quickly they've grown by filling one of those needs for the market that already seems saturated. So it's pretty fascinating.
- [48:32]
B
Yeah, I think a lot about just like day one problems that every developer faces and so you know, like authentication, picking a database. We were early investors in Mercury, which is a bank for startups like these day one decisions and there's always going to be new pain points to solve there and then as it relates to the developer experience, like as you're building your subscription products, I'm sure there's a million pain points that you have every single day. And I found software when I was operating to be like highly, highly inefficient. From design through product work to engineering deployment, post deployment there's so many bottlenecks and luckily I think we're in a moment in time where all that's being kind of remixed in terms of the functions and the workflows. And so I think there's a lot of opportunity to we call it like the software factory. But if you think about the engineering cycle and the production cycle of software to really lean into what is changing today and build new either B2B tooling or infrastructure for those new problems.
- [49:40]
A
Yeah. And at RevenueCam we're trying to solve a lot of those pain points and increasingly building out new products and stuff. But there's still just so much white space in the industry and to our point earlier about consumer, there's also space to think what's the AI native version of solving this pain point? What's the AI native version of solving authentication or other problems like supadase did for databases. The next question is what was the biggest fail of the year or portfolio company that you saw run? A maybe one of the big fails was not doing pricing experiment or packaging experiment for that one portfolio company but any other big fails that you think.
- [50:19]
B
Folks could learn from biggest failures always come back to product velocity. And I think there's a ton of pressure right now, especially within the venture backed startup world to ship things that are of a very high quality on day one. And so the you know like I've heard this like idea that kind of like iterating your way to product market fit and like that whole exercise is almost like we've kind of gone back to like a world where you are shipping extra large day one products. And so I see, I see some founders who are like stuck in their own heads or organizations as to when they should shift their product and almost waiting too long and the markets are moving so quickly that if you wait too long today, someone else is going to come in and take that market. For me, I think we have to get back to a lot more experimentation at the application layer and be willing to kind of make mistakes and not, not having to. To kind of like have day one perfection.
- [51:24]
A
Last question. Growth would be easier if I think.
- [51:28]
B
Growth would always be easier if you had like better day one data and data systems in place. We've, you know, I think a lot of the. Even up until like I left Tinder, a lot of the business intelligence questions and data questions were still very hard to kind of pull. Like we obviously like a lot of us knew how to use SQL and could good to run queries but I think a lot of the actually like I've thought a lot about this for this moment we're in in terms of like can you use AI to basically like recreate things that revenue teams can do really well in a more efficient way. So things like understanding your, your funnel better, really knowing kind of like what on the road you said like, like pricing, localization, like all these things were actually really hard for us to, to solve for. I think are easier today. And so growth would be I think a lot easier if we really lean into this like AI moment and tried to rethink the way we operate revenue teams as an industry.
- [52:30]
A
Such a great place to wrap up. Anything else you wanted to share as we wrap up?
- [52:34]
B
Yeah, if you're building a company that's venture back like would love to hear more. I'm JMJ on Twitter, so you can also follow me. I'm pretty active online. Like I want to share as much as I can about what we're doing. So follow me there and lot of space you can find me is substacks. I run a publication called the New Internet, which I spend a lot of time on as well.
- [52:55]
A
Awesome. We'll link to both of those in the show notes. But thanks so much for your time. This was a really fun conversation.
- [53:01]
B
Thanks David.
- [53:04]
A
Thanks so much for listening. If you have a minute, please leave a review in your favorite podcast player. You can also stop by chat.subclub.com to join our private community.