The Exchanges

Q I would love to start. Growth is this new discipline, and you've been in growth orgs in some incredible companies. We have Uber, Hotel Tonight, Masterclass. What was the entry into growth for you, Adam?

A I mean, so I, I was in really digital marketing very early on, so almost 20 years ago. Uh, my first client ever was Sun Microsystems, and so we were doing, uh, you know, we were requiring Java developers to make apps for phones. Uh, that looked like candy bars at the time, not, not iPhones and things like that. And so, uh, really kind of grew up in this world of very data centric marketing where everything that we did could be measured and thought about. And inevitably, like my kind of path became this emerging media path where I'd helped clients understand, like, how do you leverage new technologies like social and mobile and video? And for a lot of those traditional clients, so Budweiser, JC Penney, et cetera, It was not just thinking about marketing. It was also thinking about the product. Like what, how does the product need to evolve and be different? You can't just take what you had on your website and throw it on a mobile device or put it on Facebook or things like that. And so that to me is like feels a lot like what I do is growth now or like a precursor of it. But Uber was really the first place that we called it growth, right? I was hired by Ed Baker. He, he brought over the kind of Facebook structure that, uh, they had built, uh, at Facebook. And so That was the first time I had a title and thought of myself as part of a growth team instead of just a marketing team …

AI assessment note: “Uber was really the first place that we called it growth, right?”

Q Let's be wild. Um, so if we start chronologically, your first growth was Hotel Tonight. What was the biggest challenge and how did that experience impact your mindset?

A Yeah, so Hotel Tonight, you know, was a mobile-only travel app, and the relationship that we had with our hotels was one that you, the rates that we were marketing could only be done on mobile devices. It was a kind of a rule left out of a lot of the early paperwork with Expedia and, and the big traditional players, and that meant that we couldn't leverage SEO, and that's really how, like, most travel companies had grown up into that point, and so that really forced us to be at the forefront of Anything mobile growth, right? Like, uh, we were doing a lot of incentivized ads to, to jump up into the app store. We were doing a lot of the, you know, early versions of mobile referral programs with contact lists. It really just kind of honed in my ability to understand and think about like new channels. And so, you know, one of my like happy moments to look back on is that I was working with the Facebook product team and was the first customer to use mobile ads on, on Facebook. Uh, and so actually being, like, at that forefront, and the only reason we were able to do it is because we had a good brand, and we weren't a mobile game, and so Facebook wanted, like, a different example other than games kind of in that mix, and so, uh, yeah, that, that kind of new channel ability and, and thinking outside of the SEO box for hotels was, was a really big opportunity for us.

AI assessment note: “really just kind of honed in my ability to understand and think about like new channels.”

Q How long do you leave a message out before you know whether it's worked or not? Like, is it instantaneous where you're like, oh, this isn't working? Or does it actually take some time where you need more data to understand the true effectiveness?

A Yeah. So I mean, it, the, the data matters, right? So at Uber, we can learn pretty quickly. Uh, I mean, we were spending a billion dollars a year at one point. And so for me to test something in the ads layer, I could get learnings within minutes. Right. Uh, whereas like, would you, would you pull it then in minutes if it saw nothing and you were like, uh, potentially if it was like, uh, if it, like most of the time we were again, building like creative systems. And so it was just like, Hey, we're going to actually test 50 different messages now within this Creative system within a week, rather than just testing one thing for a week, then having to test the next thing, we had the volume that we could test like a ton of different things at once. And so rather than putting all those impressions against one message, we could like, you know, separate it and actually get, you know, a lot more insight and learnings into the direction we were going. Whereas like Lambda School, right? Like you think of the funnel for Lambda School starts with acquiring a student, then they go through an admissions perspective, like a process, Then they're a student for nine to 12 months. Then you're interviewing for a couple months. Then they get a job. So it's literally like a year long funnel before you know if something really genuinely worked. And the volumes we were talking about are like a hundre…

AI assessment note: “learnings within minutes... Lambda School... literally like a year long funnel before you know”

Q Let's be wild. Um, so if we start chronologically, your first growth was Hotel Tonight. What was the biggest challenge and how did that experience impact your mindset?

A Yeah, so Hotel Tonight, you know, was a mobile-only travel app, and the relationship that we had with our hotels was one that you, the rates that we were marketing could only be done on mobile devices. It was a kind of a rule left out of a lot of the early paperwork with Expedia and, and the big traditional players, and that meant that we couldn't leverage SEO, and that's really how, like, most travel companies had grown up into that point, and so that really forced us to be at the forefront of Anything mobile growth, right? Like, uh, we were doing a lot of incentivized ads to, to jump up into the app store. We were doing a lot of the, you know, early versions of mobile referral programs with contact lists. It really just kind of honed in my ability to understand and think about like new channels. And so, you know, one of my like happy moments to look back on is that I was working with the Facebook product team and was the first customer to use mobile ads on, on Facebook. Uh, and so actually being, like, at that forefront, and the only reason we were able to do it is because we had a good brand, and we weren't a mobile game, and so Facebook wanted, like, a different example other than games kind of in that mix, and so, uh, yeah, that, that kind of new channel ability and, and thinking outside of the SEO box for hotels was, was a really big opportunity for us.

AI assessment note: “that meant that we couldn't leverage SEO, and that's really how, like, most travel”

Q I agree, especially in terms of that kind of intersection of the T. We're going to get to, like, uncovering quality But in terms of, like, the structure itself, where do you think about, how do you think about, sorry, where a growth team sits within an org, especially given that kind of holistic view of a CMO growth?

A Generally speaking, I actually don't think most companies need a growth team. Like, growth, again, should be infused throughout the business. So quick story in terms of Uber, right? I was hired by Ed. We, like, formed the growth team, and we were already, you know, we just, Got funding from Google. We're already two billion dollar company, right? We had 300 employees. Most of those were ops people, like at the, at the city level. But, so let's say it was like a 75 to a hundred person kind of centralized engineering driven organization. But we had like massive product market fit. It was very, very obvious at that point. We built this growth team because the core product team was like knee deep in trying to figure out how to like grow our product. Like the core product, we needed someone to be able to focus on growth. That quickly evolved into two different growth teams with Rider and Driver, and then an international growth team, a China growth team, and then eventually it disappeared. So like we actually, all of those functions within the growth team eventually actually merged back into the core business to where by the time I left, we actually didn't have a centralized growth team anymore. And I, I think people assume that like, well, Uber succeeded because they had a growth team, like, you know, pre-seed And like built it out and they still have it and it's working magic and …

AI assessment note: “Generally speaking, I actually don't think most companies need a growth team.”

Q and, you know, how do you price Uh, what you will be willing to pay for, for that rider. I think, you know, we mentioned Northstar earlier and the importance of it. When you speak with founders and advise your founders today, how do you determine what Northstar metric that a founder should choose? How, how do you advise them on what to choose and how they should decide it?

A I like to look for a couple things. So one is like, what is something that can rally as much of the company as humanly possible, right? Like, so you could say something like a new customer is our Northstar. Uh, but you know, there's huge chunks of the business that really are like, whatever, we're gonna do our job, whether we get 10 X, then the same number of people, or like we've slowed down, like the job is exactly the same in front of us. I also think that, you know, when you're dealing with marketplaces, like having a metric that actually forces you to think through which side of the market needs more growth or more effort. So at Uber, I think you and I talked about this around like, The, like, trips was our metric, because it's like, okay, well, a trip can't happen without a rider and a driver, and so if trips slow down, it forces us to go into the weeds and say, like, well, why aren't they happening? Is it pricing? Is it the amount of riders on the, in the market? Is it the amount of drivers in the market? Is it where they're going? Like, it just forces you to ask more thoughtful questions. And then the last thing I like to think of is, like, actually rooting it to the customer problem. A lot of Silicon Valley uses like DAUs or MAUs or things like that, but most people don't actually use those products. Like the problem that their products solve doesn't happen daily or we…

AI assessment note: “I like to look for a couple things. So one is like, what is something”

Q How long do you leave a message out before you know whether it's worked or not? Like, is it instantaneous where you're like, oh, this isn't working? Or does it actually take some time where you need more data to understand the true effectiveness?

A Yeah. So I mean, it, the, the data matters, right? So at Uber, we can learn pretty quickly. Uh, I mean, we were spending a billion dollars a year at one point. And so for me to test something in the ads layer, I could get learnings within minutes. Right. Uh, whereas like, would you, would you pull it then in minutes if it saw nothing and you were like, uh, potentially if it was like, uh, if it, like most of the time we were again, building like creative systems. And so it was just like, Hey, we're going to actually test 50 different messages now within this Creative system within a week, rather than just testing one thing for a week, then having to test the next thing, we had the volume that we could test like a ton of different things at once. And so rather than putting all those impressions against one message, we could like, you know, separate it and actually get, you know, a lot more insight and learnings into the direction we were going. Whereas like Lambda School, right? Like you think of the funnel for Lambda School starts with acquiring a student, then they go through an admissions perspective, like a process, Then they're a student for nine to 12 months. Then you're interviewing for a couple months. Then they get a job. So it's literally like a year long funnel before you know if something really genuinely worked. And the volumes we were talking about are like a hundre…

AI assessment note: “at Uber... I could get learnings within minutes. Right. Whereas like Lambda School... it's literally like a year long funnel”

Q You look wonderfully young. I am younger than you, but I look incredibly older. Um, uh, tell me, you mentioned the billion dollar spend there. Um, I think paid is really, really hard. When you think about the ratio between paid and organic, How do you think about advising founders?

A So ultimately, like, you want to make paid a tool, not a crutch, right? You want it to be something that you can add fuel when you need that fuel, whether that's because you're Zoom, and there was a pandemic, and you're like, oh crap, like, we need to go win the market right now, like, move as fast as possible, just dump all of our money into the next six weeks, because it will be more effective now than ever before. In that moment, you should probably be willing to make it, like, 90%, right? Um, the, but I also, like, I'm, I, you shouldn't, to, to have, like, a refined tool, you also don't want it to be zero percent, necessarily, because you're gonna miss those moments if you're, like, not operating it at all. So I, from, like, a, a generic, I'm gonna just give you an answer, like, I usually tell people 30% tells me that you're not dependent on paid, and it tells me that you're doing it enough To have like a need to keep refining and improving it, being relevant in the moment and those types of things. Um, and by giving that anchor of 30%, it, it starts to allow people to be uncomfortable when it's above 30%, right? It doesn't mean you shouldn't go there, but you should start to get uncomfortable. If it's like, man, we're spending way too much money. When you've put that anchor at 30, it allows you to at least say like how much is too much rather than just saying like, oh, thi…

AI assessment note: “I usually tell people 30% tells me that you're not dependent on paid”

Q Sorry, I'm too, I didn't, I've never been to China, I didn't, I didn't know the Chinese. What was so wild about it?

A Well, so one, you know, none of the channels that we've used are there, right? So like, oh, we've been using Facebook and Google and all these job boards, and like none of them exist in China. So you literally had to take like everything you know about media buying and planning and marketing and like throw it out the window, go understand and learn that market, and then like figure out how to do all of the different channels there. So for instance, the app store is a much more distributed world there, right? It's not just like Hey, drive everything to Apple. It's like, oh, you actually need to go buy relationships with various different app stores to be able to be there and to be discovered there. When we would hire like agencies and things like that, it became very clear that, uh, everyone had all our data. So like, like DD knew everything we were doing. Uh, whereas like Lyft and Uber always knew what each other were doing because we were watching each other, we're friends, things like that. But like, we never had each other's data. Like China, like they definitely had our data. Like, a hundred percent. We were just like, the Chinese government has it. Didi has it. Like, everybody that wants to compete with us has it. It's like, available readily in the market for us. Um.

AI assessment note: “none of the channels that we've used are there, right?”

Q I'm too interested. I always think with Masterclass, they must just grow insanely because of the distribution channels of the talent, whether it's Serena Williams or Gordon Ramsay. To what extent did new customers come or from when you were there from those distribution channels of the talent versus the company and the product?

A It was pretty mixed. I would say the majority still comes from Masterclass first. The, the kickoff moment, I actually, I think a lot about Launching a class, a master class similar to, like, trying to get on the New York Times bestseller list, where you use the leverage of that talent to hit that spark right out of the gate to get the biggest audience in, like, one fell swoop. Um, and so that's where that talent network would really come in handy. We also had the ability to do, like, white labeling and things like that, right, where we're able to leverage Gordon Ramsay's Facebook page to do marketing and that type of stuff, which was definitely an advantage that a lot of companies don't have. But I would say the, like, that, that burst at the beginning was valuable, but, but you still got a lot more value over the course of time from an individual class than just that, that moment at launch.

AI assessment note: “I would say the majority still comes from Masterclass first.”

Q or first growth mindset, really kind of central person that you bring on with growth at the core, you want an analyst mind, someone who actually can create the foundations from data, um, in particular. When you think about the type of person that you want as that first growth mindset, they could be in product, they could be wherever in the org, what type of person do we want?

A I agree with that. I think having a very data-minded person is important. I don't think they have to be an analyst. Like, I think of myself as somebody that, like, wields data really, really, really well, but I'm not creating, like, media mix models and, uh, you know, like, like, hardcore modeling, but I know how to, like, dig into it and read it and understand it, ask the right questions, propose the right things to my, my teams, or go find the right resources to build it, and so I, I agree wholeheartedly, though, that, like, The, the foundation of growth tends to be experimentation and like really great experimentation takes a very data driven mindset. And so I think having a very data driven person is important. And then I think it's a matter of like, what else do you have in the business? Like if you have, if you don't have anybody that like really understands customers, then I think having somebody maybe with a bit more of a marketing or, uh, like a product management experience is helpful if you do, but like you need to build a bunch of technology, then like somebody that It's maybe more technical and has more of an engineering mindset to flavor that is valuable.

AI assessment note: “having a very data-minded person is important. I don't think they have to be”

Q I agree, especially in terms of that kind of intersection of the T. We're going to get to, like, uncovering quality But in terms of, like, the structure itself, where do you think about, how do you think about, sorry, where a growth team sits within an org, especially given that kind of holistic view of a CMO growth?

A Generally speaking, I actually don't think most companies need a growth team. Like, growth, again, should be infused throughout the business. So quick story in terms of Uber, right? I was hired by Ed. We, like, formed the growth team, and we were already, you know, we just, Got funding from Google. We're already two billion dollar company, right? We had 300 employees. Most of those were ops people, like at the, at the city level. But, so let's say it was like a 75 to a hundred person kind of centralized engineering driven organization. But we had like massive product market fit. It was very, very obvious at that point. We built this growth team because the core product team was like knee deep in trying to figure out how to like grow our product. Like the core product, we needed someone to be able to focus on growth. That quickly evolved into two different growth teams with Rider and Driver, and then an international growth team, a China growth team, and then eventually it disappeared. So like we actually, all of those functions within the growth team eventually actually merged back into the core business to where by the time I left, we actually didn't have a centralized growth team anymore. And I, I think people assume that like, well, Uber succeeded because they had a growth team, like, you know, pre-seed And like built it out and they still have it and it's working magic and …

AI assessment note: “I actually don't think most companies need a growth team.”

Q I think a big thing that founders often struggle with is like understanding what is a retained user and what is true retention. When you think back to like Uber, it's probably easier than say like a Lambda, but like when you think back to Uber, How did you define a retained user, and how do you advise founders on what, what they should define a retained user as?

A I think cohorting is really, really, really important when thinking about retention. I think a lot of times people get stuck in just looking at our monthly actives going up and things like that, and like really looking at different cohorts either on like a weekly or monthly basis, um, and then again going back to like what is the use case, like what is the problem that you are solving, And what is the natural use case of that problem? And so at Uber, if, uh, if I took a segment that I knew were, uh, commuters, where I'm like, I would expect these people to, this, this cohort in this segment to use our product three times a week. Um, you know, like maybe not every single trip, but they're gonna use it three times a week. Uh, like we'll, we'll pull in enough data to do that analysis. We'll do some, like, histograms to understand, like, What is the normal, like the average, uh, and then using that against that cohort to see like, okay, does that three trips a week? Is it happening regularly month over month or week over week? Um, and then that gives you both the, okay, this is a retained user and it gives you the anchor to say like, oh, if they drop down to two. Or drop down to one a week, then that's someone I could actually start engaging with now in a way that's proven. You don't want to have to try to like recapture a user that's totally churned. You want to see someone like, …

AI assessment note: “using that against that cohort to see like, okay, does that three trips a week”

Q You look wonderfully young. I am younger than you, but I look incredibly older. Um, uh, tell me, you mentioned the billion dollar spend there. Um, I think paid is really, really hard. When you think about the ratio between paid and organic, How do you think about advising founders?

A So ultimately, like, you want to make paid a tool, not a crutch, right? You want it to be something that you can add fuel when you need that fuel, whether that's because you're Zoom, and there was a pandemic, and you're like, oh crap, like, we need to go win the market right now, like, move as fast as possible, just dump all of our money into the next six weeks, because it will be more effective now than ever before. In that moment, you should probably be willing to make it, like, 90%, right? Um, the, but I also, like, I'm, I, you shouldn't, to, to have, like, a refined tool, you also don't want it to be zero percent, necessarily, because you're gonna miss those moments if you're, like, not operating it at all. So I, from, like, a, a generic, I'm gonna just give you an answer, like, I usually tell people 30% tells me that you're not dependent on paid, and it tells me that you're doing it enough To have like a need to keep refining and improving it, being relevant in the moment and those types of things. Um, and by giving that anchor of 30%, it, it starts to allow people to be uncomfortable when it's above 30%, right? It doesn't mean you shouldn't go there, but you should start to get uncomfortable. If it's like, man, we're spending way too much money. When you've put that anchor at 30, it allows you to at least say like how much is too much rather than just saying like, oh, thi…

AI assessment note: “I usually tell people 30% tells me that you're not dependent on paid”

Q Sorry, I'm too, I didn't, I've never been to China, I didn't, I didn't know the Chinese. What was so wild about it?

A Well, so one, you know, none of the channels that we've used are there, right? So like, oh, we've been using Facebook and Google and all these job boards, and like none of them exist in China. So you literally had to take like everything you know about media buying and planning and marketing and like throw it out the window, go understand and learn that market, and then like figure out how to do all of the different channels there. So for instance, the app store is a much more distributed world there, right? It's not just like Hey, drive everything to Apple. It's like, oh, you actually need to go buy relationships with various different app stores to be able to be there and to be discovered there. When we would hire like agencies and things like that, it became very clear that, uh, everyone had all our data. So like, like DD knew everything we were doing. Uh, whereas like Lyft and Uber always knew what each other were doing because we were watching each other, we're friends, things like that. But like, we never had each other's data. Like China, like they definitely had our data. Like, a hundred percent. We were just like, the Chinese government has it. Didi has it. Like, everybody that wants to compete with us has it. It's like, available readily in the market for us. Um.

AI assessment note: “none of the channels that we've used are there, right?”

Q Fascinating. Perception and reality, baby. Um, listen, I want to dive into a definition because growth is such an overused term and so confused. What does the role of head of growth and growth CMO mean to you, Adam?

A Yeah. So two very different things in my mind. I'm on a bit of a high horse right now about that, this idea of a growth CMO. And so let's just talk marketing for a second. So when we think about marketing and building marketing teams, I find so many companies get stuck in this trap of, do I want like a performance driven CMO, or do I want a brand driven CMO? And what I, I believe that that does is infuse this idea that you actually have to think about those two things like wildly different. Where when I think about growth, whether it's a header growth or a growth CMO or whatever, it's more about, you know, the, the art of understanding how to leverage all of the data, all of the flexibility of like the real world economics of our world that we live in now, uh, and technology and actually be able to implement that. And to me, that's not only valuable for paid ads, right? Or SEO. It's also valuable for how you think about the design of your business and your brand and the story you're telling and the content you're creating. And so to me, a growth CMO is actually like a full stack CMO, but actually leverages the idea of, hey, let's bring in data experimentation and product and engineering to help us drive the entire system, everything from your performance media to Brand and PR on the other end of the spectrum.

AI assessment note: “to me a growth CMO is actually like a full stack CMO”

Q or first growth mindset, really kind of central person that you bring on with growth at the core, you want an analyst mind, someone who actually can create the foundations from data, um, in particular. When you think about the type of person that you want as that first growth mindset, they could be in product, they could be wherever in the org, what type of person do we want?

A I agree with that. I think having a very data-minded person is important. I don't think they have to be an analyst. Like, I think of myself as somebody that, like, wields data really, really, really well, but I'm not creating, like, media mix models and, uh, you know, like, like, hardcore modeling, but I know how to, like, dig into it and read it and understand it, ask the right questions, propose the right things to my, my teams, or go find the right resources to build it, and so I, I agree wholeheartedly, though, that, like, The, the foundation of growth tends to be experimentation and like really great experimentation takes a very data driven mindset. And so I think having a very data driven person is important. And then I think it's a matter of like, what else do you have in the business? Like if you have, if you don't have anybody that like really understands customers, then I think having somebody maybe with a bit more of a marketing or, uh, like a product management experience is helpful if you do, but like you need to build a bunch of technology, then like somebody that It's maybe more technical and has more of an engineering mindset to flavor that is valuable.

AI assessment note: “I think having a very data-minded person is important. I don't think they have to be an analyst.”

Q I mean, Lambda. Lambda is an interesting one. Um, uh, Biggest challenge in, in the growth role at Lambda, and how did that change your mindset?

A Yeah, so actually similar to Uber, where I started, and like, literally halfway through my interview, it was about, how do we get more riders? Travis came in, it was like, wait a minute, what about drivers? I had to like shift and think about it very differently. Lambda School was similar, where it was like, hey, how do we get more students into our school? And then we quickly realized that like, Lambda lives and breathes on getting people jobs, not getting people into a school. And so we shifted all of our product and marketing work to the, like the job placement side. And that was just this like unique moment where. You've got all of these different customers using the exact same product. You have students, you have teachers, like getting them into that point. You have student coaches, you have salespeople, and you have the hiring managers. And so that like. Building product and growth around like a, just a hugely instrumental part of the company's success and like a complex moment was really enjoyable.

AI assessment note: “we quickly realized that like, Lambda lives and breathes on getting people jobs”

Q I'm too interested. I always think with Masterclass, they must just grow insanely because of the distribution channels of the talent, whether it's Serena Williams or Gordon Ramsay. To what extent did new customers come or from when you were there from those distribution channels of the talent versus the company and the product?

A It was pretty mixed. I would say the majority still comes from Masterclass first. The, the kickoff moment, I actually, I think a lot about Launching a class, a master class similar to, like, trying to get on the New York Times bestseller list, where you use the leverage of that talent to hit that spark right out of the gate to get the biggest audience in, like, one fell swoop. Um, and so that's where that talent network would really come in handy. We also had the ability to do, like, white labeling and things like that, right, where we're able to leverage Gordon Ramsay's Facebook page to do marketing and that type of stuff, which was definitely an advantage that a lot of companies don't have. But I would say the, like, that, that burst at the beginning was valuable, but, but you still got a lot more value over the course of time from an individual class than just that, that moment at launch.

AI assessment note: “It was pretty mixed. I would say the majority still comes from Masterclass first.”

Q With both of those questions, I think it's often for founders listening, it's quite helpful to know like the red flags, like the glaring, oh shit, they shouldn't have said that. Because there's not always a particular right answer, but there is sometimes a wrong. What are the red flags that come with those?

A So the biggest one for me, and this is very much my marketing hat showing, is people that just don't talk about the customer, and like, what is the actual customer problem, and what it, like, how are we solving it, and what's the value of it, when they just are like, all we're going to think about is the data, uh, and like, uh, or again, just pulling in like, oh, here is how I did it exactly at this company, where it's like, just copying and pasting what you did at a previous company, Uh, is, is to me just like a red flag of like, someone taught you how to do this rather than you actually having the framework in your head to go apply it to the unique nature of my business and my customer. And so those to me are just big red flags that I see. I, I run into a lot with people that I find to be, and could be really great talent to have on a team, but are often more suited for like a very specific role. Like that has like a very actionable, like go get this thing done. It's very directed to you versus a growth role, which I think is like a very, like, like Pioneer exploratory role.

AI assessment note: “So the biggest one for me... is people that just don't talk about the customer”

Q there, and I'm applying this more broadly now across just like horizontal customer basis. How do you market to horizontal customer basis when there's old people wanting to chat, mothers wanting more money, or fathers wanting more money on the side of, you know, life, and then full-time drivers? They're so different. Do you choose one and message for one, or do you try catch all and message for many?

A Uh, both. So, like, I typically try to build some type of, like, pyramid messaging structure that on the bottom of the pyramid, like the broad stuff is, uh, money, you can make money, right? Like, okay, that might still apply to that retiree, that might still apply to both men and women, things like that, and, and that I can kind of put into mass mediums, right? I could put that on my, my, on uber.com, I could put that in TV ads, things like that. Uh, then the next tier up might be, like, something more specific. So let's take, like, safety and targeting female audiences, right? And so it's like, okay, we know that, like, women, another very large group, but gets a bit more specific, uh, safety really resonates there. So now I might take those channels and, like, put that message in, uh, I may still be on TV, but now I may, uh, not target, like, sports, right? Like, I may negative target things that I know are gonna be very male skewed or things like that. Or, um, I might, Uh, like I'm gonna put the right talent in there that actually speaks to my customer. Um, I'm gonna put that on, you know, it may not be on uber.com, but maybe there's a new badge on uber.com that says learn about safety, and like it goes down that path, right? Then it may be like, uh, what about like safety in Chicago, right? Where it's like, oh, like there's like a, like we're seeing that safety matters mor…

AI assessment note: “Uh, both. So, like, I typically try to build some type of, like, pyramid messaging structure”

Q I think a big thing that founders often struggle with is like understanding what is a retained user and what is true retention. When you think back to like Uber, it's probably easier than say like a Lambda, but like when you think back to Uber, How did you define a retained user, and how do you advise founders on what, what they should define a retained user as?

A I think cohorting is really, really, really important when thinking about retention. I think a lot of times people get stuck in just looking at our monthly actives going up and things like that, and like really looking at different cohorts either on like a weekly or monthly basis, um, and then again going back to like what is the use case, like what is the problem that you are solving, And what is the natural use case of that problem? And so at Uber, if, uh, if I took a segment that I knew were, uh, commuters, where I'm like, I would expect these people to, this, this cohort in this segment to use our product three times a week. Um, you know, like maybe not every single trip, but they're gonna use it three times a week. Uh, like we'll, we'll pull in enough data to do that analysis. We'll do some, like, histograms to understand, like, What is the normal, like the average, uh, and then using that against that cohort to see like, okay, does that three trips a week? Is it happening regularly month over month or week over week? Um, and then that gives you both the, okay, this is a retained user and it gives you the anchor to say like, oh, if they drop down to two. Or drop down to one a week, then that's someone I could actually start engaging with now in a way that's proven. You don't want to have to try to like recapture a user that's totally churned. You want to see someone like, …

AI assessment note: “what is the natural use case of that problem? And so at Uber”

Q is like, you have no idea if my mother signed up to Uber because I told her about it five times, or she saw it on a billboard five times, Or she got my discount code. It may have been any of those that caused her. And so, like, when, like, how do you think about the effectiveness, honestly, of CAC to LTV and CAC when measuring effectiveness of channel?

A I, I don't. I agree. I think it's bullshit. I think it's a really, as, like, a, the expectation that it's going to be a consistent metric across channels, and having, like, a full view of everything that could be included in that is, is impossible. Like, it's not, Unlikely. It's impossible. Like it's, it's impossible to fully attribute any, all of your channels, let alone like one of your channels, especially with like the walled gardens of Google and Facebook and Apple and all of this stuff now. I do still think CAC is a really, is a very efficient input and tool for a media buyer, but ideally that CAC is informed by like a media mix model that's constantly, you're, you're, you're basically just trying to optimize for your confidence in your model, not for perfection. And so, like, trying, you know, pulling in more data, pulling in more models, pulling in the information from your partners, all of that stuff, being fed back into the buyers with a, we believe that on Facebook, a customer's value is 20 bucks, go get as many as possible, is the best way to let that team operate, instead of asking them to decipher all of the magic behind the Cacto LTV.

AI assessment note: “I don't. I agree. I think it's bullshit.”

Q is like, you have no idea if my mother signed up to Uber because I told her about it five times, or she saw it on a billboard five times, Or she got my discount code. It may have been any of those that caused her. And so, like, when, like, how do you think about the effectiveness, honestly, of CAC to LTV and CAC when measuring effectiveness of channel?

A I, I don't. I agree. I think it's bullshit. I think it's a really, as, like, a, the expectation that it's going to be a consistent metric across channels, and having, like, a full view of everything that could be included in that is, is impossible. Like, it's not, Unlikely. It's impossible. Like it's, it's impossible to fully attribute any, all of your channels, let alone like one of your channels, especially with like the walled gardens of Google and Facebook and Apple and all of this stuff now. I do still think CAC is a really, is a very efficient input and tool for a media buyer, but ideally that CAC is informed by like a media mix model that's constantly, you're, you're, you're basically just trying to optimize for your confidence in your model, not for perfection. And so, like, trying, you know, pulling in more data, pulling in more models, pulling in the information from your partners, all of that stuff, being fed back into the buyers with a, we believe that on Facebook, a customer's value is 20 bucks, go get as many as possible, is the best way to let that team operate, instead of asking them to decipher all of the magic behind the Cacto LTV.

AI assessment note: “I agree. I think it's bullshit.”

Q With both of those questions, I think it's often for founders listening, it's quite helpful to know like the red flags, like the glaring, oh shit, they shouldn't have said that. Because there's not always a particular right answer, but there is sometimes a wrong. What are the red flags that come with those?

A So the biggest one for me, and this is very much my marketing hat showing, is people that just don't talk about the customer, and like, what is the actual customer problem, and what it, like, how are we solving it, and what's the value of it, when they just are like, all we're going to think about is the data, uh, and like, uh, or again, just pulling in like, oh, here is how I did it exactly at this company, where it's like, just copying and pasting what you did at a previous company, Uh, is, is to me just like a red flag of like, someone taught you how to do this rather than you actually having the framework in your head to go apply it to the unique nature of my business and my customer. And so those to me are just big red flags that I see. I, I run into a lot with people that I find to be, and could be really great talent to have on a team, but are often more suited for like a very specific role. Like that has like a very actionable, like go get this thing done. It's very directed to you versus a growth role, which I think is like a very, like, like Pioneer exploratory role.

AI assessment note: “So the biggest one for me... is people that just don't talk about the customer”

Q Can I ask? Yeah, no, I like that. I just have to ask, you know, driver growth is really, really hard. What do you think you did so well at Uber to accommodate the demand on the supply side? Like, how did you, how did you acquire drivers so efficiently, do you think?

A I mean, it wasn't one thing, right? Like, was it, it was dozens and dozens of things. So just a couple of quick ones. So one was like new channel discovery, right? Like the idea of onboarding and like, like, uh, acquiring hundreds of thousands, millions of drivers is something no one's ever done before, right? There's no case study. Like there's some learnings in trucking or in like UPS, or, you know, there are some elements in terms of like people that want to make more money. So you can take some learnings from like university of Phoenix and things like that. And like, So there's case studies on like how to do some stuff, but there was no just like, hey, here's how X company did it. You can go do it as well. And so literally like every other week we'd be like, okay, we were just spending time with our ops team and they post stuff on Craigslist to get drivers to show up at our office to sign up. Uh, could we automate that? Could we actually take that into our growth team and like make it like a scalable channel? Oh, uh, Craigslist works. Like wouldn't all job boards work? And like we, we had to go into like Uh, Indeed and Monster, and actually, like, they're used to posting, like, two jobs at a time. We're like, no, no, no, we want hundreds of jobs for every category. We want to treat it like Google, not like a job classifieds, right? So just, like, constantly iterating and th…

AI assessment note: “one was like new channel discovery, right?”

Q Can I ask? Yeah, no, I like that. I just have to ask, you know, driver growth is really, really hard. What do you think you did so well at Uber to accommodate the demand on the supply side? Like, how did you, how did you acquire drivers so efficiently, do you think?

A I mean, it wasn't one thing, right? Like, was it, it was dozens and dozens of things. So just a couple of quick ones. So one was like new channel discovery, right? Like the idea of onboarding and like, like, uh, acquiring hundreds of thousands, millions of drivers is something no one's ever done before, right? There's no case study. Like there's some learnings in trucking or in like UPS, or, you know, there are some elements in terms of like people that want to make more money. So you can take some learnings from like university of Phoenix and things like that. And like, So there's case studies on like how to do some stuff, but there was no just like, hey, here's how X company did it. You can go do it as well. And so literally like every other week we'd be like, okay, we were just spending time with our ops team and they post stuff on Craigslist to get drivers to show up at our office to sign up. Uh, could we automate that? Could we actually take that into our growth team and like make it like a scalable channel? Oh, uh, Craigslist works. Like wouldn't all job boards work? And like we, we had to go into like Uh, Indeed and Monster, and actually, like, they're used to posting, like, two jobs at a time. We're like, no, no, no, we want hundreds of jobs for every category. We want to treat it like Google, not like a job classifieds, right? So just, like, constantly iterating and th…

AI assessment note: “one was like new channel discovery... post stuff on Craigslist... Indeed and Monster”

Q Adam, you mentioned a word there, insight, and, ah, I often hear about postmortems, and I think, well, no one really talks about, like, how often to do them and, and everything around it, so, do you do postmortems? How often? Who's invited? Who sets the agenda? Can you help me understand the right way to do postmortems?

A Yeah. So the right way and the way I've done it are probably two different things. So the right way is, you know, you're ideally doing them with every sprint and there's some type of just like regularity to them. My, you know, the nature of a lot of, you know, the business, I, I tend to be, I've worked with a lot of early stage companies. And it tends to be that postmortems happen when something breaks, right? It's actually like, hey, we should probably figure out what just happened there because something went terribly wrong. But again, good, good, like, uh, postmortem health would say that you're actually doing it every time. So you're also identifying the things that are working and all of those types of things. And so, but you know, a, hey, something went wrong. Let's do a postmortem. Um, typically like there's some really great, like, Um, Miro and, uh, Coda. There's, there's some good, just basic templates that you can use. Um, and I think, uh, it, it, you know, typically it's figuring out who the right stakeholders are. So one example, um, is at Lambda School, we implemented a new, like, chat opportunity for our students, and we, we didn't loop in customer service, and customer service had, like, an entirely different chat element. And, and so it just, like, caused a ton of backlash, like, across the company, because it was like, hey, we got good data out of this, but, li…

AI assessment note: “So the right way and the way I've done it are probably two different things.”

Q Clubhouse. How do you evaluate what happened? Like, what did, what was the magic, and what went wrong?

A So it product market fit on both answers. So I think they had just killer, killer product market fit that, you know, the, the vision initially was how do we create this feeling of like a dinner party and those types of conversations in that moment, everybody needed that, but very quickly, like most people don't need that ever. You know, we talked about frequency. Most people want that like once a month, not every single day, but they opened it up so quickly to that. And then the product shifted or the market shifted where that product market fit. Doesn't quite fit there. And this is what a lot of consumer companies are going through right now, where, like, they think that, like, oh, they got to keep trying new things, but really, like, they don't have product market fit the way they used to in the middle of, like, a bear market or a bull market.

AI assessment note: “So it product market fit on both answers.”

Q Next we have Uber and I am being clinical on this. Normally I converse in some manner, but we've been clinical. Next we have Uber. What was the biggest challenge and how did that impact your mindset towards growth?

A Yeah, so, you know, I joined Uber, we had about a dozen cities, and when I left, we had probably a thousand plus cities, or, you know, the idea of cities kind of disappeared at some point. Really thinking about and driving growth, where growth really impacted both sides of the marketplace, and having to do it where the marketplace is hyper local and changes immediately, like every moment, like the marketplace has a different dynamic. Uh, I, I think that just became like a master class. Like an MBA in marketplaces and really understanding the dynamics of like, okay, we're not just thinking about like customer acquisition. We have to think about how the relationship between the rider and driver or the, the restaurant and the, the rider or the trucker and the shipping company, and like really thinking about marketplaces, like was just a hardcore element of, of helping to grow Uber.

AI assessment note: “I think that just became like a master class. Like an MBA in marketplaces”