# From Tinder to VC: Jeff Morris on Product-Market Fit, Monetization, and AI-Driven Growth

Channel: Sub Club by RevenueCat
Video: https://www.youtube.com/watch?v=5qWhNLUR3MA
Duration: 53 min
Language: English
Words: 9935
Transcript page: https://viewrankai.com/tools/youtube-transcript/5qWhNLUR3MA

---

[0:00] 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're going to have a lot of this like AIdriven 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 the anti-slop zeist and people wanting to use things whether it's in the physical world or digital world that are high quality and thoughtful and doubling down

[0:30] on product and design. Hello, I'm your host, David Bernard. My guest today is Jeff Morris, former VP of product at Tinder, now founder and general partner at Chapter 1, 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 payw walls can

[0:56] mislead you about product market fit. Hey Jeeoff, thanks so much for joining me on the podcast today. Yeah, excited to be here. So, you tweeted a few weeks ago, a banger of a tweet, and immediately afterward, I was like, I got to get you Jeff on the podcast. I I think I had DM'd you in the past about coming on the podcast. Um, but we finally made it happen. And so, I wanted to kick it off with that tweet. So, the tweet I think for to some people might be a little

[1:22] controversial in 2025. Love that. 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. Yeah. So, I guess like a bit of background before I go into the tweet is I ran revenue at Tinder for 4 and a half years through kind of our hyperrowth years. And so, I spent a lot of time thinking about monetization,

[1:46] subscriptions, and revenue obviously. And what worked at Tinder and when we really started to kind of like turn on monetization didn't happen till year years four or five um into the product. And so we had built just a a great product that had extreme product market fit. We had scaled the product to you know like 30 to 40 million monthly activives 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

[2:25] retention to kind of earn the right to to build a subscription business or monetize through inapp purchases or 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 have changed and so the revenue slopes are much more extreme but you're seeing teams now focus on monetization really on day one as a 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

[3:13] monetization earlier in the funnel. And what's really interesting too from that perspective is you're seeing a lot more testing with 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 um like it was always hard to monetize a user base. But the packaging and cadence of a subscription road map I think was a bit easier when I was operating in 2015 to 2020. We now

[3:57] invest in a lot of applications and I meet with the teams and hear their list of 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 we're thinking about. So whether it's mobile or um or kind of like B2B SAS or anything bottoms up on

[4:19] 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 uh celebrating around revenue today like which I would say maybe is a bit premature because you see either on Twitter or within pitch dejacks like the front page is hey we got from like 0 to 10 million in 3 months or 6 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

[4:52] 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 companies coming back to fund raise where the the numbers don't look quite as as advertised. 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 is 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

[5:34] with a hard pay wall 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 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 premium 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

[6:11] 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 premium 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

[6:52] hints of it. you can look at autorenew status and stuff like that. Um, but any kind of additional advice or thoughts on like who should be trying that free 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.

[7:12] It's very much depends on the category. If I was building an app today and um 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 um it's a really popular product within its segment but the challenge they have with premium 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

[7:51] their premium 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 to kind of make that happen. Like there's not a payoff of a successful outcome before you're asking

[8:15] 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 to become a paying subscriber. And so I would almost focus less on total like subscription number

[8:51] in terms of users then 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 like whalriven 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

[9:14] people complain about on on Twitter. Yeah. And I 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 U, but he's been talking a lot about how he thinks um Chat GBT 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 chat GPT have never gotten to experience thinking pro or deep research because

[9:44] those aren't available on the free tier. And so they don't even know what chat GPT is even really capable of because they've never paid. And so it's kind of to your point, it there is a little bit of a um not chicken before the egg, but it's it's like you you want your 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 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

[10:21] 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 um before they pay and and maybe CHIPT is at a scale where it it's okay and they the revenue grown tremendously, but it's a it's a tough balance. I mean, what are your thoughts on like how to balance that that like putting good stuff behind the payw wall but still providing the best possible

[10:45] experience? Yeah, I think it's 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 um you 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 the cost requirements as as opposed to,

[11:18] you know, a 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 better experience because they can either subsidize a premium 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 playbook. So I think it's it's probably good to look at the world like between u call like AI native comput inensive companies versus

[11:54] the rest of if you're building continder or a headsp space or something similar you it's kind of like the classic playbook and and you don't have to worry as much about these new questions that I think founders are are trying to figure out. Yeah, it it is tough when things are expensive. And I'm 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 the product retention, and then monetize down the road. For some companies, that is the optimal path. But

[12:35] raising money in 2025, [laughter] unless you're an hot AI startup, is is challenging. So, what are your thoughts on 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 bootstrap and do have to make these really tough trade-off decisions. I mean, my my weather app that I work on on the side,

[12:56] 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 pay wall 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 premium experience yeah I think the um venture market is treating nonInative apps as almost like a non-investible category which I think is pretty busy because we all know that

[13:34] mobile use usage and adoption is growing year-over-year. I think the knock on mobile apps is just people there's a 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 to 2020 period. I think now is a great time to build a like a hyper premium mobile experience for every niche imaginable. the cost to build an application and 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

[14:15] amazing job and um 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 pay wall and willing to pay, you know, 40 bucks a year expensive to your business or whatever it is because it's such a 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

[14:54] you're building a product that people will pay for and you should ask people to pay for it and see what the responses and I'm a big fan of monetizing early. Yeah. In that sense. Yeah. And you know, Flight is an interesting example. It may have been that you um used it at a time when it was a more of a hard payw wall, but he was actually recently on the launch podcast, which is kind of a sister podcast to this. And they have been experimenting and he was actually on Ben

[15:23] 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 if I remember correctly some premium features then get locked after the first flight. And so it's just we 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

[15:59] 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 in his way into this like weird kind of fremium where he does yeah that's almost like a like almost like a trial to me. Um, yeah, premium is like in my mind I the

[16:17] definitions could be entirely different. It's 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. Yeah, that that may be a

[16:42] good example for highcost 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 Chat GPT has or should experiment with is 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

[17:12] 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 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. 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 premium experience to kind of offset the cost of it uh while still

[17:40] kind of giving that better experience. 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 um within those orgs yet. And so like we have a portfolio company that's I won't say the name but they hit 50 million in in AR within called a year with a proumer product and I called the CEO and I was like hey this is really interesting like what are we doing on um pay wall optimizations and pricing and I started to like put my revenue hat on and he was like what like just like what

[18:19] 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 uh 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 like built out the revenue team it was 20 16 about a year into my my time at Tinder and you know it's just like

[18:54] myself and call like five or six engineers right you had like three iOS engineers and three um uh Android engineers then leaving the company was you know I think I had like 40 plus engineers who were working on all parts of the revenue road map um 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 like the 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 like really refining that part of their product. So,

[19:28] I think it can lead to again even more false positives or metrics that might not prove to be durable over time. 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." Yeah, I think it was mainly around kind of like packaging and so they had a single subscription tier and 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 like

[20:02] the like the intra subscriber who's probably younger and has less income and maybe isn't in the US to like the most uh the largest whale you can imagine, right? someone who can spend like $50,000 a year on a subscription product, which we had at Tinder. But that you're you're building for such different customers, right? But that just takes time to figure out because you're 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. Um, and you could do that forever. like that's why revenue teams are do what they do every

[20:46] day. And then and the other the other one that um 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? Um so knowing like our fastest growing markets were Ladam and India but those markets had a very different willingness to pay to a North America or UK or something similar. 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 Robbie Meta on

[21:27] the podcast. So, what's funny is like he got to build that really cool chart with like the, you know, uh, higher price tier, the mid-pric 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 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

[21:57] 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 um to fit those demand that demand curve and the need of the users? 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

[22:35] 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 and forget it. where we really started to 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 and LAM which were growing but weren't necessarily the places where we were monetizing really well and so I'd say when you start when should you start focusing on pricing I'd say like really focus on your core markets and you know for a US app developer

[23:07] generally speaking unless you're building a international specific app like that's going to be the North American 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 to what they want you to build and then the question as a product person is always is that something we should monetize or or give away for free. In the case of of Tinder, which was specific to dating as a category, there was a a certain element of, hey, we're building a network and ecosystem where if we give away everything for

[23:42] 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 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 a payw wall 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

[24:18] sessions and so or you had things like auto swipers and so um we put up that payw wall to also to create a better ecosystem but it 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 to build. Um, and we always thought of these things as being like superpowers that you could give the user and obviously like you um not everybody

[24:49] can have the full access to the superpowers because then the those features will become less valuable to the the subscriber base. Yeah, that's fascinating. Yeah, thinking of it as 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

[25:14] revenue of pulling features in and out? So, would you like put something in the free tier and then oh wait, like we really should have made that paid. How did you run those sorts of experiments? cuz those are hard and you know once somebody's gotten something for free then putting it behind the pay wall is weird and then oh I paid for that why is that now free how did you run those kind of experiments 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

[25:48] team but like when we developed a revenue feature it was kind of thought of as being a part of the revenue new product line that we we actually didn't pull things in and out very often. There were some cases where we thought we could charge for something and then we would look at the conversion data on that payw wall and it just wasn't moving

[26:08] 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. 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 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

[26:39] that feels transparent and fair. like we always like overthought um 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 to stick with us as long as we gave them a core product that still provided

[27:00] value. Yeah. And in our notes um that we're working on ahead of the podcast, you wrote something about that I thought was really great. It was uh we spent too much time building Excel features instead of testing ideas. And I assume that's what you meant like you you're overthink things and uh run the models and like price everything out and make assumptions uh and overthink instead of

[27:22] just getting out there and testing it. Is that is that what you were talking about? So we were a private company then we be 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

[27:59] what we were doing. So then they could go to the next earnings call and and give a uh what would be a reliable forecast. But that created I think like a a bit of like a a Excel culture where the product team was forced to kind of like um spend a lot of time speculating on things that were hard to predict. And so um or we'd have things that would happen in the quarter that were small parts of our road maps going into the quarter that would work in a really big way that would make up for any kind of like uh inconsistent forecasting. So that was the biggest

[28:35] thing was we kind of I think as your company gets bigger, the word gets bigger, you become a public company, the stakes get higher and see you have to do things with with more precision and um in some ways that can slow you down for sure. Yeah, that's fascinating. I I we haven't had too many publicly traded companies on the podcast yet. something I'm I'm working on. We're I'm actually interviewing the the chief product officer at Dualingo. It's going to be an

[29:00] upcoming uh episode, so that'll be fun. But yeah, imagine the pressure quarter after quarter. It's just a whole different ballgame than than most people are used to. Uh I I did want to step back and 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 you said you would like test a payw wall and if those pay walls 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 what would that look

[29:34] like? It would be like the payw wall would very specifically highlight this new feature you built and then if the conversion on those pay walls 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 is so that's how you were testing these things. Yeah, like pretty much every subscription feature had a payw wall entry point that we had a dashboard we'd wake up to every day and we could see the number of of obviously like the number of clicks it got and then look at the conversion rate

[30:13] 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 um attention and that that could have been because like the payw wall was positioned like we always thought of as being like real estate and so you have a a small canvas and a small amount of real estate. is maybe the problem is you don't you're not showing the payw wall in a aggressive enough way or it could simply be that people are in the future and deciding that it's not valuable enough for them them to pay for. I think the what we kind of quickly

[30:52] learn is it's almost like uh it's 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 um revenue lines. And I look at like Robin Hood 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

[31:32] Tinder, it was a lot a lot simpler. like we had two to three power features that people really paid for and then um we would try and design you know more features on top of those over time or new experiments but it was pretty consistent. Yeah. One particular experiment that you mentioned was uh a single experiment

[31:52] that generated $50 million in revenue. Uh 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. Yeah, so we um probably in 2018, it was actually a really fortunate surprise. Tested a a toggle on the top of the application where you could enter a new

[32:20] subscription tier from the top navbar. And obviously like you 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 like didn't want us to have that topnav 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 was like we always had a a road map as like small, medium, large XL

[32:54] experiments like like everybody else. And I would probably say that was like a a small to medium experiment. It was kind of a throwaway AB test. And you wake up and you 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 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 activives and a product that people were willing to pay for. So if

[33:27] you tried putting like a top knot into a meditation app, I'm not sure if it would convert as as high as as what we're doing. But the point is you should constantly be thinking about where users can access your premium features, where the pay walls are placed. And often I I find people are just like not thinking creatively enough. Like you have a uh maybe you have like something in the some like nav um uh like buried in your

[33:53] nav that 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. 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 payw wall was a tension

[34:28] in the company of the designers not wanting the topnav pitch but h 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 a quarterly pressure every 12 weeks to deliver. 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

[35:07] and payw walls 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 payw walls. It was like this gold shimmer. It probably took a couple days of engineering time and but people saw them and and it it was a well-designed payw wall, right? which I know is a um not something that design teams want to focus on, but we were like, if we're gonna show a payw wall, we want that to live up to the product, the core experience, and and so we we tended to

[35:39] like overdesign the the features that other people would spend less time on. I think that at least showed the users that we cared about the experience. I see a lot of payw walls that look like they were designed in 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 overoptimization mode and um you start to grind users and the product itself starts to feel almost like spammy where you have too many pay walls and I think that just comes with a

[36:14] mature product that doesn't have enough room to kind of grow and and you know when you're a public company like you're I think you can start to overmonetize too. There's a trade-off. I was lucky in in my in that role. I 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. Uh I don't think I would have been as good in like the current years at doing that

[36:38] job. 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. Uh it does get harder. I did want to get to uh 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? every kind of platform has this like golden age where there's so much opportunity and white space within new categories that

[37:14] 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 signing up I think the I think 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 like 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 ventureback

[37:48] startup side less founders building like pure play mobile products over the past 2 to 3 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 so bullish a ton of like net new truly AI native products that are mobile first come to market. I think it's just because we're like now getting out of the infrastructure buildout to the application layer and the first part of the application layer was a lot of kind of like vertical AI mostly web- based products that that obviously like like

[38:30] 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. 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

[39:05] 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

[39:27] users. And I I'll add to that too. I mean 5 billion people a day are on their mobile phones around the world. Uh 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

[39:47] 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 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 I share your you're uh being really bullish on the 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

[40:23] example like at what point does chatpt 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 are safer to build in 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

[40:59] products and they like using products from people have strong opinions. And so if you are a designer or builder who has a 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, shown 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 um 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

[41:38] idea like a part of this too is just like we love to have a sense of control and to to kind of go on that journey whether you're buying a a new pair of shoes or you're planning a summer trip. I also just think, you know, people might have more free time. And so, again, what do you do when you have free time? Like, 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

[42:11] and higher. And that's a great thing because you have you're going to have a lot of this like AIdriven 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 um are high quality and thoughtful and um well designed. And so I think if anything, doubling down on product and design and and user experience will separate people from kind of like the general purpose super apps. And sure, I could track my

[42:55] travel on chat GPT. I could probably already do that, but Flight is just such a compelling product that I'll stick with that. 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 may maybe that's to this point. It's like because the bar is raised instead of being a solo founder just hacking it out by yourself, finding other top people to build with might help you achieve that

[43:27] level of quality. Yeah. I read this quote. It was like the 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 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 of mobile consumer talent. And I think now the incentive to start a company and to do things on your own has

[44:01] 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

[44:37] together. Yeah, I think that's uh that's great advice and it's it's tough because there's so many I see so many developers, you know, get to, you know, 2K and MR and 5K and MR. And I do wonder if if like a group of of two or three of them or, you know, somebody more product oriented, somebody more designoriented, 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. Um, so yeah, may maybe that's a good challenge to folks listening to the podcast. Like if your side project hasn't taken off,

[45:12] maybe you need to collaborate more and find some uh some talent to work with instead of thinking you have to do it all. I It's definitely like I see these apps and these stories of people getting to a couple million 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 like 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 uh that wouldn't kind of like satisfy me but I

[45:46] can see how that would be for a lot of people like a really great career option. It just depends on the personality and and kind of what you want to do with your career. Well I think now's a good time to kick off the lightning round. I call it the lightning round, but uh you don't have

[45:58] we can have a discussion around these. It's kind of a loose thing. Uh I've started putting here at the end of the podcast. Um 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 um or just something you think people could learn from that you saw in the past year. Yeah, I think for us on the investment side like the we were preede investors in Suba Base which I think the company's done an incredible job of

[46:31] really leaning into what's happening in AI and becoming like the database of record for most major website builders. um they've done so by being extremely developer dri 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 loved doing is I've gone back to even as a VC designing new products and so we have a incubation which will be able to to share next year, which was a has been a ton of fun to work on because it's

[47:15] been back in the Figma files and getting um 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 weeks which is more like a venture scale product, but it'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 and investing, but I really need to build things to be happy as an

[47:46] investor, too. That's fun. And it's interesting you brought up superbase. I do think you know this podcast is very focused on building consumer subscription businesses but some folks in our audience might think about building some 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 superbase 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

[48:20] it's it's pretty fascinating. 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 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

[48:47] points that you have every single day. And I found software when I was operating to be like highly highly inefficient from design through you know product work to engineering deployment post- deployment like 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 those new

[49:29] problems. Yeah. And at Revenue Cat, I mean, we're, you know, we're trying to solve a lot of those pain points and increasingly, you know, building out new products and stuff, but is there's still just so much white space in 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 painoint. What's the AI native version of solving authentication or, you know, other problems like Super did for databases. The next question is what was the biggest fail of the year or portfolio company that you saw run a run a maybe maybe one of the big fails was

[50:03] not doing pricing experiment or packaging experiment for that one portfolio company but any other like big fails that you think folks could learn from biggest failures always come come back to product velocity and I think there's a ton of pressure right now especially within the venturebacked 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 uh iterating your way to product market fit and like that whole exercise is almost like uh we've kind of gone back to like a world where you are shipping extra-large day one products

[50:40] and so I see I see some founders who are like stuck in their own heads or organizations as to to when they should shift their product and almost waiting too long and And the markets are moving so quickly that if you wait too long today, someone else is going to come in and and and take that market. For me, I think I think like we have to get back to a lot more experimentation at the application layer and and be willing to kind of like make mistakes and not not having to to kind of like have day one

[51:13] perfection. Last question. growth would be easier if I think 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 could 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

[51:51] recreate things that revenue teams can do really well in a more efficient way. So things like understanding your your funnel better, um 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 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

[52:18] we operate revenue teams as an industry. Such a great place to wrap up. Anything else you wanted to share as we wrap up? Yeah. uh 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 at Substacks. So I run a publication called the new internet which I spend a

[52:44] lot of time on as well. Awesome. We'll link to both of those in the show notes. Uh but thanks so much for your time. This was a really fun conversation. Thanks David. 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

[53:04] to join our private community. [music]

---

About this transcript
Read from YouTube's own caption track and laid out by ViewRank AI (https://viewrankai.com).
ViewRank AI finds the videos already beating a creator's own average on Instagram, TikTok and YouTube Shorts, transcribes them from the audio itself in more than 60 languages, and turns what worked into new ideas and scripts.
Free transcript tools, no account needed: https://viewrankai.com/tools
How to read any video this way: https://viewrankai.com/llms.txt