David Barnard: Hello, I'm your host, David Barnard, and with me today Revenue Cat, CEO, Jacob IDing. Our guest today is Ravi Metta, former chief product Officer at Tinder now working with high growth consumer and AI startups as a hands-on product advisor on the podcast, we talk with Ravi about subscriptions as a force multiplier for consumables, why narratives matter more than metrics in goal setting and why you might want to try a longer onboarding or a shorter one. Hey Robbie, thanks so much for joining us on the podcast today. Yeah, Ravi Mehta: Thanks so much for having me. I'm excited to be David Barnard: Here. And Jacob, always nice to have you as well. Jacob Eiting : I'm back. I'm here. It snowed three inches today, David, on November 8th or whatever day it is. It's crazy. It's upset. Nice. David Barnard: I'm in Texas and it almost froze last night. So what, you're out in San Francisco, Robbie, so you don't have any I'm actually in LA. It was like 80 degrees a few days ago. Yeah. Jacob Eiting : Wow. Sorry, what a country. What a David Barnard: Country. It was 80 degrees yesterday and then it got dropped. So anyhow, onto subscription apps. So I wanted to kick things off with this chart you created from your experience at Tinder. And I've talked about this chart so much. I've called it your famous chart because I've just obsessed over this chart ever since I first saw it, and it's always hard to talk about charts on a podcast. So for the video podcast, we will see if the production team can actually overlay this chart. But for those listening along, you might want to just pause and go to the show notes and link to this chart because I think having the visual in your head is actually going to be super helpful to understand what we're talking about here. So on the X axis is number of paying users. On the Y axis is willingness to pay, and the idea is you want to fit this demand curve. So what Tinder did so beautifully is that with the Tinder Plus product, it was a lower price product. So you had a lower willingness to pay, but you had way more users who were willing to pay that amount. Then for Tinder Gold, you have a higher willingness to pay higher price product, but then it's fewer users who are willing to pay. And then Tinder Platinum has the highest willingness to pay the highest price point, but the fewest number of users. But the beautiful thing is creates a nice share step where you meet people where they are on the demand curve, how much they're willing to spend. And then the thing about Tinder and what Tinder did so well is that you also layer consumables on top of that. So the super likes and other consumables fit that demand curve even better because on top of each of these subscription tiers you can actually spend more money. So I've described the chart, but tell me about why you created the Chart and how you thought about this at Tinder to even create the chart and the conversations that led to this even becoming Tinder's monetization philosophy that then became the chart. Ravi Mehta: Yeah, definitely. So the idea behind the chart is it's very similar to a lot of the charts in economics 1 0 1 where you have a demand curve and then you're just trying to figure out how to price things, and as price goes up, demand goes down. So that's the theoretical model. The thing that happens very concretely in practice is if you have one subscription tier at one price, we know there's two buckets of users that don't get their needs met. There are users who just can't afford the price. If it's $30 a month or they don't want to pay the price, there's a whole bunch of users who might have some willingness to pay that you're actually not going to capture because they're not willing to go to $30. Maybe they'd be willing to spend $10 or $20, but you're just not going to get them as customers. And then the other thing that people don't think about enough is that you have a bunch of people who are willing to pay $30 within those people. There's a whole bunch of people that are willing to pay $50 or $60 to, you're leaving money on the table on both sides of that subscription. And so what you can do is you can add additional subscription tiers, maybe a lower price subscription or a higher price subscription, and then you can partially address the problem, but you still have this open space. You still have in between the subscriptions, there's these cracks of people that have a higher willingness to pay or a lower willingness to pay whose needs aren't met, and that's where a la carte purchases come in. And so in addition to having, you can have maybe two or three subscription tiers, going beyond that is going to be two complicated. You can also have microtransactions so people depending on what they need can purchase as much or as little as they want, and that allows you to get to a much more perfect price discrimination. And so this combination of a subscription set of tiers as well as Microtransaction products turns out to be one of the most optimal ways, especially within consumer to price your product. It works really well in dating. Tinder's really proven that it also works incredibly well in gaming, and we've seen now a lot of game companies have moved to this idea of having a subscription as well as having all of these things that you can purchase within the game. Jacob Eiting : Do you think the benefit of having the subscription is just like it sort of recurringly fills half of that demand curve area, right? Because in theory if you didn't have those sort of recurring commitments, you could fill that all with consumables, if that's truly where the demand curve is. Do you think it just generally raises the spending under the curve or what's the interplay there? Ravi Mehta: Yeah, I think it's just a good single subscription is just a really good threshold monetization point where there are a whole bunch of users who are willing to pay that amount. And so by framing the price there, by getting people to think about the value in that way, you can move a significant set of free users over to the paid side in a way that is very predictable. That's another thing. From a company standpoint, subscriptions are really nice in terms of the predictability of the revenue. The challenge with having a microtransaction only approach, which theoretically should actually be perfect price discrimination because people buy as much as they want, but in reality the psychology of it is if people have a need one month, they'll spend more, they have less of a need, they spend less, and then that leads to this kind of up and down for you as a business that you need to manage through. And so subscription is a nice way to kind of ratchet that up and say, okay, there's this kind of flat rate that we want to get people into. It's good for them because getting a ton of value each month, it's good for us, it makes our business more predictable. And then you can use additional tiers or additional microtransaction purchases to kind of fill in the business model from there. David Barnard: Does Tinder have a free tier? I haven't used it enough personally as a happily married man. And how do you think about the free tier in relation to this? Ravi Mehta: Yeah, actually that was one of Tinder's innovation. So dating in the very early days with Match, any Harmony was paid only in order to be a member of the site. In order to match with people, you had to be a paid member. And there were a couple of companies that innovated around free to play dating. The first is okay Cupid and the second is Plenty of Fish. Both of them saw really fast user growth because essentially they pull down any friction, they get a much larger number of people into the product, and that's always great when you have a product that has network effects, you want as many people using it as possible. Tinder came in and said, okay, we're going to do the same thing. We're going to have a free to play product. About 85 to 90% of users are entirely free, so there's very little friction to get started. There's lots of people that are on Tinder that are swiping on each other, that are messaging with each other. So it's a really vibrant ecosystem from that standpoint. And for a subset of those users tend to 15% who want to get more out of this experience, who want to be able to match with more people who want to be able to match with less effort they're willing to pay. And that's where the subscription tiers and the microtransactions come into place. And that's I think one of the most interesting questions for consumer app builders right now is do you want to have a free tier? Do you want to have a limited pay trial or do you want to not have any trial at all? Do you just want to have people come straight in and pay right away? And depending on what your product is doing for people and the psychology associated with that and the network effects associated with that, the right answer for one company may be totally different than the right answer for another company. Jacob Eiting : It doesn't work without a lot of people. Right? A hundred percent. So you don't want to gate. It's actually interesting to me that, and I'm sure there's probably reasons this works, but so many dating apps were fully paid on both sides of the network. It seems like it would really limit your network effects, be able to get, maybe it works in big cities, but anywhere outside of that would be really tough. You'd have just tough meeting supply and demand, I would think. Ravi Mehta: Totally. And there's an interesting thing there where Tinder needs as many people as possible, and then broadly, there's two categories of people. There's people that are getting a lot of swipe rights and there's people that are not getting a lot of swipe rights that tends to break down on gender lines. So women get a lot more people swiping on them than men do. And because you have these two different characteristics of people within the system, it's important to be free so that the people who are in demand, the people that others want to swipe right on are incentivized to come into the product and don't have to pay to be there Jacob Eiting : For payers, it's predominantly men on Tinder, Ravi Mehta: It is predominantly men. It's a little bit more balanced on Hinge and a little bit more balanced on Bumble, but the needs of someone who's getting a lot of people swiping right on them and the needs of someone who's not getting as many people swiping right on them are very different. And the Tinder paid products tend to focus on people that are not getting a lot of swipes, so they're things like boosts and super likes which help you get more matches. Whereas Bumble, for example, has products for people that are getting a lot of inbound attention to help them kind of filter and sort. Jacob Eiting : I was going to ask if Tinder ever considered bifurcating their products for which side of the supply to demand curve you're on, right. Ravi Mehta: Yeah, I think there's an interesting and really significant opportunity there. Tinder hasn't really been able to land it yet. Bumble I think has landed it much better because they've been focused on the female user ever since inception, and that's part of their brand. And I think Hinge has done a really nice job of saying, Hey, we're focused on people that are here for serious relationships across genders, and they have a more, I think, broad set of products. Jacob Eiting : It's like hiring market tools. There's all these tools out there to help you apply to jobs. And then there's on the other side, there's all these SAEs to help you filter out the always it's money to be made at on every side of the market. David Barnard: To Jacob's point earlier about not having the subscription, and I should have known Tinder had a free tier, but do those free users then spend on consumables and is that a significant part of monetization? Is having this free user spend on consumables and then do you monetize them any other ways like ads? Jacob Eiting : I don't know if this is on purpose or not, but interestingly, there's a little chunk on the value demand curve here where right of the cheapest subscription there is actually no IAP or no consumables, Ravi Mehta: So I didn't do that deliberately, but it is the case that very few free users actually buy micro transactions. It tends to be that these subscriptions are kind of force multipliers for the micro transactions. Jacob Eiting : Obviously there's probably 10 times as many or nine times as many free users as there are subscription, but it'd be interesting to see if they still don't generate a meaningful amount of volume. Ravi Mehta: I think part of it is a product value problem. So the two main micro transactions that you can buy are super likes and boosts, both of which help you get more matches. And then the main thing you get from Tinder Gold is you can see who's swiped right on you. So the two products work together, you can get more people to swipe right on you and then you could see who's swiping right on you. And those work together to get you more matches. And so if you don't have Tinder Gold, the value of those Microtransaction products is a lot less. Jacob Eiting : I would also imagine too, if your entry level subscription product price point is pretty low, there's probably not a whole lot of people to the right of that. You know what I mean? That are like, oh, it's 4 9, 9 a month too much. I got to pay a dollar a month or whatever. There's probably not a ton of volume there, Ravi Mehta: A hundred percent. And then that cheaper tier is meant to be an on-ramp, find people that are willing to jump the penny gap, get them into a paid product that shows them that they can get a lot more from the experience, and then from there you can upgrade them to Tinder Gold or to the Microtransaction products. Do you show ads to that for users or are they otherwise monetized? They are. There are ads. It's a small part of Tinder's revenue. It's just the numbers in terms of the value of an ad impression versus the value of someone subscribing to Tinder is such a huge difference in terms of order of magnitude. It's a nice way to fill in the gap, but it's not like, I mean business driver. Jacob Eiting : Yeah, it's incremental. Everybody I've talked to ads is less than a quarter. I'm sure there are exceptions to that, but it's not a huge part of the revenue mix from everybody I've talked to. But it's meaningful. I mean, 10, 20, 15% part of your revenue mix is you should do it, but it's not going to be the workhorse for your business in most cases. For sure. And it helps you subsidize the free users. David Barnard: This happened after your time, but what are your thoughts on the super premium tier that Tinder was experimenting with and have you heard anything about how it's performed? Ravi Mehta: So I actually started work on Tinder Platinum, and this came out of insights from this graphic knowing that there were people on Tinder Gold who were purchasing a lot of micro transactions, people spending a hundred to $250 a month on Tinder. And what we wanted to understand is why are they spending this amount? What's their motivation? What are the things that we could do from a product standpoint to create something that better meets their needs? And that was the genesis of Tinder Platinum, and it really came down to the core value of Tinder, which is one of the questions was is this people signaling? Are they trying to signal wealth or something like that by spending a lot on Tinder or is it more utilitarian? Do people just want to match with more folks? And it turns out it was more utilitarian. People are just looking for more matches. And so Tinder Platinum, it gives people access to additional super likes and additional boosts, so it bundles that together. One of the interesting things about the monetization products within Tinder, and I think this applies elsewhere, is Tinder is a game that operates by a certain set of rules. If I swipe right on you, you can't necessarily see that I did that unless you have Tinder Gold and then you can break the rule because you've paid and you can now have access to that feature. The other rule that was sort of golden in Tinder is you can't message someone until you've matched one of the products that's in Tinder Platinum is the ability to message someone before you've matched, which is incredibly valuable for folks to be able to get more matches. Jacob Eiting : LinkedIn has that feature too. Ravi Mehta: It's remarkably similar in certain ways, David Barnard: But no, I was talking about the $500 a month one that they had been experimenting with the Uber, Uber platinum, I don't even know what they call it. Ravi Mehta: Yeah, I'm not even familiar with that. Yeah, so definitely after my time, Jacob Eiting : The number of people, but you still should keep finding area under the curve potentially, because I was like, what would be the hyper premium version of, it'd be a personal matchmaker or something like this, right? Would you go all the way that far? I think at some point you go beyond what is in the practical scope of a software company to do what you do, but this is often the rails. But Airbnb's done this more as a marketing thing. There's crazy experiences. There's no way that makes money for them, I guess. But have, I've heard Brian talk about this several times, which is the a hundred star experience, and you've seen 'em kind of put it into their product. But I think what we're talking about here is how you go from selling something for the one star, two star, three star, four star, right? That's probably 80% of the value you're going to capture is matching to that sort of spectrum. Ravi Mehta: I think so. And then there's always the whales who are willing to spend more, and so it's good to cater to them. Games do a really good job with that. And I think there's also the brand signaling if you can have really premium products within your brand or within your product ecosystem that suggests that it's a premium place to be. David Barnard: Yeah, we're actually talking about this at APG Growth Annual, and to your point Jacob, it is kind of beyond the typical playbook of a high growth margin software play, but for a lot of apps there are potential to do small things that don't scale for the people who are just willing to spend more or want those kind of different experiences. So at App Growth Annual, I was talking to a guy who has a meditation app and was struggling to grow and started offering classes and intensivess and week long things, and I think he followed up recently with me and said he's now almost doubled revenue. So the digital product is providing half the revenue now, and these in-person experiences Zoom calls and other things are providing the other half. And so when you have this base of users, and again for Tinder at the scale of Tinder, maybe it doesn't make sense, but this is one-on-one matching for Jacob Eiting : They want to give up a 10 David Barnard: K matchmaker, maybe Jacob Eiting : Those high gross margins, right? When you're at Tinder scale, but when you're at a smaller scale, it's potentially worth considering. It's David Barnard: Interesting. How did y'all go about staging into this three tier model and layering those on top? And was there worry about confusion? And I know the app is really careful to not show a paywall with all three options at the same time, but what was the thinking as you started to work toward fitting this demand Ravi Mehta: Curve? It was pretty organic, so I wish I could say we had this graphic and the company laddered into this strategy very intentionally. I think it was more of an organic process of launching one subscription, seeing how it does, figuring out what are the things that people really value in that bundle, what are the things that are less important? What's the next level that you can provide someone? And so for a very long time it was basically just Tinder plus Tinder Gold, and then Tinder Platinum came after looking and saying, actually, there are people that are spending a lot, how can we better meet their needs? And actually there was one of the interesting things behind Platinum was people would spend more if they could get more utility, we weren't hitting the limit of what they wanted to spend, they were hitting the limit of what Tinder could do for them. And so coming up with a product that met their needs was important. And then for the Microtransactions it was largely about how can we create things that enable people to match more effectively? Boost is similar to the Boost on LinkedIn where your profile gets seen more by people in the ecosystem. Super like is the ability to send someone alike that's differentiated? And so when you send someone a super versus a regular, they're three times more likely to match with you. And then there were a bunch of other Microtransaction products that Tinder has tried along the way, some of which have stuck, some of which haven't. So it's a really organic, very experimental process. I think one of the interesting things about Tinder, I don't know if this is still the case, but it used to be that Tinder had more skews in the Apple app store than any other app because Tinder would test out 7 99, 8 0.9 9, 9 9 for Tinder, Tinder Plus, and then other price points for Tinder Gold and then other price points for boosts and then bundles of boosts and super likes. And so there were literally hundreds and hundreds of different skews available because of all the testing and then all that testing would get multiplied by different locations. And so if you're in, the pricing is going to be different in the UK versus South America versus in the us. So it's all pretty experimental and organic. I think a really key thing that the company did well though is understanding the underlying user behavior of what are people looking for from the product and then creating products that really map to that user behavior and help people get value, get more matches for less time spent. David Barnard: This being kind of the plutonic ideal of monetization, I know a lot of people would love to get to this, but having advised a lot of startups since your time there, I'd imagine you've started to build some kind of ideas around the game theory of what kind of products this works for and what kind of products it doesn't. Any thoughts Ravi Mehta: There? One of them is that core question of are you free to play? Do you have a limited free trial or are you paid only? I think that's the first question to ask. And free to play works if you have really significant network effects. A limited paid trial works if you can get the person into a habit loop really fast. You've got seven days to get them into that loop of using your product and you want to limit the friction to actually for them to get in and then get that habit loop built that works. If on the other hand, you need someone to be financially committed in order to really adopt your product. I think an interesting example here are gyms, right? You would never want to do a seven day free trial at a gym. Instead you want to charge people up front and now they have both a financial commitment and as well as a personal commitment to go and to use the gym. And so I think that's the first question to answer. And then once you've answered that, then you could figure out, okay, where do we start in terms of a subscription? What's the right price point for the first tier? And then for Microtransaction products, I think it's important to understand how does the value that someone get scale with their usage when they get a lot of value from their product, what are they doing more of in order to get that value? And then you can create Microtransaction products that really meet that need. And so the best a la carte or market transaction products do have that scaling effect of 10 is going to be 10 times better than one a hundred is going to be 10 times better than 10. As long as they're scaling linearly or about that, then people want to buy more of it as they're getting more value. David Barnard: But then you also got to figure out what those users would actually be willing to pay those 10 times or more for. And that doesn't kind of break the game. If you're a scanner app and you limit it to 10 scans a month and then you pay a dollar per additional scan, I mean that's just not going to probably fly. So for certain kind of utility apps and other things, there's maybe not that kind of similar game theory approach where people would be willing to pay additional consumables for those kind of products and experiences, right? Ravi Mehta: Yeah, I think it depends. So one of the things I think people undervalue is just the fact that someone is using your product. The fact that they've installed the app or they've gone to your website, they're using it there means that people have a lot of stuff to do other than use your product. The fact that they're doing it means they're pretty highly motivated, and so that means that they have an interesting level of willingness to pay. And so I think it's better to start out with something that's a little bit higher, especially going back to that threshold thing that we were talking about before. Get people into a subscription that's $20 a month or $30 a month, whatever the framing is for your particular space, and then you can kind of optimize from there. I think a lot of companies and founders make the mistake of monetizing their users and then they build a system where, okay, you can get your first thing for a dollar and then you can get five more of them for $3. And now you're in a system where a user has to be incredibly engaged in your app in order for you to be making a reasonable ARPU on a monthly basis. So set that high water line of 20 bucks or 30 bucks, you've got a really good place to start. If nobody's willing to do that, then you've got a product market fit problem, especially if there's already framing for that price in the market. And then that suggests that you should be working on product market fit, not monetization, and if they are willing to do that, then you can optimize from there. David Barnard: And you mentioned a lot of founders are under monetized. Any specific examples come to mind where you think if you could go in and apply this playbook to their business, you would two or three x their revenue because they're just currently quite under monetized? Ravi Mehta: Yeah, I think granola is a good example. So I use Whisper flow and granola every day. Incessantly Whisper Flow had a limited paid trial, they got me into that habit loop. I started using it and then once it came time to pay, it wasn't even a thought. I was like, I have to, I'm using this every day. I need to keep using this versus granola, they have some sort of free tier, which I don't fully understand what the limits are, but I've never paid for the product even though I use it every day. David Barnard: And as we were talking, it came to mind. Riverside is a great example of this. I think we are only paying like a hundred or $200 a month for Riverside, but it's so incredibly valuable to what we do with the podcast. It is such a drop in the bucket compared to my time the production team. We send mics to guests. I mean that's a hundred bucks a pop. We're paying them less than we spend in microphones to send to guests. So that's an example of probably being way under monetized, but it's hard to differentiate and find those features that I would be willing to pay for that the hobbyist podcaster wouldn't pay for. And then delineating all the different ways to charge for that. Jacob Eiting : I mean that's an interesting thing with going back to the Tinder examples, just like the, because at some point Riverside is a counterpoint. If somebody's doing a for fun side podcast, whatever, a hundred dollars a month is probably a big ask. What we're doing, obviously it's not even meaningful, but for Tinder, Tinder's an app that actually the success case of Tinder is worth a lot of money. Not directly necessary, but it is. It's like to find a soulmate or even just companionship or whatever at a good time, that's actually quite valuable. So you can charge quite a bit to lever onto that. Right? Going back to David Scanner app, it's like, well, I mean I either scan the document or I don't, there's not a huge your product market fit problem there. It's just that that's just not a compelling, there's not lot value there. But founders I think often, especially early stage, so undervalue their products unless maybe they're second time founder or they're doing some very specific price arbitrage thing. Maybe that's what granola is doing. I don't know anything about granola, but maybe they're just like, Hey, we got a bunch of venture money, we're just going to dig a giant hole and it's fine. Then we're going to be on every app and we'll figure it out later. But I've seen less of that and more of the like, oh, I don't think it's worth that much. Oh, I don't feel like the product is ready, dah, dah, dah, dah, dah. But to your point, if you don't price it in the market at a competitive rate, you're not going to know your best way to measure product market fit. You can measure it with surveys and all that other stuff, but there's nothing more revealing than if somebody's going to open their wallet and pay you, I feel like is the best way to measure product market Ravi Mehta: Fit a hundred percent. And I think that that framing thing is really important. The fact that you guys are sending out microphones that's a hundred bucks a guest and you're willing to do that. The analog in Tinder is we thought a hundred to $200 a month, that's a massive amount to be spending on Tinder a month. Why are people spending that much? And we talked to people and they said, look, if I'm going out on a couple of dates a month, that's like 400 bucks. And so actually spending a hundred dollars on Tinder is actually a really good investment for me relative to the amount that I'm spending on this need, which is I want to date people, I want to meet people. And so if you have a product that is solving an important need for someone, there's a system around that that kind of fits into the problem that you're solving. And so you should think about what the value is of that system rather than just like, oh, 20 bucks a month is a really good place to start what everyone else is charging. David Barnard: And I brought up Scanner Rafts as this canonical example of it's free. You can do it in the Notes app. And this actually goes to your point exactly that there's scanner apps making really great money. Why are they making really good money? Because they layer on the products that are valuable to people. If you're scanning on a daily basis and that scan needs to go into a certain workflow, a lot of the scanner apps that are succeeding, it's because they have inbuilt storage. They have OCR. When OCR, they added OCR when OCR wasn't a thing, and that's what people were willing to pay for the cloud storage, the easy sharing, the workflows, they layer onto what would otherwise be this commodity transaction that things that are actually valuable to people and that's how they make their money and how they find that product market fit to Jacob's Point is like they add the value and people pay for it. Ravi Mehta: Yeah, a hundred percent. And if you're getting 200, 300 pieces of paper a month for your business and you need to be able to scan it really easily, that fits within the broader context of your business. Jacob Eiting : Adobe Acrobat Reader Edit, which is their big scanner app on iOS, 6.3 million a month. Congratulations, Adobe. That's amazing. It's almost a hundred million dollars run rate on a scanner. David Barnard: Well, I wanted to move on and talk about this company you were working with this year, Sesame Care who moved from a three step checkout to a 25 step checkout and boosted conversion 40%. So I kind of stole the thunder there. Why did that Ravi Mehta: Happen? So Sesame is a really interesting company. It's creating an alternative to the typical healthcare market within the us. So the healthcare market in the US is completely intermediated by health insurance. In order to go see a doctor, you typically will give them your health insurance and then you might have a copay or not have a copay. It's a system as we can see what's happening with the government right now that is in many ways broken. And the model with Sesame is let's actually just create a free direct marketplace between doctors and patients. Doctors can choose how much they want to charge, patients can pay that in cash if they need to, and that makes sense for a lot of people who are both uninsured, but increasingly there's people who are underinsured where you can actually see a doctor for less than what your copay would be. One of the really key cash pay areas within healthcare over the last two or three years has been weight loss medication. There's been with Ozempic and Wegovy and Zeep, there are these new medications that people want access to that their Dr. May or may not want to prescribe, that they may or may not want to pay cash for the medicines themselves. And so a number of companies have launched direct to patient services around weight loss sesame. We initially launched a program with Costco where you could come in, you get low price on having access to care and then seeing if weight loss medication is right for you. We had a very typical checkout there. It was three screens, you kind of get in, you check out, and then we launched a much more sophisticated version of the program as sort of like a V two where we expanded the intake from basically just a little bit of information to a checkout screen. Instead, we now have 20 different questions. We estimate the amount of weight that you could lose on the medication. We get your medical history, we ask why you're looking to lose weight, what are the things you've tried? And so it's just a really comprehensive intake. And we saw a higher conversion rate because as part of that intake, people got increasing confidence that the care that they were going to get is really good, really comprehensive. We weren't just focusing on just being a kind of pill sort of approach. And so by the time that you got to the checkout screen, people were much more likely to check out and the step to step conversion rate that we were seeing from one question to the next is north of 99%. And so it was a really good example of how sometimes the best way to optimize your intake or your onboarding is not to simplify it, but to extend it around the psychology of the user so that you're giving them the information and the motivation that they need in order to feel really good about completing that process. David Barnard: But Tinder famously had a super fast, less than a minute of onboarding. What's the spectrum there? How do you think about the uber simple onboarding and where that actually works and should continue to be applied? I think there's a lot of apps where that probably should still be the case and you're going to squash your conversion by introducing 25 steps between getting into the app and actually achieving some kind of goal. How do you think about that spectrum from a super frictionless onboarding as quick as possible to intentionally adding friction? Ravi Mehta: Yeah, it's a really good question. I think it comes down to what is the aha moment for your product? What's the moment where you're delivering a significant amount of value? In the case of weight loss, the value moment is when a person meets face-to-face with their doctor and it's much better for their doctor to come in knowing all of the information that you entered about yourself and be able to use the time that you have with the doctor to talk about the questions that you have to see whether or not the weight loss medication is good for you to get you the information that you need to make sure you can get it covered by insurance or whatever else it is. And so moving the information gathering out of that visit and into the intake phase one gets people excited about the fact that this is a really comprehensive program and then makes the most use out of that aha moment where it's a patient talking to a doctor and that creates the value. And so the shorter intake actually meant that the doctor was having to ask a lot of those same questions in the visit and burn up valuable time where the patient's questions weren't getting answered. But what's the aha moment for dating? The aha moment for dating is getting into a conversation with someone and if you could shorten the time from when they go from, I'm just trying out this app to I'm actually in a conversation with a person that increases the aha moment. And so sometimes that's a matter of increasing friction because the friction along the way gives you the information or the motivation that you need, and sometimes it's a matter of decreasing friction in because you want to get a person to a particular moment really quickly. A framework I really like for this is Dery contractor has a framework called the Psych Framework where the idea behind it is that you can psych a user up or you can psych a user down as they're going through your product, and it's important to manage that motivation in a really intentional way and keep the motivation high. David Barnard: Gotcha. Yeah, I pulled this up and we will put a link to this in the show notes as well. There's a really cool chart where it kind of tracks the psych where you add five psych points, add five psych points, and then you hit an email form fill and that takes away five psych points. You have to enter your credit card that takes away 10 psych points and thinking about it in this way and kind of managing that through the onboarding, and you'll probably, you'll know the ones that are creating this negative psych because when you're tracking your analytics, those are the ones people are dropping off on. Those are the ones that aren't performing as well, but you need to do some of those, but I like you build up and then you cash out and then you build up and you cash out. And I really like even the visual of it in that blog post. Ravi Mehta: Yeah, for sure. And some people don't think about this, but one of the highest negative psych moments in a typical onboarding flow is having to define your password. You might be using a password manager, you want it to be unique, you want it to be secure. All of the stuff that goes into that actually decreases your motivation and maybe you bounce and go back to scrolling on TikTok instead of completing that form. And so many companies I think that have really good onboarding flows have moved to just give us your phone number and we'll send you a one-time password, and then you get in and if we need to set up a password later, we can do that. Or if you want to log in with Apple or Google, you can do that. And that is a really good example of how taking out a negative psych moment can just get a lot more people through the onboarding process. And sometimes those inefficiencies lie in places that you think you have to do, but you don't necessarily have to do it. David Barnard: You said somewhere that by creating this really frictionless onboarding experience for Tinder that actually expanded the TAM for dating. What do you mean by that? How did you think about expanding TAM through more Ravi Mehta: Frictionless onboarding? The problem that dating had at the time that Tinder came out, and this was I think 2012 timeframe, was that in order to get into Match or eHarmony, you had to fill out 20 or even a hundred questions, whatever it was, you need to spend 2030 actually creating your profile. And so only people who are really serious about, I think online dating can work for me, were actually going to end up in an online dating product. And so that meant that the total addressable market for online dating was pretty small. Instead, Tinder massively decreased the friction to get into an online dating app through a few different things. One, by using Facebook login, so you didn't need to create account two by having you just pick pictures from Facebook that you wanted to use for your profile three by having a short Twitter like bio. And so you could go from, oh, maybe I'm interested in online dating to actually swiping on people and maybe talking to someone in less time that it took to create your profile on eHarmony massively less time instead of 20 minutes, you could be in and swiping on people in a minute and a half, two minutes. And so that increased the total addressable market because all of these people who had very limited willingness to pay with their time could now actually get into a dating app for the first time and see that it could really work with them or work for them. And so as a result, you had a lot of younger people who had never considered online dating before, come into and use the Tinder app, and that was a key moment for online dating to go from a niche market into a market that nearly every single person in America uses. David Barnard: I love the dichotomy here where we, and I didn't intentionally play it this way, but starting with increasing to 25 step checkout, boosted conversion, 40%, everybody listening was probably like, oh yeah, I really should add more onboarding. I really should do more. But then Tinder doing less is what helped make it happen, and there's probably a happy middle ground for a lot of companies. No, it's an unhappy Jacob Eiting : Middle ground, David. David Barnard: Well, you have a long one. That's right. Jacob Eiting : You should have a short one. I don't think the middle is the death zone because yeah, I mean also, I dunno, buying a GLP one that's a complicated, very technical, very risk associated and all this stuff, I wasn't going to call Tinder hookup app. Some people may have called it that at some point, maybe few times, looking for hot people to go hang out with maybe date. Who knows? That's a very, everybody knows how to do that, right? There's less to explain there, you know what I mean? It's like meet this person, not meet this person attractive, not attractive, right? Or to you, whatever, stay away from the messy middle, you know what I mean? Know who you are. Are you the long onboarding? Are you the very, very short onboarding and go hard on either? Ravi Mehta: I'll give another really interesting example, and I think this all comes down to motivation and confidence. You want to keep a person highly motivated during the onboarding process and that you want them to be confident that what they're getting is what they want. At TripAdvisor, we had tested out a new algorithm, so it used to be that you would always see hotels sorted by their traveler ranking, so by their average review score. Instead, we personalized that based on your past behavior to show you hotels that you're more likely to convert on. We did some testing without doing anything other than just changing the algorithm, and we saw that people were actually converting much better with the new just for you algorithm, and then we rolled it out as just for you and said, okay, now your default is just for you. We've looked at your past behavior, we're showing you a set of hotels you're likely to convert on, and as soon as we branded as just for you, the conversion rate went down and the reason that the conversion rate went down when it was branded just for you versus when it was sort of a blind algorithm, is that travelers don't want you making decisions for them. They looked at that and said, TripAdvisor doesn't know what's just for me. They don't know anything. And so people converted less well, even though when we just did it for people and didn't tell them they converted better. And so there's a combination of both actually getting to the right answer for the user, but also creating confidence around that right answer. And that might be a longer intake, that might be a shorter intake. David Barnard: Any specific questions or advice if you were advising a startup and they're like, should we do a long onboarding? Should we do a short, I mean, ideally you probably experiment with both, but what would be the thinking or framework to decide? Are we that short onboarding company or are we that long onboarding? Ravi Mehta: I would say ask what is the aha moment? And then what do you need to do to foster the confidence and the behavior to get a person to that? The GLP one case, as Jacob was mentioning, that's an injectable. This is the very first time in most people's lives that they're actually going to inject themselves with the medication. It takes a lot of information, a lot of handholding for a person to even consider whether or not they want to talk to a doctor about it versus something like dating short profile, a couple of photos, I just want to get in there. I want to see who else is here and I want to swipe on. People match and have conversations. The consequence of the decision is very different, and so as a result, the intake should be optimized in a different way. Same with travel, right? Travel is a very high consequence decision. People only do it once or twice a year. They spend next to their car in their house. That's the third most expensive thing they do during the course of a year. They want to make that decision with the confidence that they're making the right one, which is not an algorithm telling them this is the right thing for them, but it's actually them coming to the decision of, oh, I looked at all of my options and now I feel like this is the right thing for me. Even if those two answers are the same, they want to go through the process of being confident about their decision. David Barnard: If you could draw some lines around what your monetization is as well, and I think part of what's working for a lot of apps with these long onboardings is that you're showing the paywall in onboarding, and so you're not necessarily getting them to that aha moment before they see your paywall. And then especially if you're not a freemium product and have a hard paywall, you got to manage that psych to getting them to the paywall before they really get to experience the product. So you got to find a way to manufacture these aha moments, this confidence, this excitement for the product so that they get to that paywall at a state where they're willing to start that free trial to then actually get to experience the product. And so for a freemium product, maybe being able to get to that aha moment quicker and then have the confidence that you're going to monetize them in the long run once they've had that experience is one way to think Ravi Mehta: About it. And then you could create value for people before they've monetized. I think comms a really good example. As soon as you open that app, you start to hear rain sounds right, and so their promises were going to make you more calm, and they do that before you've done anything on intake. In fact, even their commercials do that. They have those calm commercials where they just did a timer of 15 seconds of rain sounds, and so they're delivering the value that the product promises from the very first touchpoint with the product. And if you're doing that during the onboarding, if you're creating value for people, you're onboarding could be as long as you want. It can be 90 screens long, as long as you are creating the value promise for the user that they want to get from your app, and then at that point they're ready, they're happy to pay, like it's already creating a lot for me. If on the other hand, your onboarding is, it's like a IRS form, it's like name, rank, serial number, and you're just asking for information, it's not even really clear why you need the information. At some point a person is going to get bored and bounce. David Barnard: One of the things you talk a lot about are frameworks and mental models. Why? What's the value in frameworks and mental models and how do you even define those? Ravi Mehta: Yeah, I think the value is in, we are dealing with incredibly complicated problems. We're trying to build businesses. The tech industry is moving really fast. Ultimately, products live or die by user psychology, whether it's B2C or even B2B, right? There's still a psychological element to it about whether or not a person wants to buy a particular product. And so we're making decisions in a really intense and fast moving environment. I think frameworks are helpful to be able to say, let me take a step back from this decision and start to think about it in a simpler way and start to pull apart some of the factors that might be conflated and come to a better understanding of actually, maybe if I think about it this way versus that way, you can start to think about, well, what is the root cause that you're solving for? Similar to what we've been talking about, right? This idea of should you have a short onboarding or a long onboarding is a really key fundamental question. And if you hadn't have been thinking about in that way, you might actually end up with a middle-sized onboarding and say, okay, balance of all the factors. I'm going to do a little bit of this, a little bit of that, and end up with something that's less opinionated and less incisive because you didn't pull apart the different things that were conflated. And so I think the magic of frameworks is not that they do the thinking for you, but that they help you ask the right questions to pull apart the factors that really matter. David Barnard: Well request for blog posts if you have some free time. I would love to see a Ravi meta onboarding framework of how really think through these things that we kind of loosely talked about, but have a more framework approach to how to think about onboarding. I think that would be really fascinating. Ravi Mehta: It's a really interesting topic. I feel like, especially now with ai, onboarding is evolving very quickly. Yeah, it's interesting to see what all these different companies are doing. David Barnard: Well, you have a ton of different frameworks and mental models that you've published on your blog and talked about on podcasts, and you put out prolific in your content production. So folks, you can go to robbie meta.com and follow 'em on LinkedIn and stuff like that to hear more. So I had a plethora of options to draw from, but the one I wanted to talk through was ntts narrative commitment and tasks. So why did you come up with that and what is Ravi Mehta: It? Yeah, so it's an alternative to OKRs, and the reason that we developed it was we originally developed it at TripAdvisor and we were trying to get really good at OKRs. Even there was a book at the time about OKRs. We did a mini book club. We all read the book. We all started to talk about it. And what I saw then as well as what I've seen with other companies is that many companies want to get better at goal setting. They have to get better at goal setting. They try to adopt OKRs, and then it doesn't go well as they had wanted. And they spend one quarter. You try it out, you realize it didn't go well, you make some changes for the next quarter, you make some changes for the next quarter, and then all of a sudden a year has passed and you haven't quite locked in your goal setting framework. And you've spent a lot of time trying to do that. And so the question I was trying to ask is why do people have such a hard time with OKRs? And it comes down to, I think something very simple, which is goals are a three legged stool. You need the what you need the why, you need the how. And OKRs only have two of the legs. And what's interesting is this idea that I got is from John do's Ted talk on OKRs. He talks about goals being a three-legged stool, and then he says, OKRs solve for two of the legs. And the important thing that's missing from OKRs is the third leg existed in a very clear and direct way at companies like Intel and Google because they were designed around OKRs. And so OKRs could work in a system where you had the strategic why really well-defined, but if you don't have that strategy framework to go alongside with OKRs, OKRs tend to break down because they're incomplete. And so the idea behind narratives, commitments and tasks is that they are the three legs of the stool and that they are independent. And so you can work with just them without any other strategic dependencies. Narrative is what is the story strategically that we're trying to solve with this set of work? Commitments are the things that you are committing to do to make progress on that story. And tasks are the things that you'll need to do in order to deliver on your commitments. And so the narratives are the why. The commitments are the what and the tasks are the how. And collectively those three pieces work together to provide you with a set of goals that can stand on its own, that standalone that doesn't need to exist within any other system. And so as a result, I found that people that have adopted them have found a really good alternative to OKRs that in some ways it's similar, but it works better for people. Got those three parts. Jacob Eiting : How do you differentiate between a commitment and a task? It's just accountability on completion or, Ravi Mehta: Yeah, it's a really good question. So one of the things with commitments is that because OKRs use the term key results, most people think about key results have to be a metric that we're moving. Commitment is just something that we say that we're going to do. It could be moving a metric, it could be completing a task, it could be launching a particular program, it could be doing some research. The commitments are the set of things that we as a team believe are necessary for us to make progress in this area. And they can be whatever you want. If there's something that you need to do during a quarter that is not critical to making progress is not something that you want to commit the team to, then it can be a task. But if one of the tasks is so important that you want the team to be a hundred percent committed to achieving that by the end of the quarter, then it should be a commitment and it can exist in both areas. Jacob Eiting : I always find my biggest challenge with these systems is people turning them into an intellectual busy box. It's like, Ooh, something we get to word lawyer on, and here's my thesis. Why? It's like the work is hard arguing about these frameworks is easier than the work. And so people go, people go, Ooh, this is my problem, and it's tractable, which is why David mentioned we tried OKRs and then we kind of nuked them. And then I've just been coming up with weird, memorable things every few quarters, and I've kind of adopted this security through obscurity in corporate planning, which is just changing things periodically to keep people from getting too used to any one model because I think it creates, no matter what model you use, the org begins to a slime mold grow around it and totally shaped like it, which is not necessarily good. Do you think this system in some ways helps evade that or is it an ever present problem, these frameworks? Ravi Mehta: I think there is a problem just around process and exactly what you're saying, which is people sort of shape themselves around the system they're working in. One thing that I have found really effective is the word commitment is kind of scary. And so people don't enjoy making commitments as much as they do making goals or making OKRs. It's like, oh, I got it. I'm committing to do this. I take my word very seriously. And so people tend to come up with fewer commitments and then are really focused on them during the quarter. And actually the fact that people are talking about commitments is a great forcing function for conversation before you actually say, we're finalizing our NCTs for this quarter. So I found that that really helps. The narrative helps like, okay, let's spend one or a couple sentences describing the why. The commitments help because people only want to commit to the fewest possible things. So it's usually like three to five things. And then the tasks I think about is just a scratch pad. It gives us a warm start on the quarter. The goal is not to come up with these lofty goals, and then all of a sudden it's day one of the quarter and nobody's talked about how you're actually going to implement any of those. David Barnard: Yeah. I love getting down to this blocking and tackling level, which we don't always do on the podcast, but I mean this is the messy work of actually building great products is that you need to think about these kind of things. If you just go right to tasks and you don't have any kind of narrative for why they matter, what are you even doing? But yeah, how do you fit in all the paper cuts and other things? Does that become a commitment we're going to knock down the paper cuts this quarter, and that's a specific commitment, or do you see those kind of paper cut tasks as something that lives outside of this framework? Ravi Mehta: Yeah, I think that this goals or NCTs or OKRs or whatever you call them, operate alongside would just an overall culture around product and the tenants that you have around what you're creating. If you have a tenant that really values design or quality, that's incredibly important and that should be factored into the OKRs or the NCTs, and it should become a commitment if you feel like you're moving away from that, right? If the product has gotten so buggy that actually you have a bunch of tasks on your goals for the quarter that need to get done, they're not necessarily aligned to any strategic narrative, but they just need to get done. The product is getting kind of crappy. It's like, guess what? That is your strategic narrative. Your product quality is going downhill. You're going to start losing users, make that the priority for the quarter is to get your quality back to the bar that you're setting for yourself. Same thing with other things that feel like maintenance. If it's gotten to the point where it's no longer maintenance, it's something that really needs to get done, make that part of your strategy, that hygiene around product that I think really undermines companies where they're so focused on what's next, that they don't actually build the thing that the customer needs right now. I think a really good example of this is Spotify. I worked with Spotify product leader a number of years ago, and he said, quality is our most important feature. We ship that first and then we get to everything else. And I think that's a really good way to think about things. And that's really present in Spotify. I can't remember the last time Spotify cut out or crashed on me. It never gets in the way of listening to music, and that's very different than some of the other things that they compete against. And so if quality is absolutely central to you, make that part of your strategic narrative. David Barnard: How do you advise companies to think through the narrative part? I mean, it's actually something I've always appreciated about revenue Kat, and I know Jacob, you probably don't want to take too much credit for Jacob Eiting : It. I need to advise a company to think through narrative. It's like good luck. David Barnard: It can be so clarifying. And so revenue Kat, our mission is to help developers make more money. And so much of what we do, we talk about the culture, is to help developers make more money. And as an indie app developer working on my apps, I've just never had that kind of clarity of vision or narrative around the products I'm working on. So how do you think about helping folks do that? Ravi Mehta: Yeah, so I have another framework called the product strategy stack, which I really like to use, which says that product strategy is actually five layers. It's company mission is the top, everything flows from that. Then there's the company strategy, and then there's the product strategy, then there's the roadmap, and then there's the goals. And so actually the goals are the output, not the input. And if you are saying, our strategy is to increase revenue by 10% next year, let's look at what our roadmap should be. I think you're in a world of hurt because you actually have nothing that's tethering you to what you should be doing. Instead of you're saying, our mission is to help app developers make more money, then everything flows from that, and the goals that you get out of that process will be really aligned to the mission, and that's where you're going to get a strategic advantage, and that's where you're going to be able to create something that's really valuable for folks. David Barnard: Jacob, how did you come up with that mission? Did you go off on a mushroom retreat for three days? Jacob Eiting : I'm straight as an arrow. David. No, it was very near the beginning. Almost the beginning, but not the exact beginning, but it was before we hired anybody, but it kind of fell out of, in that case, the software a little bit came before, at least the phrasing, but we never would've worked on that software. If that mission wasn't important to us to begin with, we would've picked a different thing to work on. But then I was very specific in making sure it was pithy and memorable and you could put it on a t-shirt and then just repeating it day after day after day after day for the last eight years. But I feel like software really should just be, or products or companies in general, should be the instantiation of a mission. Who cares if a company exists, right? That's sort of like a legal framework and sort of like a loose agreement of cooperation. The narrative, that's why I was kind of joking, is the narrative and the mission come first. I suppose you can a mission and a narrative onto a company and a product or a company in a product that's lost its mission maybe, but often I feel like that flows from founders and founding team, but it would be my hope that for revenue Cat specifically, we've ingrained the mission so strongly. There could be no concept of changing the mission or changing the narrative because you wouldn't have a company, it'd be a different company. You'd have to split the whole thing in two. Everything else though is more fluid strategy, product roadmap, all of that stuff is sort of, so I, Robbie, I think very much agree with the stack. It makes a lot of sense, customer of one. We do this in so many words, we don't necessarily do it in a framework sense, but talk a lot about everything else flowing from mission. But then at the bottom is a product goals. I guess it flows right into tasks and commitments. What are we trying to do on the product? Exactly right. Ravi Mehta: And that's the strategy stack kind go together to create, here's how we're defining our strategy and here's how we're going to execute against it. David Barnard: And maybe that's a good expectation for folks who are working on products that aren't working. Jacob Eiting : Get your mission straight David Barnard: Or move on to a mission that you're passionate and excited about and start over with something that has a narrative and a mission first, Ravi Mehta: Not just a product. And if your customer's not mentioned in your mission, that's a problem. I think what's really powerful about the revenue, I think Jacob Eiting : That's a lot of people's mission, Ravi Mehta: Which a lot of companies operate in that way, and then it filters through the entire organization and then all of a sudden everyone's just like, how do we just turn the screw on our customers to get more money from them? And that is the source of disruption. Big companies get disrupted because they start focusing on themselves, not their customers. Jacob Eiting : I mean, it goes beyond companies. I think if you look through human cooperation through history, the best and greatest empires and organizations were built not under the guise of extraction. It was all under the guise of a righteous mission of some kind of belief system. And then they tend to fall when they become bureaucratic morass where everybody's out for themselves. Ravi Mehta: We wouldn't know anything about that in Jacob Eiting : This picture. No, it's not like history is littered with examples. But yeah, I think it's exactly the same in companies, and it's a delicate balance. It's hard to maintain, right? It's very lucky if it survives the founders. I mean, you could even look at Apple now and you could ask the question at least, did it survive the founder in that case? I think there's probably good arguments in both directions, but it's TBD, Ravi Mehta: And it could seem like everything's fine. The timelines are really long. If you've done well by your customer, you might have 10 years or 20 years or 30 years of products that you can deliver that are extractive before it catches up with you. But it's important to catch it before it becomes a vicious cycle, and then it's impossible to unwind. Jacob Eiting : Yeah, I should do some. I'm trying to come up with the top of my head of organizations that have lasted like a hundred plus years post founder, post even founding family and stuff like that. I dunno if you know any, I can't name it off the top of my head. I'm sure they exist though, where they're very still very mission driven, still very mission oriented, even though it's been handed off many multiple times. Ravi Mehta: Microsoft is how old now. It's a good example. Jacob Eiting : Yeah. Well, but I think it's 50 years old now, right? We'll say they're on iteration three of leadership. David Barnard: They're wander wandering through the wilderness with Balmer. Balmer. Jacob Eiting : Balmer was even kind of a founder though, and that even goes to show how kind of touchy it is. And yeah, now with Satya, they might have somebody who's maybe even potentially stronger than the founder. David Barnard: He's got that founder energy for Ravi Mehta: Sure, Jacob Eiting : More adapted for the time. He's a better founder for the moment. Ravi Mehta: Steve Blank has a really good article about the visionary versus the operator and how visionary CEOs surround themselves with operators. They need people to execute, but when they focus on their succession, they typically promote an operator into their role. And the reason is because if you had other visionaries around the visionary to begin with, that would cause conflicts. But companies need that visionary, and so a lot of times you have Bill Gates was the visionary, bomber was the operator, and then you had to have Satya come in and bring the vision back. Jacob Eiting : Not to speculate too much about internal Apple politics, but there were a bunch of folks that Steve had worked with, like Scott Forstall and even Johnny, and Johnny and Scott didn't get along. I think this would all be considered potentially visionary replacements. So we ended up with Tim obviously one of the greatest operators in the history of a hundred Ravi Mehta: Percent, yeah, Jacob Eiting : Business, but very clearly in the operator bucket. And so yeah, that's a fascinating observation and probably true. I'm going to do some research and organizations have survived a hundred plus years and we think are still very mission oriented. I think it's difficult. It's difficult to find. Ravi Mehta: Nintendo might be a good example. Jacob Eiting : This is a great example, and I would recommend the acquired podcast. I'm going to offer another podcast, but they did a really good multi-hour breakdown on Nintendo, but Nintendo is also kind of a pseudo family company in the sense that it's passed from one generation to the next in sort of this way that only Japanese companies kind of can pull off arguably more mission focused than they were at the beginning, which is good. It's a good example. Yeah. David Barnard: So we're starting a new thing on the podcast. I'm going to wrap each podcast with three questions, and I prepped you ahead because these are tough questions. But what is the biggest fail of the year in your mind? And for operators, this is going to be more directed at the biggest fail in their business, but for you as a consultant, this could be broader industry or a client that you worked with, but what's the biggest fail of 2025 for you? Ravi Mehta: I think the biggest fail is a GI think everyone thought this was the year. Were you working on it? Jacob Eiting : We have you to blame Robbie for the Ravi Mehta: Exactly. Jacob Eiting : Come on. Ravi Mehta: Yeah, I took some time off. I didn't quite get to a DI fast enough. I think this goes to a lot of what the tech industry does bad is either over hype things or under hype things. And either it's like generative AI can't do anything and it's meaningless. It's not that useful to we're all going to die. And the truth is somewhere in between. It's been a magical year in terms of agents and reasoning models. Jacob Eiting : Remember a year ago, we didn't have cursor. Ravi Mehta: We didn't have cursor, we didn't have Claude skills, we didn't have Atlas or Comet, we didn't have all the reasoning models. All of this stuff has gone incredibly well this year. So it's actually been a great year for gen ai. And I think this whole idea that we're in a bubble right now is coming out of the fact that people thought we would be hitting a GI this year, and I never thought that was the case. I think we're still a long way off. That doesn't mean that the things that are happening right now aren't fundamental and transformational. David Barnard: So what's the biggest win of the year? Ravi Mehta: Yeah, I think the biggest win of the year is Claude. I used to use chat GPT 90% of the time, and now between Claude Code and the Claude Main app, I'm using that almost a hundred percent of the time. I think they've done such a good job with their models. They write, the reasoning is good, their deep research works well. Cloud code is pretty exceptional in terms of how much it's really lived up to in the vision of an agentic coding tool. I think they've just done a great job. They've focused on their core. They haven't gotten distracted by other products like SOA and building a browser, and they've focused on the essentials of what they can do well, and I've become really dependent on it. David Barnard: And the last question is growth would be easier if, Ravi Mehta: I think growth would be easier if, especially right now, people focused obsessively on turning their earned audience into an owned audience. There's all of these distribution channels right now that are going through massive shifts, whether it's SEO or the algorithm changes on TikTok or YouTube or LinkedIn or other places. It used to be that if you got a pretty sizable following, you could count on that to distribute your products. I don't think that's the case any longer. This is especially true for YouTubers, for example. Now what gets in front of users is really a matter of the algorithm, not of your following. And so I think it's very important for companies to obsess about how do I take an audience that I don't own and turn it into an audience that I do own? And I think that's the result of three things. One is create a direct channel with your audience, whether it's email or something else. And then two is create habits around your content so people come to you. Having a podcast that people are coming to on a regular basis and listening to is an extremely important way to have people break through the algorithm. And then the third and most important thing is create habits around your product. So if you can create those listening habits, if you can create those usage habits and you can have a direct channel to your audience, you'll be in a much better position to weather what's happening, which is a pretty significant reshuffling of distribution. David Barnard: Yeah, such a great answer. Well, as we wrap up, anything else you wanted to share? Ravi Mehta: Nope. Welcome people. To follow me, I've got my substack. It's just blog dot ravi meta.com. You can also look me up@ravimeta.com. I work with companies, so if you have a startup or a company where you're looking to figure out product strategy or monetization, feel free to reach out. We'd love to chat. David Barnard: Awesome. Well, thank you so much, Robbie. This was a ton of fun, a really great conversation. Went a lot of places I didn't expect. Those are always the same. I Jacob Eiting : Told you, I'm the bringer of podcast chaos. Right. David Barnard: Awesome. Thank you, Robbie. Yeah, thanks for having me. 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 dot sub club.com to join our private community.