[00:00:00] Ravi Mehta: I think the commonality is how do you stay top of mind for a particular user for the thing that they're trying to accomplish with your product?

[00:00:12] VO: How do you build a habit-forming product? Do you need to invest… We saw these different… You don't just gun for revenue in the door.

[00:00:19] Andrew Michael: This is Churn.FM, the podcast for subscription economy pros. Each week, we hear how the world's fastest growing companies are tackling churn and using retention to fuel their growth.

[00:00:32] VO: How do you build a habit-forming product? We crossed over that magic threshold to negative churn. You need to invest in customer success. It always comes down to retention and engagement. Completely bootstrapped, profitable and growing–

[00:00:45] Andrew Michael: Strategies, tactics, and ideas brought together to help your business thrive in the subscription economy. I'm your host, Andrew Michael and here's today's episode.

[00:00:56] Andrew Michael: Hey, Ravi, welcome to the show.

[00:00:58] Ravi Mehta: Thanks for having me. I'm excited for the conversation.

[00:01:00] Andrew Michael: It's great to have you. For the listeners, Ravi is the CEO and co-founder of Outpace, reinventing the way that people learn and grow by providing access to tools from experts and pairing them with a one-on-one coach who provides personalized guidance. Prior to Outpace, Ravi was the chief product officer at Tinder, a product director at Facebook, and the VP of consumer products at TripAdvisor. He's also an investor and advisor. So my first question for you to Ravi is, what was the turning point for you when you decided you wanted to start your own company?

[00:01:32] Ravi Mehta: Yeah, it's a really interesting question. So throughout my career, I've gone between smaller companies and larger companies. My career started when I was in high school. I started a game company. I ran that through high school and college. And so I've always had an entrepreneurial streak. And I get fascinated by 2 things. One is working on problems at scale, which impact millions of users. And then I really enjoy early-stage entrepreneurship, being able to work on something new, come up, think about what's happening in terms of tech and consumer behavior, and be able to build something that's really forward-looking. And so I've known throughout my career that I wanted to have experiences both at larger companies, as well as smaller companies a couple of years ago. So this was 2020 timeframe, right as the pandemic was getting started. I knew that I wanted my next role to be focused earlier stage, but I didn't know what I wanted to focus on.

[00:02:25] Ravi Mehta: And so I spent about 18 months as an executive in residence at Reforge, where I helped them launch the product strategy program and help them build and launch the product leadership program. And that gave me an opportunity to talk to a lot of people who are at a really interesting midpoint in their career and thinking about how to get ahead, especially in a work climate that was changing in part due to hybrid work in part due to just natural trends that have been unfolding over a long time. And so that's when we decided to start Outpace. The goal of the company is really to help give people more one-on-one personalized support that they need to be successful in their work lives. And over the last couple of years, we've gone through product market fit discovery and moved from providing access to live coaching services to now we are AI focused. And so we built our platform to provide essentially an AI based coach to help people get the personalized feedback, the personalized sounding board that they really need to think through the things that they're working through in a way that's not, you know, abstract and conceptual, but really specific to their particular situation.

[00:03:29] Andrew Michael: Very interesting. It's like you sort of started out as well at Reforge, as you mentioned, as an entrepreneur in residence. Well, my question was going to be like, why Outpace? How did you come up with it? I think that's obvious now as well after speaking to the various execs. And then you sort of now, if you want to call it a small pivot and move more in towards like the AI and personalized approach. What led to that learning as well from that perspective? Why did you make the switch towards AI now and as opposed to the one-on-one individualized coaching?

[00:03:58] Ravi Mehta: Yeah, so the thing that we identified early on is that there's lots of ways for people to learn and grow. And one of the most effective ways to learn and grow is to work with a one-on-one coach. And coaching is an interesting market where there's an incredibly high level of satisfaction, there's a 90 to 95% rate of people saying, you know, I would work with my coach again, or I was really satisfied with the experience. So it can be incredibly powerful for people, incredibly effective for folks. And so the challenge in the coaching market has not been on the demand side, it's really been on the supply side, the supply of good coaches is scarce and expensive. So very few people get access to one-on-one coaching. And so we were initially inspired by what we were seeing with things like BetterHelp and Talkspace and Future and other companies that were taking what used to be a one-on-one relationship between a person and a provider and productizing it so that you could deliver that one-on-one service and much more affordable price point.

[00:05:00] Ravi Mehta: And so we started there as a place to think about product market fit and get to a better optimal in terms of the cost and the value of the service. We were using generative AI to help make coaches more efficient. And what we found as we were using generative AI is that the technology has evolved so quickly that we quickly got to a threshold where it was possible to deliver an entirely AI-guided experience that's never going to be quite the same as one-on-one coaching, but can offer many of the same benefits at orders of magnitude lower cost. And so that really was both a technology direction that we were really excited about, and then also aligned with our mission of giving every ambitious professional the access to the personalized guidance that they need. So it was the right moment for us both to solve the core problem that we wanted to solve, as well as to take advantage of recent changes in technology.

[00:05:51] Andrew Michael: Interesting and I think the obvious question then that you probably get a lot is like how do you ensure the quality and consistency I think when it comes with mentorship often you seek individuals who have key experience and domain expertise. How are you handling that on your end?

[00:06:05] Ravi Mehta: There's a few different approaches. I think one of the key things, it's of course like a question that's top of mind, is can an AI-driven coaching experience actually be good enough to approach what a human can do? And one of the things that we're really excited about when we hear back from folks is it's not that they say that they're happy. It's actually that they say that they're surprised. There's healthy skepticism that goes into this. But once people give it a chance and they work with AI to be a sounding board and to help them put together personalized plans and goals, it can be incredibly effective. And there's a couple of things where AI actually has an advantage over human coaches. The first one is, it's real-time. So, you can get help in the moment where you need it versus in your next coaching session that might be a week away or a couple of weeks away. And then the second thing, which is really interesting and unexpected, is that an AI coach can actually be very consistently knowledgeable and very consistently empathetic.

[00:07:01] Ravi Mehta: There was recently a study done where the researchers compared the answers of human doctors with medical answers generated with open AI. What they found was that the answers from AI were rated two times more useful and seven times more empathetic. It was really surprising that AI is actually more consistently empathetic than human doctors at first blush, but when you think about it, it's because doctors are constrained by their time, by their energy, they just don't have the bandwidth, especially in today's healthcare system to be able to write long responses, to be able to write those responses, really thinking about what does this person need both in terms of medical advice, as well as just in terms of you know, really good bedside manner, whereas the AI doesn't have those constraints and is often able to emulate what the very best doctors can do, but do it in a really consistent way.

[00:07:53] Ravi Mehta: So certainly there's challenges, there's lots of room to grow for AI technology, there's misinformation problems. So there's definitely things that we need to work through. But I think we're already today at a point where the quality of the results that people are getting are often approaching what humans can do and sometimes consistently more consistent and better than what people can provide both in terms of being real time, as well as in terms of the depth and the consistency of the answers.

[00:08:19] Andrew Michael: Yeah, for sure. I'm always shocked and surprised of how good it's getting every single day just learning something new and it's just like mind blowing. And now I'm almost taking things for granted, like I'm using it, and it's just like, okay, it's always been this way, which is strange. I think the other pro, I guess, as well, that AI has on doctors is you'll actually be able to read the handwriting if they're writing you personalized notes, so–  

[00:08:42] Ravi Mehta: Absolutely, yeah.

[00:08:44] Andrew Michael: I can empathize better. Yeah, so today, obviously, like I want to shift gears a little bit and jump to your experience and the time you spent at Tinder as well, and perhaps as well talking a little bit about TripAdvisor, because I think We're talking just a little bit before the show that there's definitely some interesting ways as well of looking at churn retention at these businesses and maybe we can just start with Tinder and you can just give us a little bit of an overview of what your role was there and then we can jump into sort of what is interesting when it comes to churn retention from that perspective there.

[00:09:14] Ravi Mehta: Yeah. So I was the Chief Product Officer at Tinder. I came in during a really interesting time when Tinder has gone through a couple of phases. One was an early phase where there was just incredible product market fit out of the grate. Tinder grew very quickly, engagement was very high, retention was very high. It had something that was significantly better than other dating products in the market. It was a much better fit for mobile and the unique capabilities of mobile. And so it was able to grow very quickly. And then in the early years of growth, engagement was high, but monetization was low. There wasn't a really clear monetization strategy. And there was a question of, well, how do you monetize this new mobile free dating experience that's working really well for people, but that people are using because it is so accessible.

[00:10:00] Ravi Mehta: And one of the reasons it's accessible is because it was free, which is very different than Match.com and eHarmony and others, which were pay-to-play services. And so the second phase of Tinder was really innovating around monetization. And the key thing there was Tinder Gold, which is a subscription product where people could see who swiped right on them. So prior to Tinder Gold, the only way to match with someone and to know that someone is potentially interested in matching with you was to continue to swipe on people. And Tinder Gold allowed you among other things to be able to see who's already swiped right on you so that you could more quickly get matches and get into the conversations that you wanted to be in. So I came into the organization at a time when Tinder Gold was doing very well, and where we needed to move on to other ways of monetizing the user and other ways of really engaging the user.

[00:10:53] Ravi Mehta: And so I spent a lot of time thinking about the Gen Z strategy, how to keep Tinder really fresh and engaging for younger users, as well as just generally how to organize the product team around the scale that Tinder was operating at. And so one of the key things that I did When I was there, I reorganized the team into three different pillars. An innovation pillar, really focused on thinking about where is dating going and how to build that future. Two was a growth pillar, focused on maximizing monetization growth, thinking about engagement, acquisition, international growth. And the third was a trust and safety or a platform pillar, really focused on keeping Tinder's users safe, understanding who those users are, providing really great ways to authenticate and providing all the tools necessary to make sure that the Tinder experience was a high quality and safe experience.

[00:11:39] Andrew Michael: Very interesting just hearing sort of the different stages of growth of the company and then the entry point from your perspective. I want to go back to the start though as well, just what your opinion is of what do you think it was about Tinder that really allowed it to have that breakout growth in the beginning? Do you think it was just purely the freemium aspect of it, like being one of the first products that was free or was there something else that was magical about it? And the obvious swipe left and right. I think that was probably one of the first interactions.

[00:12:08] Ravi Mehta: I think there were two things that were really magical about it at the time it launched. The first one was just how mobile-centric it was. This was a time when more and more people were getting smartphones. And where in order to use a dating product, the dating products of the day were really inspired by newspaper classifieds. And so there hadn't been a lot of innovation around what does it mean to search for and to connect with people. Tinder, on the other hand, took a look at this and said, there's some really interesting things that you can only do on mobile. One of the big ones was location-based search. So just being able to see the people that are near to you was a massive improvement in the user experience. The swiping mechanism is both fun and lightweight, but it's also like very tangible and completely well-designed for mobile interfaces.

[00:13:00] Ravi Mehta: So I think the first magical thing was, it was the first dating experience that was really truly designed from the ground up for mobile. And then the second thing was that the barrier to entry was just so much lower than it was for the other dating products. For example, eHarmony at the time advertised how long their onboarding process was, how many questions people would need to answer. And it would take anywhere from 15 to 25 minutes to set up an account. And this meant that the people that were on those dating products were really highly committed, knew that this was something that they wanted to do. And as a result, were typically older and looking for a serious relationship. So just the user experience in that case, actually limited who the target market was for those products.

[00:13:46] Ravi Mehta: And Tinder did an exceptional job of massively reducing that barrier to entry both by being free. So that, of course, decreased the barrier to entry. Two was using Facebook, so enabling you to quickly build your profile from your Facebook photos, so that you could go from, hey, I think I might want to check this out, to being live on the site with a profile swiping on people in a matter of a minute or a couple of minutes. And so, that combination of being really mobile-centric plus lowering the barrier to entry meant that there were a whole set of people who had never used dating apps before that were now interested in using Tinder. And that was one of the reasons why Tinder grew so quickly. It was really both product innovation, as well as product innovation driving an entirely new market.

[00:14:38] Andrew Michael: Yeah, it's super interesting as well. If you start to think as well, as you mentioned, what would the ideal customer profile look like for a business like Tinder versus like Match for others where you highlighted like they were going there specifically to find somebody potentially to date long term, to marry, to be out, where somewhere like a Tinder just wants something a little bit more easygoing, if you want to highlight the ideal customer profile. And in my mind, I'm thinking as well, like the LTV, then of the two different segments are completely different, where the one case is that you have this graduation churn where they come on, they find one, they get successful, and then they're done, versus somebody who's looking for something a little bit more casual, and they will continue to use the app. So I'm intrigued how you looked at sort of the segmentation when it came to the user base.

[00:15:24] Ravi Mehta: From a monetization perspective, or an engagement perspective, or both?

[00:15:27] Andrew Michael: Both.

[00:15:28] Ravi Mehta: Yeah, I think what's interesting is there was a much more uniform base of users on a product like Match or eHarmony at the time because there was just the filtration of it's a paid product and it takes a lot more effort to get into the product. I think the beauty of Tinder and one of the reasons it's the biggest dating app and has been for a long time is because it's not so prescriptive about what the use case is. It's not so prescriptive about who you should be looking for, what you should be looking for. There's, Tinder has this kind of brand that it's for casual relationships. But at the same time, more people get married to people that they meet on Tinder than any other dating platform. There's more people in their 30s using Tinder than there are any other dating platform.

[00:16:14]Ravi Mehta: And so it's the biggest platform long-term because it offers the ability for lots of people to come into the product and search for what they want without having to be limited to a particular way of meeting people or a particular way of presenting themselves. So if they're interested in long-term relationships, they can say that in their profile. If they're younger, they're just interested in something more casual, they can put that in their profile. And so, from a segmentation standpoint, at a very high level, the segment is everyone. Tinder should be a product that works for all people that want to meet other people. In terms of a more granular level, the segmentation is done at a very micro level where a key thing that Tinder does very well and needs to do really well is figure out who's the right set of people to show you within your list of people that you're swiping on, so that you are swiping right on the people that you want to meet.

[00:17:13] Ravi Mehta: And so the segmentation is both really broad in some sense, because it's a mass market product, and then also extremely micro down to the individual person based on the AI and personalization algorithms that are driving the stack of the people that you see when you come into Tinder, which is based on your people who swiped right on you, people that you've swiped right in on past behavior and other factors.

[00:17:34] Andrew Michael: Yeah it's very interesting. Like in my mind I'm doing thought experiments as well and I'm just thinking about the different types of usage behaviors and maybe I'm making assumptions now, but I don't know if you would say like a more casual user might have a less filled profile where somebody's maybe looking for something more serious and long-term might spend a bit more time populating that profile. And I don't know if you ever did any look into this in terms of how that, like how maybe the increased personalization of the product for the individual user perhaps impacted negatively or positively retention. Was there anything you ever looked into on that side?

[00:18:08] Ravi Mehta: So, what was interesting is because Tinder is such an open platform where people can put whatever they want in their profiles and in their photos, there were things that people were doing by convention to sort of signal what they wanted. And so, just putting LTR in your profile, as an example, someone saying, hey, I'm interested in a long term relationship. And so, it is the case that people that are more serious that are interested in meeting other folks will spend more time on their photos, will likely have more photos. We'll likely have longer profiles. And one of the things that we spent a lot of time thinking about, and Tinder's continued to evolve since the time that I was there, is how do you create more and more tools for people to be able to signal what they're looking for and for people to be able to search based on those things.

[00:18:50] Ravi Mehta: And so Tinder has this Explore feature, which is one of the manifestations of that, that allow people to convey what they're looking for, and search and discover, but do it with serendipity. I think one of the things that Tinder's founders really wanted to make sure was that Tinder was not a search engine for people where people weren't filtering by height and income and things like that, which is what they were doing on some of the other dating platforms.

[00:19:18] Ravi Mehta: So the needle to thread from a product standpoint has been how to create the tools that people need to present themselves and to find other people without it turning into that kind of search engine quality where it's just a bunch of filters and people are filtering on the things that, you know, nominally they might say that they want, but in actuality, like one of the things that people really love about Tinder is it is serendipitous. A lot of discovery about who you want to meet happens after you've matched and after you're into a conversation.

[00:19:45] Andrew Michael: And that is another key difference as well. If you think about that between other platforms as well, where it's more like you're going to a supermarket and you're ordering item versus the other way, it's like it's serendipitous. As you say, you might need someone. The other thing as well then struck my mind, like you mentioned, LTR in the profile. In other businesses, you might even have that as a churn risk. If you had a health score, it could be a flag that comes up. And then if it's a large enterprise business, the CSM would reach out and try to work with this. Obviously, with your type of business and with Tinder's type of business, you have this churn where you have successful churn and people have left. And interested, how you thought about this as a business and what were some of the ways you perhaps tried to, I wouldn't say mitigate it because that's what success looks like, but how was this treated at Tinder?

[00:20:33] Ravi Mehta: Yeah, churn is an interesting question for dating products, in general. You know, what's interesting is dating products share some of their DNA with social products. And social products have incredibly high engagement and incredibly low churn when they work well. But in contrast, Tinder and other dating products have much higher churn. And so, the initial thinking might be, well, of course, they have higher churn. People are coming to meet someone and when they've met someone, their use case is completed. And then they're going to delete the app and use other social products. And Hinge has really leaned into that. Their whole motto of design to be deleted is to say, yeah, that's what our app is for. You're supposed to use it for a limited period of time. It's supposed to work for you.

[00:21:15] Ravi Mehta: And then from that point forward, you won't need it. But what's interesting is that when you look at people who are churning from month to month, there's 2 types of churn. There's good churn and there's bad churn. Good churn is the product has really worked for you, whether it's Tinder or Hinge or other products. And you never want to get in the way of that. Because ultimately, people are coming to these products to meet someone. If you do things that make it less likely for them to churn off for good reasons, that's ultimately going to undermine the efficacy of the product. And you know, this is a space where there are certainly network effects that prevent people from leaving, but there's also, you know, relevancy effects and other things that lead to, you know, a pretty long tail of competitors. And so there's many other products for people to go to, whether it's Bumble or Hinge or others.

[00:22:05] Andrew Michael: You could see some dark patterns as well. Like, hey, Ravi, you got matched with five extra people today, come back and check us out. Like you said, you don't want to get in the way of that experience as well.

[00:22:16] Ravi Mehta: Because whether people realize it or not, they are doing this calculus of, is the time that I'm spending on Tinder giving me what I want? And so in the case of good churn, it's like, yeah, it is giving me what I want. I've met someone, I'm not going to use the product. But it turns out that the majority of churn is actually bad churn, which is people leaving the product because they feel like the time that they're spending is not actually turning into the conversations that they want to have and the dates that they want to have. And there's 2 reasons for this. One is dating is just hard, right? As a thing that people do, it's time consuming, it's emotionally taxing. And people burn out not just from Tinder, but from dating in general, and people need to take a break. So there's kind of this natural rhythm around dating.

[00:23:06] Ravi Mehta: And then the second thing is you know, the quickness, the speed of being able to swipe on people and match with people and do that really quickly is novel initially. But over time, it can become boring or overwhelming when you feel like you've got to swipe dozens or more times a day in order to just get to a single match in a single conversation that you want to have. And so that's another reason that people will churn out. And so a really key thing for Tinder to think about from a churn standpoint, is how to solve that kind of natural burnout that comes from dating, and then two, how to create a product experience that is diversified enough, entertaining enough, retentive enough that it gives people other things to do.

[00:23:53] Ravi Mehta: So that it's not always just about that constant loop of swiping. And so there's been a number of things that Tinder has done in order to make that experience more interesting, more entertaining. When I was there, we launched something called Swipe Night, which was a weekly series where at eight o'clock every Sunday, people could come in, experience a really interesting interactive video experience together, and then go match with each other and talk about it. So it was a way to get people engaged and having conversations without it being entirely about dating as the outcome.

[00:24:24] Andrew Michael: Very interesting, yeah, because you can definitely see it has like the patterns of an addictive product, and it has the intensity as well, like of the frequency of usage, it has the variable reward as well in it, so as you're going through, you never know what you're gonna match with when you come back. It has this sort of like key characteristic patterns of like a gambling sort of casino, and I think in Nir Eyal's book, Hooked, he talks about this quite a bit, so very, very interesting.

[00:24:51] Ravi Mehta: There's an interesting analog with gaming, right? On one side, you have games like Zelda or other games that are really designed around entertainment as a thing that we're trying to drive for people. And there's some repetitive things, but there's repetition within the context of how to create an entertaining experience. And then on the other side, you have some social games where a lot of how they monetize is through repetitive experiences that start to feel like a grind. And so people you know, are engaged, but engaged in a very kind of vacuous way in a way that's not fulfilling for them versus engaged in a very fulfilling and entertaining way. And dating apps are interesting because they vacillate between the two depending on the experience that you're having.

[00:25:32] Ravi Mehta: And so it's possible to be spending a lot of time on a dating app and meeting people being great conversations. And it's possible to be spending a lot of time on a dating app and feel like you know that time is not well spent, but feeling like that's the only alternative that you have in order to meet someone and to move forward on the goals that you have for yourself.

[00:25:48] Andrew Michael: And I think this is just like any other social product as well is like, you're investing your time in these products. And if you're not getting back that value or that level of entertainment, like, that's the cost. And when you're spending too much time, you're not getting the value. That's when you start to see churn in a bad way.

[00:26:04] Ravi Mehta: Absolutely.

[00:26:05] Andrew Michael: So it's interesting that you worked in at Tinder, which had this sort of issue, this graduation component, where like, if you do your job extremely well, you end up losing customers. If you don't do your job well, you end up losing customers. Like it's sort of this catch 22. But obviously, you can improve the one end of the bad trend. The other company as well, I think that is an interesting component to churn and retention is TripAdvisor itself. We talked again as well, previous to the show, I think this comes into sort of the frequency of usage and how often you would use a product like TripAdvisor. If I think to my own experience as well, maybe I use it more frequently because I've actually started to use it for restaurants locally. It tends to be quite good in Cyprus, but prior to that, maybe I'd use it once, twice a year just to try and understand the different places I'm going. Interested what churn and retention look like and what some of the focus was there in a business where frequency is not enough to build a habit usage for a product like TripAdvisor?

[00:26:59] Ravi Mehta: Yeah, so there's a whole class of products, which are episodic usage products, where they're extremely valuable for a period of time, and then a person, a person's need is fulfilled. And so that could be real estate products where you're looking for a rental or a home purchase. Travel products definitely fit within that category. It could be tax preparation. Reforge has published a really good framework by Vivek Kumar called the ICED Framework, which talks about all of the things that are necessary to do to make sure that you have a really engaging experience even when you have a low frequency product. For TripAdvisor, there's a number of things that the company did in order to make sure of two things.

[00:27:41] Ravi Mehta: One is, you know, when a person is in a travel episode, so they're starting to research a trip and starting to get serious about a trip, you want to make sure that TripAdvisor is top of mind. And then the second thing is ideally to keep them engaged, even if lightly, during the time when they're not planning a trip, so that when they do go and plan a trip, rather than going to google and searching will actually come directly to TripAdvisor. And so TripAdvisor uses a number of techniques that were talked about in that ICED framework including one, having a really strong strategy. So that if you do start with Google, TripAdvisor is often one of the first organic results that come up. And so at that moment where people start searching, TripAdvisor is able to capture and then retain that traffic. Paid search is also really important. That's another place where people start.

[00:28:33] Ravi Mehta: And so from an acquisition standpoint, you have to be able to master those channels that people are going to when they begin an episode of usage. And then the other things that TripAdvisor has done to retain people when they're not actively traveling is things like having a great inventory of restaurants and having great restaurant reviews so that people are getting value from the product and coming to the product on a more regular basis. There's also campaigns like the Traveler's Choice Awards. And so having an ongoing conversation about what are the best beaches in the world? What are the best destinations in the world? What are the best travel products that people are using? Keeps people engaged in the platform and coming to the platform for a unique value that TripAdvisor alone can provide, which is, you know, the aggregated reviews and opinions of hundreds of millions of travelers.

[00:29:23] Ravi Mehta: And so there's, those are a few of the things that the company has done to both make sure that TripAdvisor is top of mind when you start a travel episode and two, to make sure that once you've used TripAdvisor, even if you're not actively planning a trip, you're coming back moderately frequently and staying acquainted with the brand and with this product.

[00:29:41] Andrew Michael: The Traveler's Choice Awards is an interesting one and sort of being able to stay top of mind in that manner. It's very similar to, I think to the Zillow approach with the Zillow estimate where they've taken Zillow and both TripAdvisor have taken their unique data that they have internally and they've seen okay, like what can we do with this data that can become interesting for our users and then let's make sure that we're informing them and updating with this information you want to stay up to speed. And again, you may not be in the market for a holiday right now at this moment, but receiving an email and saying, the top five beaches in Europe this summer is going to get you thinking, okay, let me go back to TripAdvisor when the time is right, they had that great recommendation, or let's go see what's available. I think it's really interesting how these businesses that suffer with this episodic usage can actually look internally to say, okay, yes, fair enough, we have this episodic issue.

[00:30:32] Andrew Michael: But what unique data do we own ourselves that we can then turn around and leverage into great pieces of content that our users are going to want to keep up to date with and keep it sweet. Just like Zillow's estimates, you buy a house, but then you want to know what the value of that house is. You want to see if it's appreciating or depreciating. So it still holds your top-of-mind the next time you decide to buy that or purchase that house. Super interesting. What was some of the challenges internally when it came to sort of focusing on channel retention then at TripAdvisor? Because like you mentioned, some of the things like were SEO and they were paid media. Most of that sounds like it's coming from the marketing perspective. So I guess marketing had a big role to play in retention at TripAdvisor. From a product perspective, was there any way like, were you working closely with marketing on these initiatives? Like how was retention dealt with internally from a product perspective?

[00:31:25] Ravi Mehta: Yeah. So specifically for the retention mechanisms like SEO, CRM, SEM, both marketing and product work really closely together. SEO, for example, a lot of TripAdvisor's ability to win at SEO is based on the review flywheel and being able to continue to get more and more user generated content, which can then be remixed and displayed in different ways. So the TripAdvisor is ranking on hundreds of millions of different queries for travel products, whether it's hotels in Boston, boutique hotels in Boston, hotels with pools in Boston. The ability to answer those questions and provide the best answer to those questions is really based on the fact that there's so much interesting review data and metadata coming in from travelers that powers that content engine.

[00:32:17] Ravi Mehta: So that's one of the key ways in which TripAdvisor was working with marketing and product to drive those things. Traveler's Choice is another thing. Traveler's Choice is definitely a marketing-driven campaign, but the way that the company generates its Traveler's Choice results is by looking at the user-generated content and really optimizing the review product in order to maximize the number of reviews that the company is getting and maximize the quality and the depth of those reviews. So a couple of examples of how marketing and product work together on those things.

[00:32:48] Andrew Michael: Nice. And so obviously then at Tinder and TripAdvisor, you worked on products that one had this episodic issue and trying to deal with, the other one had the challenge of graduation churn. You also then worked at Facebook where the, I guess again, like frequency of usage is not a problem. People are using the product really regularly. You have really high engagements from that perspective when things working. The question I think would be like, what would you say is one commonality between these three businesses when it came to churn retention? And perhaps like, why were each of them unique?

[00:33:21] Ravi Mehta: I think the commonality is, how do you stay top of mind for a particular user for the thing that they're trying to accomplish with your product? There's so many different products today, attention spans are so short, that whether it's Facebook, or TripAdvisor, or Tinder or something else, there's always another piece of content, there's always another product, there's always something else to do. Facebook has an incredibly engaging and retentive set of products in Instagram and Facebook and Messenger and WhatsApp. But that didn't prevent Discord and TikTok and Snapchat. Because if you have really interesting content that people want to spend time on, the barrier to switch is really small.

[00:34:12] Ravi Mehta: And so I think that's the number one challenge for product books is how to make sure that you're top of mind through some combination of harkening back to Nir’s book. There's internal triggers and there's external triggers. The internal triggers are something where you trigger yourself as a result of past habits. And the external triggers are things like emails, notifications, or other things that a company can do to bring you back into the product. And so thinking deeply about that combination, that mix of external triggers and internal triggers, is really important to make sure that you're bringing a person back into a product. And, you know, high retention never happens entirely organically. It's never just a matter of a person having a habit and sticking to that habit. People break habits all the time, people lose habits all the time.

[00:34:56] Ravi Mehta: And so, you know, there needs to be this constant process of breaking through the noise, even for the products that people are using on a daily basis. And then I think the thing that's different is, you know, specifically, how do you do that? And when do you do that? In the Tinder use case, if you're not dating, if that's not something that you're looking to accomplish, there's not really a good reason to bring you into the product. For TripAdvisor, if you're not planning a trip, there are some things that you can do, whether it's restaurant reviews or attraction reviews. And there's a question of how far do you take that before you get outside of your core value proposition. TripAdvisor could certainly have been more like Yelp and say, we're going to add gyms and law firms and things like that to the product, but it just wouldn't have matched with the value that the product provides.

[00:35:43] Ravi Mehta: And so even though it might have created some additional use cases that a person might come to the product for, it just wasn't aligned with the core strategy. And then I think for Facebook, it's a question of know, who are the people that people want to hear from? What's the type of content that they want? I think where Facebook has lost share in the past, it's been because there's some new format that people are really interested in spending time with, you know, whether it was like the ephemeral sharing on Snapchat, or the vertical video on TikTok. And if the company is too slow to provide that to folks, they're going to move off platform and get that elsewhere. And so I don't think everything that a person wants to do socially can be done in one product, but it is important to make sure that there's a suite of things that offer people the different formats that they want and solve the different use cases that they want.

[00:36:39] Andrew Michael: And capture their attention. What's one thing that you know today about channel retention that you wish you knew when you got started with your career?

[00:36:48] Ravi Mehta: I think it goes back to just how inorganic it is. There's a very clear correlation between how effective your CRM campaigns are in terms of segmentation and the quality of the outreach, the click-through rate on the outreach, the deliverability on things, and your retention and your ability to reduce churn. So you absolutely have to have a great product that people want to continue to use. That's the first step. And that's often the hardest step. But even when you have that, that doesn't mean that retention and churn are going to happen entirely organically. There needs to be a lot of thought, a lot of effort, a lot of motion around what are the specific things that we're doing to bring people back? Not once a week, not once every couple of weeks, but you know, every single day to keep them engaged.

[00:37:36] Andrew Michael: Yeah. And it takes time to get to great retention as well.

[00:37:40] Ravi Mehta: Absolutely.

[00:37:41] Andrew Michael: Very nice. Well Ravi, it's been an absolute pleasure hosting you today on the show. Is there any final thoughts you want to leave the listeners with before we wrap up today? Anything they should be aware of or how can they keep up to speed with your work?

[00:37:53] Ravi Mehta: Yeah, absolutely. So I'm active on LinkedIn. Feel free to connect with me there. You can also go to ravi-mehta.com. I've shared a few different resources for product managers. I have some writing on product strategy, on product competency. So how to think about your skills as a product manager, as well as other things. So feel free to sign up for my newsletter and follow me on LinkedIn and reach out. I'm pretty accessible. So if there's anything I can help with, feel free to reach out to me.

[00:38:18] Andrew Michael: Amazing. Thanks so much. For the listeners, we'll make sure to leave everything in the show notes that we discussed today so you can pick up and find those there. And thanks again for joining Ravi. It's been a pleasure and wish you best of luck now going forward.

[00:38:30] Ravi Mehta: Thank you. Thanks for having me.

[00:38:31] Andrew Michael: Cheers. Thanks.

[00:38:40] Andrew Michael: And that's a wrap for the show today with me, Andrew Michael. I really hope you enjoyed it and you're able to pull out something valuable for your business. To keep up to date with Churn.FM and be notified about new episodes, blog posts and more, subscribe to our mailing list by visiting Churn.FM. Also, don't forget to subscribe to our show on iTunes, Google Play, or wherever you listen to your podcasts. If you have any feedback, good or bad, I would love to hear from you and you can provide your blunt, direct feedback by sending it to Andrew@Churn.FM. Lastly, but most importantly, if you enjoyed this episode, please share it and leave a review as it really helps get the word out and grow the community. Thanks again for listening. See you again next week.