The original growth hacker reveals his secrets | Sean Ellis (author of “Hacking Growth”)

Introducing the Guest

Lenny Rachitsky: The Sean Ellis test, such a seemingly simple idea that has had such a profound impact on the startup world.

Sean Ellis: The question is, how would you feel if you could no longer use this product? Once you got a high enough percentage of users saying they’d be very disappointed, most of those products did pretty well. If you felt too low, those products tended to suffer.

Origins of the Sean Ellis Test

Lenny Rachitsky: Say someone is listening and they’re like, “Okay. Man, I’m getting like 10%. I don’t know what to do.” What do you find often works?

Sean Ellis: Just ignore the people who say they’d be somewhat disappointed. They’re telling you it’s a nice to have. If you start paying attention to what your somewhat disappointed users are telling you and then you start tweaking onboarding and product based on their feedback, maybe you’re going to dilute it for your must have users.

Case Study: Lookout’s Two-Week Score Boost

Lenny Rachitsky: Moving retention often is really hard, but I guess it sounds like there’s often something you can do.

Sean Ellis: It’s usually much more function of onboarding to the right user experience than it is about the kind of the tactical things that people try to do to improve retention.

Next Steps After Reaching 40%

Lenny Rachitsky: What are like three or four things that you think people should definitely try to help improve activation?

Uncovering User Context & Building Growth Flywheels

Sean Ellis: In my experience-

Certainty of the 40% Threshold & Team Focus

Lenny Rachitsky: Today, my guest is Sean Ellis. Sean is one of the earliest and most influential thinkers and operators in the world of growth. He coined the term growth hacking, invented the ICE prioritization framework, was one of the earliest people to use freemium as a growth strategy, and maybe most famously developed the Sean Ellis test to help you understand if you have product market fit, which a large percentage of founders use today and profoundly impacted the way startups are built. Over the course of his career, Sean was head of growth at Dropbox and Eventbrite, helped companies like Microsoft and Newbank refine their growth strategy, was on the founding team of LogMeIn, which eventually sold for over $4 billion, and he’s the author of one of the most popular growth books of all time called Hacking Growth. In our conversation, we dive deep into two topics. One, how to know if you’ve got product market fit and what to do if you don’t, and two, how to figure out how to grow once you’ve found product market fit.

If you’re in the early stages of a new product wrangling with product market fit or trying to figure out how to jumpstart or further accelerate growth for your product, this episode is for you. If you enjoy this podcast, don’t forget to subscribe and follow it in your favorite podcasting app or YouTube. It’s the best way to avoid missing feature episodes and it helps the podcast tremendously. With that, I bring you Sean Ellis.

Sean, thank you so much for being here and welcome to the podcast.

Sean Ellis: Thanks, Lenny. I’m super excited to be on with you.

False Positives, Switching Costs & Timing

Lenny Rachitsky: There’s so much that I want to talk about. There’s so many directions we can go, but to keep it focused, I want to spend time on two areas. I want to talk about how to know if you have product market fit and what to do once you have product market fit in terms of figuring out how to grow. I know these things are very linked. I know you spent a lot of time on these things. How does this feel?

Sean Ellis: Sounds perfect. Yeah, let’s do it.

Limitations of the Sean Ellis Test

Lenny Rachitsky: Okay. Okay, amazing. Let’s talk about, first of all, the Sean Ellis test, slash something people call sometimes the product fit test. Such a seemingly simple idea that has had such a profound impact on the startup world. I’ve never actually seen you talk about the history of this thing, how you came up with these questions, how you came up 40%, the whole journey of this thing. So let’s talk about this. But first of all, can you just tell people what is the Sean Ellis test for folks that aren’t exactly familiar with this?

Sean Ellis: It’s a simple question that helps you figure out, does anyone consider your product a must-have, or ideally, who and how many people consider it, but ultimately it’s about trying to figure out is your product a must-have, which could be equated to having product market fit. And so the question is, how would you feel if you could no longer use this product? And I give them the choice, very disappointed, somewhat disappointed, or even not disappointed or not applicable, I’ve already stopped using the product. And what I’m trying to find are those people who say, “I would be very disappointed if I could no longer use this product,” then that’s a really powerful vein to dig into when you discover that you actually have some people who would give a crap if your product disappears.

Prematurely Declaring Product-Market Fit

Lenny Rachitsky:

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Customer Acquisition & Growth Readiness

Sean Ellis: I would say it’s a leading indicator of product market fit. The lightning indicator is, do they actually keep using it? So probably retention cohorts are more accurate, but the problem is, like your time at Airbnb, how long do you have to look at a retention cohort before you know that you’ve actually long-term retained someone?

And so with this question, you can kind of find out day one, you don’t need a good analytics system in place to be able to see if product market fit exists. And so yeah, the 40% was not something I originally had in there. Originally, I was trying to have just a filter so that I was not treating all feedback from customers the same, but I was trying to find feedback from customers who actually really cared about the product. And then was over time, at the time I was working for a couple of YC-backed companies, and so those companies were all pretty connected, and so I would share the question with a lot of other startups in Silicon Valley. And so over time, I started to see there was a pattern that once you got a high enough percentage of users saying they’d be very disappointed, most of those very disappointed without the product, most of those products did pretty well. And then if you felt too low, those products tended to suffer.

Adjusting the 40% Threshold

Lenny Rachitsky: Okay, there’s two things I want to definitely follow up on here. The first is such an important point that you made at the beginning when I introduced this test that you described it as a leading indicator of product market fit and actually retention, people actually using your product, the product actually being used by the market is the actual ultimate test. So the idea here is this is a good way to get a sense of, before you actually have data, are we headed in a good direction? Could you speak more about that, of like, when to use this and when it’s most useful in best [inaudible 00:08:34]?

Origin Story of the Test Question

Sean Ellis: Yeah. I mean, so for me in particular, when I come into a company, my goal is to help them grow. And so I don’t want to put myself in a situation where I’m going to fail because no one actually cares about the product. And so it can really be asked at a company of any stage. It’s helpful to understand who your must have users are. But essentially once you have even an MVP, like a very first MVP on the product, you can still get some useful feedback about the product if it’s resonating with anyone.

So I actually had a company where I had committed to work with them. It was right after I left Dropbox and I committed to work with these guys for six months to help them grow. I ran the question and it came back at only 7% of users saying they’d be very disappointed without the product. And so I’m like, “I have six months to help them grow and they’re only at 7% right now. It might take six months to get the 40%. Am I doing them a disservice by being in a growth role and being on payroll during this period of time?” But fortunately with the signal and the information we got from the initial survey, we were able to get them at 40% in two weeks.

Lenny Rachitsky: Wow. What did you do there just as a case study?

Silicon Valley’s Tech-Driven Early Adopters

Sean Ellis: Yeah. Yeah. So the company called Lookout, it’s a mobile security company, and now most of the things in Lookout are built into iPhones and Androids. But at that time, the product had everything from backup my data to find my lost phone to protecting your phone with a firewall and antivirus. And so when we ran this initial survey, I dug into the 7% who said they’d be very disappointed without the product and found that most of that 7% were focused on the antivirus functionality. So they were like, they know they need to protect their computer from viruses, smartphones were becoming more like computers, so it just made a lot of sense for them that they’d need to protect their phone. And interesting, at the time, I think there was only one kind of phone virus that had ever even happened, but it was a pretty easy mental leap for people.

And so now we knew, okay, it’s antivirus that people really valued. And so step one was just reposition the product on antivirus. So that kind of creates a filter. So anyone who now is coming in to sign up for the product who doesn’t care about antivirus is not going to convert, and those who are excited about antivirus are going to convert. We already know from the initial survey that people value that after they convert. So by setting the right expectations around it up front, you’re going to bring people in with the right expectations. But then the second thing that we did was we streamlined onboarding so that the first thing that they did after signing up for the product was to set up the antivirus and then get a message “you’re now protected from viruses.”

And so it’s really the combination of those two things. It’s set the right expectations and then speed to value. And so the next cohort of people that we surveyed were at 40% saying they’d be very disappointed without the product. So that literally took two weeks to make those changes. Six months later, it was 60% on the score. And then I think they hit the billion dollar valuation four or five years later on ultimately being one of the early unicorns.

And interestingly, as all of those things were built into mobile phones now, they’ve completely changed the business, but they continue to do really well, but they’ve continued to iterate the business. I think that having that kind of finger on the pulse early in the business was important to build the muscle in the business to be really responsive as the market changed.

Lenny Rachitsky: Sean, this is already amazing. There’s just a fractal of topics I want to explore from this very short conversation already. So the first is just follow this thread of basically you’re sharing kind of a growth strategy that I imagine you execute, is look for the percentage of people that would be very disappointed if your product went away, see who they are, see what they’re excited about and lean into that both positioning-wise, onboarding-wise, and probably also cut out stuff from your product that they don’t care about.

Durability of the Percentage & Sample Size

Sean Ellis: Yeah. And I was coming at it from a marketing perspective initially. Over time, I position myself more in a growth role with product and marketing as areas I could influence. But as a marketer, I probably didn’t have a lot of influence on a engineering founded company to say, “Let’s cut out stuff.” So it made more sense to say, “Let’s just sequence the onboarding so that we’re highlighting this and onboarding to this.” That was a little easier to sell.

Segmenting Audiences & Strategic Choices

Lenny Rachitsky: And just hearing that you can move this score so quickly without even changing the product substantially, I imagine what surprised a lot of people when you think about moving retention often is really hard. And maybe we talk about that, but I guess it sounds like there’s often something you can do that’s not very hard that might significantly shift this product market fit test.

Sean Ellis: Right. And then that ultimately moving retention is really hard, but it’s usually much more function of onboarding to the right user experience than it is about the tactical things that people try to do to improve retention.

Choosing Survey Tools

Lenny Rachitsky: Okay. I want to put a pin on that and come back to that because a really important topic. I’m going to come back to, say someone runs this survey and they get 40%, what should they have in their mind of like, “This is what this is telling me”? Because I think a lot of people are like, “I got product market fit. I got this. Let’s go, go, go.” What’s the best way to think about what this tells you?

Sean Ellis: Yeah, I mean it tells you something really important, which is, you haven’t created something that people don’t care about. So that’s an important insight. But until you deeply understand that product market fit, you kind of don’t have the tools to be able to grow the business. So that’s really the next step, is to dig in and figure out who considers it a must have, how are they using the product, what did they use before, what problem are they solving.

One of my favorite questions is… So I tend to have a lot of questions that I build off of that I’m using that filter, trying to drill into the users who say they’d be very disappointed without the product, and one of my favorite questions is, “What is the primary benefit that you get?” And then I use that initially as an open-ended question to kind of crowdsource different benefits people are getting. But then I run another survey where I turn it into a multiple choice question, force them to pick one of four distinctive benefit statements. And then the question that follows on that next survey is, “Why is that benefit important to you?” And then I start to get really good context.

So I actually came up with this question when I was working with an early YC company called Xobni, which is inbox felt backwards. And when I ran that question, basically the people who said they’d be very disappointed without the product we’re focused on, “Xobni helps me find things faster in my email.” So it’s great to know, okay, that’s the benefit. But when I asked, “Why is that benefit important to you?” They said, “Oh, I’m drowning in email.” I kept seeing that statement as a written statement. And so when I then was trying to figure out how to acquire customers, when I tested “drowning in email?”, that set such a good hook. That was the context that people were living in, that they were really responsive to the message of find things faster with Xobni and then a description of what Xobni is. So I think when you can really dig into the context of why that must have benefit is important to people, you start to get the ingredients to build that flywheel that leads to long-term sustainable growth.

From Leading Indicators to Retention Cohorts

Lenny Rachitsky: So what I’m hearing is whether you have 40%, whether you have 60% or even 7%, the actual best use of this tool is look at that percentage of highly disappointed and see what they’re looking for, what they’re excited about.

Superhuman’s Evolution of Survey Methods

Sean Ellis: Start drilling in, start feeling back that onion-

Follow-Up Surveys & PMFsurvey.com

Lenny Rachitsky: Start drilling in.

Sean Ellis: … and just deeply understand them and make sure that ultimately your product roadmap is doubling down on the things that are important to your must-have customers. Onboarding is bringing new people to the right experience. Your messaging is setting the right expectations, your acquisition campaigns are targeting people who actually have the need. And so it’s all about getting the right people to the right experience. And then even your engagement loop is about just reinforcing how to get people to experience that benefit more often.

Growth Priorities: Activation to Acquisition

Lenny Rachitsky: Awesome. And the 40% threshold, so what you shared is you basically emerged from just looking at tons of startups doing the survey and finding a pattern. How firm is that 40%? How big of a deal? Is it 39 versus 41?

Sean Ellis: I don’t think it’s that firm. To me, I think the real power is having some kind of target for the team to be shooting for that basically says, “We’re not going to aggressively start to grow until we hit this target.” And I think that as just a focusing piece is really important because I think one of the biggest challenges in an early stage startup is half the people feel like we’re years from having this product ready to grow, and half the people are like, “What are we waiting for?” Where if you can actually get people on the same page of what does product market fit look like for our business, and it’s at that point that we’re going to.

Before I ever heard the term product market fit, I remember the conversations back at LogMeIn in the mid 2000s of kind of like, “When do we step on the gas? What is the combination of factors that need to be in place before we start pouring fuel on the early fire?” And so yeah, I think that kind of nail it then scale it. It’s probably been a term that’s been around for decades now, but it’s all kind of pointing to that same concept of product market fit.

LogMeIn’s Activation Case Study

Lenny Rachitsky: How often have you seen false positives with this test where someone gets 40% and something is not right, they’re actually far from it? Or is it generally pretty accurate?

Deepening Understanding via Qualitative Research

Sean Ellis: If you’re having people say that they’d be very disappointed without your product, that’s a really good sign. What I can tell you is that not necessarily a false positive, but what is driving people to say they’d be very disappointed. One of my favorite books is Hooked by Nir Eyal and he talks about in the kind of engagement loop that your last step is investment.

And so I ran the survey on a business that I thought was a fairly commoditized business. Part of it I wanted to see, could I use the same go-to-market approach on a later stage company and use it to accelerate growth. And so this was a business called webs.com. They eventually got acquired by VistaPrint. But they’d been pretty flat for the year before I went in there. And then I started to use this approach to try to dial in their growth engine. I ran the survey thinking, “Yeah, you’ve had products like Wix and Weebly that have come on to the market since this more legacy website building product has been around. I personally think they’re a little easier to use, they’re a little better.” And so I didn’t have high hopes when I ran the survey, but it came back with one of the highest scores I’d ever seen. And it was like 90% of the people saying they’d be very disappointed if they could no longer use the product.

Defining Activation Metrics

Lenny Rachitsky: Holy shit. I’ve never seen that.

Sean Ellis: And I was like, “How could that be possible? This product is kind of a commoditized category. I wouldn’t even say it’s one of the best.” And then when I want to dug into it again, it comes back to that Nir Eyal Hooked model, is that the investment people have made in building that website, they put so much into that they know exactly how to make the changes and the kind of the CMS kind of side of things, they have spent a lot of time just making it beautiful. And so ultimately it was something that that was why they were saying they’d be very disappointed.

But fast-forward when I initially went in, still doing these things help the business resume growth and have significant growth over the next 12 months after we did these things. So still the signal we got from why people would be very disappointed without the product was important and speed to value. All the other things I think about in go-to-market for an early stage product still were relevant, but just I think they were a little stronger on the percentage he’d be very disappointed.

Even Eventbrite when I was there when we ran it was probably the second highest I’d ever seen. But with event organizers, if they’ve already set their event up on that platform and they’ve sent it out to their list and all those people are coming in and they’re managing their event, again, they’ve invested a lot in the platform. So sort of switching costs I think can factor in there. So it’s a function of both switching costs and utility of the product.

Growth Engines & Growth Loops

Lenny Rachitsky: So that’s a question I wanted to ask is, what’s your guidance on when to ask this question? What I’m hearing is, if you ask it very far along the journey, when they’re very invested, you’ll get a much higher score. Is there any advice on the timing and the best time to ask this question to your users?

Sean Ellis: What I recommend is a random sample of people who’ve really used your product. So they’ve gone in, they didn’t just sign up, but they went in and hopefully hit that deviation moment. They’ve used it twice, two plus times, and they’ve ideally used it, say, within the last week or two weeks, so they haven’t churned yet. So if it’s a random sample of those people, that’s kind of the ideal time to ask it.

Choosing Where to Focus Growth Efforts

Lenny Rachitsky: Got it. So basically it’s people that have activated whatever that means to you and have been using it for a couple weeks?

Sean Ellis: Yeah.

Finding Growth Inspiration via Customer Conversations

Lenny Rachitsky: Not people landing in your home page, not people just signing up, not people months later.

Birth of the Dropbox Referral Program

Sean Ellis: Not people who’ve seen a demo of your product, but it’s people who actually have experienced the product. But it’s okay if you’re hitting people who’ve used it months later, but in that Lookout example that I gave, if I’m testing people’s perception of the product after I made updates to the onboarding, I’m going to only want to survey people who went through the new onboarding.

Lenny Rachitsky: Yep. In the experimental. Yeah. Okay. So I asked people on Twitter what to ask you. A lot of people had a lot of awesome questions. I’m going to sprinkle in a couple of these questions throughout the chat.

Freemium & Word of Mouth

Sean Ellis: Sure.

Engagement & Natural Usage Cycles

Lenny Rachitsky: One came in from Shraaz Doshi, a popular guest of the podcast.

How to Choose a North Star Metric

Sean Ellis: One of the ones that I listened to recently.

Lenny Rachitsky: Amazing. I think it’s the second most popular episode behind Brian Chesky. Okay. So he had a question of just, “What are the limitations of the score? When does it break down? When should you not use it if ever?” Is there anything of just like, “Here’s when it’s not going to work for you”?

Evolution of Growth Strategies

Sean Ellis: Yeah. I think one-off products would probably, like, how would you feel if you could no longer watch the movie you just watch? I wouldn’t care. Even when I run a workshop, I don’t run this as part of my survey after I do a workshop because how would you feel if you could no longer attend the workshop you just attended? It doesn’t make sense. So I’ll ask an NPS question as my filtering question so that I’m looking at focusing in on feedback of people who love it, also then through a separate lens, looking at people maybe who would be my detractors. So I think one-off products are probably not good products to run the question on. There may be other places as well that I’m not thinking of right now, but that [inaudible 00:25:00].

ICE & RICE Prioritization Frameworks

Lenny Rachitsky: It sounds like not many. What I’m hearing is it’s generally widely applicable.

Sean Ellis: Yeah, I think it is, at least from my perspective. It’s been really useful for me anyway.

AI’s Impact on Growth Work

Lenny Rachitsky: Awesome. Okay. And then the follow-up question from Shraaz is, and I kind of asked this, but I’m curious if there’s anything more here, just, “Have you seen any instances of startups over relying on the score prematurely declaring product market fit when in reality they haven’t reached it yet? And just are there any other caveats of like, ‘Cool, I got 40%’?” Is there anything else you should know, like, ” Okay. But maybe check this one thing”?

AI & Cross-Functional Growth Challenges

Sean Ellis: Yeah, I mean, I think to me it’s kind of like what really is the definition of product market fit is the definition that people who get through my crappy onboarding and actually experience the product love it. And if I’m able to retain those people, that means I have product market fit. Or, is fixing that crappy onboarding part of getting to product market fit as well? I think that’s up for debate.

So to me, the hardest, I wouldn’t obsess on onboarding if I know those who kind of get through the challenge of getting started with the product still don’t like the product then feels like it’s a core product issue or wrong people using it in the wrong way issue. But once you have that, then ultimately it doesn’t mean that you’re ready to grow. When I focus on growth, then customer acquisition is almost the last step. Once I validate that it’s a must have for those early users, then I’m thinking about, “Okay, how do I optimize speed to value? How do I make sure that people have the right prompts to come back and use the product at the right time so that’s kind of more of that engagement loop? How do I get my existing users to bring in more users if there’s something that makes sense on that end? Even how do I optimize my revenue model?”

Once all of those things are working well, then I’ll obsess on the customer acquisition side. But customer acquisition is so hard that if you’re not really efficient at converting-

… customer acquisition is so hard that if you’re not really efficient at converting and retaining and monetizing people, you’re going to really struggle on the customer acquisition side.

Lenny Rachitsky: Yeah, cool. And we’ll talk about customer acquisition/growth.

Asking the Right Questions at the Right Time

Sean Ellis: Sure.

Lightning Q&A Session

Lenny Rachitsky: Another question I wanted to ask, and a couple listeners asked, is the 40%. I had Jag from Nubank on the podcast, I think you may have worked with them, and they use 50% as their threshold because apparently Brazilians are very nice.

Sean Ellis: Yeah. Optimistic I think is what I said.

The Customer Support Analogy

Lenny Rachitsky: Yeah. I guess the question is do you find instances where you should increase that percentage? And in B2B, is anything different? Do you change the percentage in B2B? Any advice there just when you adjust the threshold?

Sean Ellis: Yeah, I hadn’t really thought too much on that. Again, for me, generally I’m trying to just figure out is this a product that can grow? So if I got a 37%, am I going to be like, “Oh no, this would be impossible?” Or if I had a 70%, does that mean I’d say, “Oh yeah, I want to jump in and work with this company?” It’s more nuanced than that. Obviously, if it’s a 70%, but I have no idea how I grow the business, I’m going to be stuck there. But I do think he brought up a really good point that, culturally, some people are going to be more optimistic or pessimistic. Interestingly, when I came up with the question, I used to just use a normal satisfaction question.

When I was working at Xobni, I’m just an intensely curious person anyway, so I’m just trying to dig in and understand the customers, and so I’ve always done lots of surveying. But at Xobni, I was going to use my filter as a satisfaction question, so how satisfied are you with this? I’m very satisfied. I’m somewhat satisfied. And our main customers were actually senior management, and so I thought senior management’s never satisfied. I’m going to get always this super lukewarm thing. How can I change this question to give me a more real answer from these guys? Well, if I flip it and say, “How would you feel if you could no longer use this product?” I’ll probably get a more honest answer back from them. And of course, they’re very disappointed if they can’t get what they want.

And so initially it was just for the case of Xobni, but then I went to Dropbox right after Xobni and like, “Oh, I’ll try the question again.” And the insights I got back were really useful. And so each company I went to, I kept using the question. I’m like, this works way better than your typical satisfaction question. But initially, it was more about thinking just senior management to get a more honest answer out of them.

Behind the Scenes at TikTok

Lenny Rachitsky: So that’s the origin story right there?

How to Connect & Collaborate

Sean Ellis: Yeah.

Lenny Rachitsky: Wow. That senior managers are just very harsh and they don’t need anything?

Sean Ellis: Yeah.

Lenny Rachitsky: And you have to flip it. That is so interesting. That question is such a good reminder of how hard it is to build anything people really would be disappointed not to have. That’s why this works so well. People are like, “I don’t need this. Who cares?” That’s the core of this, is just that is hard.

Sean Ellis: Especially when I first moved to Silicon Valley. The first 15 years of my career were not in Silicon Valley, and so I was in Eastern Europe and then New York and then Boston. But you move to Silicon Valley and you have people who get really excited about technology for technology’s sake. And so just something being cool is like, “Isn’t it cool that we can actually do this?” drives a lot of people. And so to me, I’m very practical. If it’s not something that is really bringing value to people, then the likelihood that that product’s successful long-term is going to be pretty low.

Even, interestingly, at Dropbox, through the six months I was there, I’d ask one question multiple times a month. I broke the early beta users into a bunch of different lists. And I’d ask, “Which best describes you? I like to be among the first to try cool new technology, or, I only try things that I think will be useful for me?” And over the six months, it flipped from 90% being people who try things that they want to try cool new technology to six months later, it was people who only are going to try something that they feel like is useful. But what’s cool is just because what motivates you to try something is you’re an early adopter and you want to try something cool, if you’re going to keep using it, it’s because it’s giving you some utility. And so I can still use those early adopters to help me figure out where’s the value inside the product.

Lenny Rachitsky: Awesome. So actually, two questions along those lines. How durable do you find this percentage being? Say you hit 40%, how often does that fade and go away versus stay there or go higher?

Sean Ellis: Yeah, I haven’t seen it really fade back down, but I’ve seen companies fail despite having it. And I think a lot of times then, it becomes an execution challenge. Once you have product-market fit, not everyone’s going to be a good executor. But before that, I think getting to product-market fit, obviously there’s a lot of methodology for doing it today that might make it a bit easier for people, but I still think it’s fairly random and pretty dang hard. And so ultimately, the risk factor of creating something that people care about is really difficult. So if you can get to the point where you have 40% of the people who are using it saying they’d be very disappointed, and you have a reasonable sample size. Let’s say you’ve got 10 people and four of them said they’d be very disappointed without it, you’re still going to get something useful from those four. But I wouldn’t say that’s a sample size that you can really go to market on, so yeah.

Lenny Rachitsky: What’s a good sample size you look for of just, “Okay, this is actually good data I want to rely on?”

Sean Ellis: It’s really funny. So much of the stuff I self-learned, but I basically at one point said I need at least 30 responses, and I just thought I randomly made up a number and then I had people telling me, “Yeah, 30 is the minimum that you want on stuff.” Okay. And even when I first created this survey, I remember showing it to the co-founder of SlideShare and her PhD was in survey-related stuff like cognitive psychology, but she basically said it was really about surveying. And she’s like, “This methodology is amazing. How did you come up with this?” And so having some of that validation around these things helped. But a lot of it was just, again, driven by my own curiosity and also just knowing that that failure is such a likely outcome that trying to reverse engineer that failure, and then the number one reason for failure would be that people don’t actually care about the product. And so when I find that, that’s a really good sign that we’re now down to an execution challenge.

Lenny Rachitsky: And there’s this obvious element of you may have product-market fit with people, but that group might end up being very small and the business you build around it could actually be cool, but it’s not going to be a massive business. Is there anything there you can share? It’s hard to know the size opportunity even though some people really, really like it.

Sean Ellis: Yeah, I talked about I go to a multiple choice after I initially use open-ended questions to crowdsource the different use cases. But then I try to force people in a bucket, and then I can run filters on each of those buckets and I’ll be like, “Oh, people who use it this way are like 60% likely to be very disappointed without the product, but people who use it this way are 35% likely to be very disappointed, but way more people use it the 35% way.” And so then, do you want that intensely loyal group or the much broader group that’s maybe a bit less, but almost there?

I think that becomes a bit of a strategic conversation of do we want to have a better chance of surviving, going after a niche that we know we can serve well? Or have we raised so much money that we have to go after a really big market, and one that’s not going to be long-term? But maybe then you’re like, “Okay, once I have traction in that market, I can start to try to appeal to some other markets.” But I think that’s where some strategic decisions come in.

Lenny Rachitsky: Do you have a heuristic of which you often recommend or is it very dependent on the situation?

Sean Ellis: I prefer a more passionate customer base and work from there, just because I think your biggest competition when you’re really innovating is just being irrelevant. And so if you’re deeply relevant to anyone, I think that gives you a much better chance of long-term success.

Lenny Rachitsky: Awesome. That’s a really good insight. Okay, two more questions along this line and then I want to talk about growth strategy. One very tactical question. Is there a tool you recommend for doing this sort of survey? Do you recommend inline? In the product? An email? Something else?

Sean Ellis: I’ve used a lot of different tools. I actually had a survey business that I sold to private equity years ago. It is called Qualaroo. That’s an inflow survey tool. I think just using SurveyMonkey with emailed surveys works fine. And for me, it’s a lot more of what’s pleasant for the customer to fill out and then what’s going to give me something where I can work really easily with the data? So at Bounce, for example, they had already intercom in place that had just introduced surveying, but it was a really crappy customer experience, at least at that time. That’s been almost a year now or actually a little over a year. And so I’m really sensitive to is it a good survey experience for the consumer itself? But yeah, I don’t think I’m stuck to any one platform there.

Lenny Rachitsky: Such an important topic. Just, again, to remind people why this is so important, one of the most common questions founders ask is, “Do I have product-market fit? Have I built something people want?” That’s just an endless series of, “I don’t know. How do I know? When do I know?” And this is telling you in a really interesting way. So your advice is this is a leading indicator. You don’t actually know until people actually start using it and whether they retain and continue using it. Is there just advice on the shift you make from relying on the survey to actually looking at retention cohorts? Is it just once you have enough data, once you have a couple of cohorts, then start looking at that? Forget about the survey?

Sean Ellis: Yeah, but retention cohorts don’t give you any of the qualitative insights into the why, so that’s why we continue to do the survey. So initially I would say if the survey comes back and it shows whatever your target number is… If you want to be Nubank, it’d be a 50%. Or two of the companies I launched, we launched in Hungary, and I would say it was the opposite end of the spectrum of Brazil, maybe more pessimistic than the average culture. And so maybe 30% is good enough there, but that ultimately, whatever your target is, that you have the signal that says, “Okay, we have enough value here. Let’s start working on growing the business.” But while you’re working on growing the business, I would be paying attention to those retention cohorts. And if you’re churning out all the customers who were saying that they’d be very disappointed without the product, then okay, let’s retrench and rethink, do we really have product-market fit here and what do we need to do to get it if we don’t?

Lenny Rachitsky: Awesome. And speaking of Nubank, if anyone wants to see how a company has actually operationalized this in the way they operate, that there’s an episode that we’ll link to in the show notes where every new product at Nubank they build, before they launch it, they wait for 50% threshold. For people to say 50% of people would be disappointed if this product did not exist as they’re developing it. And only then do they launch it publicly.

Sean Ellis: Yeah, I think they even do it down to the feature level.

Lenny Rachitsky: Wow.

Sean Ellis: So if you think about it, how would you feel if you can no longer use this feature starts to give you, again, the signal, is that feature a must-have feature? And if it’s not, maybe we shouldn’t have it. And so yeah, I was super excited when I saw how they were using the survey and they were doing it before I engaged with them.

Lenny Rachitsky: Oh, wow. That’s awesome.

Sean Ellis: But they were doing it, I think, from pretty early on in the business.

Lenny Rachitsky: The reason they can do this is they have a lot of users. They have millions of millions of users, so they can ask some small percentage of people this question. Because people hearing this might be like, “Oh my God, how many times am I going to be asked this question when I’m using this feature?” But they have a lot of users, so it’s easier.

Sean Ellis: Yeah. Yeah.

Lenny Rachitsky: Okay. Last question, I promise, along these lines. Say someone is listening and they’re like, “Okay. Man, I’m getting 10%, I’m getting 15%. I don’t know what to do to increase my product-market fit.” You should have just a strategy of just dig into the people that are very disappointed and see what they have to say. But any other advice/what do you find often works in helping people move from, say, 10% to 40%?

Sean Ellis: Yeah, so one of the things that’s cool about almost open-sourcing the survey approach is, again, watching how Nubank has evolved their usage. But one of the other companies that I think used it in an interesting way is Superhuman. And I would say that they basically ended up probably putting a lot more momentum behind the question than it had even before. They posted something about how they did it on First Round Capital’s blog. And what I have always said, and again, it’s me coming at it from probably initially a marketing background, which is I’m taking the product as a fixed thing, and how do I actually figure out how to market and grow this product? And product changes are going to take a long time, and so what are the variables that I can control with a marketing background? So one of the things I’ve always said is just ignore the people who say they’d be somewhat disappointed. They’re telling you it’s a nice to have. They’re as good as gone, so just ignore those guys.

I’ll put one piece in the middle there before I say what Superhuman did. The reason that I say ignore those guys is that if you start paying attention to what you somewhat disappointed users are telling you, and then you start tweaking onboarding and product based on their feedback, maybe you’re going to dilute it for your must-have users. And ultimately, it becomes kind of good for everyone but not great for anyone. And so that was my fear of trying to read too much into the users who say they’d be somewhat disappointed. But the Superhuman guys actually found, I think, a good way around that where they said, “Okay, what is the benefit that my must-have users are focused on? And then of the users who say they’d be somewhat disappointed, so the nice-to-have users, of those users who are also focused on that benefit, what do they need in the product for it then to become a must-have for them?”

And so they’re staying true to that core benefit, but they’re trying to essentially take those on-the-fence users and moving them up. And so I think their way of approaching that addressed what my concern was, which is are we going to break it for the must-have users?

Lenny Rachitsky: That’s an awesome insight. By the way, did Rahul and the team there just do this on their own or were you involved in any way in this at Superhuman?

Sean Ellis: No. That’s the same thing. Like I said, I wasn’t initially involved with Nubank. I wasn’t involved with them. We wrote about it in our book in 2017, and so I think that I got it out there. But I actually teamed up with the Kissmetrics team in 2012, and essentially published this survey on survey.io where we just made it freely available for people and a really easy template to prepare and send out, and the how-to guide on it. It was all just free. Kissmetrics is using it as maybe lead gen. And for me, I just wanted a way to put something out for the community. And so it’s been out there for a long time, so it’s not surprising that different companies have found different unique ways to use it.

Lenny Rachitsky: That’s awesome. I think that post is one of the most popular in First Round. It really had an impact on a lot of people.

Sean Ellis: Yeah.

Lenny Rachitsky: So just to repeat, the approach you recommend for when you’re digging into… I wrote this down. When you were talking for how to dig into what benefit people are finding, your advice is it’s basically a follow-up survey to the extremely disappointed people asking them what is the primary benefit you get? It’s an open text initially. Then once you get a collection, you do it sounds like another survey as multiple choice. Here’s five benefits-

Sean Ellis: To a different group of people, to be clear.

Lenny Rachitsky: Different group. Yeah. Got it. Awesome. And then it’s like, which of these four or five benefits is what you’re getting out of this product? And then the question is, why is this benefit important to you?

Sean Ellis: Eventually the survey.io got closed down, but essentially the template that I typically used was then moved to PMFsurvey.com. And so you’ll see some other questions that I have on there as well, like what would you use instead if this product were no longer available? And that’s one of the interesting things is you start to see people who say they’d be somewhat disappointed, usually, they’re focused on a commodity use case and they know an easy alternative to switch to. So to be a must-have, it needs to be both valuable and unique.

Lenny Rachitsky: Okay. Anything else on this topic of the Sean Ellis task product-market fit test before we move on to growth strategy advice?

Sean Ellis: No, I think that’s it.

Lenny Rachitsky: I think we did almost an hour on that one topic, which I love because I feel like this is such a powerful tool that I think people sort of know and have used, but I think there’s a lot of opportunity to use it more effectively. And all the stuff you pointed out about it’s not just you have this threshold goal, let’s move, let’s grow. It’s like, this is how you figure out how to make it better and better and grow faster and faster. And it’s actually a good segue to talking about growth.

Even though you coined the term growth hacking, you spend most of your time on the opposite, essentially, which is helping companies figure out sustainable growth strategies, not just a bunch of hacks to grow for a little bit and then disappear. And from what I’ve seen, it’s all rooted in this idea of product-market fit and what helps you find product-market fit, and I imagine many of the stuff we’ve talked about.

Sean Ellis: Yeah. Just one quick interjection there is that when I coined growth hacking, I did not think of it as a bunch of one-off hacks. What I thought of it was what’s more about what is the way to ultimately drive sustainable growth? But it’s, over time, maybe more interpreted the way you described it, but just to jump in and say that.

Lenny Rachitsky: That’s a really good clarification, so how did you actually initially frame it when you first-

Sean Ellis: Yeah, I just said it’s about looking at every single thing that you’re doing and scrutinizing its impact on growth in the business. And particularly, I think most marketers, when I first moved to Silicon Valley, most CEOs who were asking me to help their companies, they were saying, “We need help with awareness-building,” and I’m getting introductions from top VCs. And so, so much of, I think, the way people were approaching growth was marketing textbook how to approach it. And startups just don’t have the luxury to do all of those things, and so you got to really focus on how do I acquire customers to an experience that’s going to make them keep using this product? And so maybe I picked the wrong term in calling it growth hacking, but I think it at least opened the conversation to getting more people thinking about maybe we should be thinking about growth in a different way than as it’s traditionally taught in marketing courses in school.

Lenny Rachitsky: Is there another term you think you should have used? Do you always think back, I should have called it this? Is there anything that you’ve had in your mind?

Sean Ellis: I don’t. I think sometimes having something that’s a little divisive is almost better because it’s too easy to just go completely unnoticed. But I was trying to put a name on not just how I was approaching growth, but seeing Facebook obviously had a very different approach to growth than most companies. LinkedIn, Twitter, there was a handful of companies that were approaching it in the same way I had previously been approaching it, and I just thought this thing needs a name. And so I sat down with a couple of friends, came up with a name and it stuck. But yeah, obviously from day one it was pretty divisive with different groups.

Lenny Rachitsky: That’s a fun story. Thanks for sharing that.

Okay, so talking about growth and helping companies figure out how to grow. Say you go to a company, they’re getting 42% on the Sean Ellis test, and they’re like, “Okay, cool, let’s start thinking about growth.” What’s your first piece of advice to them to start when they’re thinking about growth? And then just broadly, how do you approach helping them figure out how to grow?

Sean Ellis: Ultimately, it’s about trying to get as many of the right people to that same state that we just talked about with the must-have users, so trying to get as many people to experience the product in a way where they’d be very disappointed if they could no longer use the product. And so that’s not just acquisition, which is how most companies think about… Initially, it was awareness then maybe the more developed way was, oh, let’s at least focus on profitable acquisition. But in my experience, the hardest part really sits inside the product team, so how do you shape that first user experience so they actually use it in the right way and it’s not so difficult that they give up? And that ultimately, we understand what makes it a must-have product. And then what we’re trying to do is build a… Yeah, it sounds kind of theoretical here, but I can go into the details on how, but build a flywheel around that must-have value.

So step one would be understand it. Step two for me is then figure out a metric that essentially captures units of that value being delivered. And so when I think about a north star metric, that’s what I’m thinking about is something that reflects how many people are coming in and experiencing that product-market fit experience, whatever that is. And it’s not just me telling them, “Here’s what your north star metric should be.” It’s that ultimately the team needs to decide that together. And then really just diagramming, what are all of the different ways that we can grow that north star metric? So that’s where you start to actually build, I call it a value delivery engine, but it’s what does our onboarding look like? What’s that aha moment? That activation? What does the engagement loop look like? Is there any referral? Try to capture it as it is today.

And then, from there, thinking about where are the biggest opportunities for improvement, so those high-leverage opportunities, and then ultimately starting to run experiments against those opportunities. Generally, I think I touched on it a little bit earlier, but generally the sequence that I like to do is start with activation because that one’s just so critical and it’s easy to get lost in between, especially for an early product. The product team’s so focused on the roadmap. We’re two features away from not even needing marketing anymore. This thing’s going to take off. And then a marketing team so focused on bringing new people in, but how do you get those new people to a great first experience falls through the cracks a lot of times. So a lot of focus on activation and then engagement and referral and getting the revenue model right. And then once each of those pieces are working well, then starting to really obsess on the channel side.

One thing that I’ll say. When I go in and directly am involved with a company on the acquisition side, I am thinking about my hypotheses on the acquisition pretty early on, because if I go into it and I have no idea how we’ll acquire those customers, I’m not real confident I’ll figure it out when I’m there. So I want to have two or three things that seem pretty viable as ways to profitably acquire customers, and knowing that once I get deep into it, I’ll probably come up with one or two more and I’ve got five, one of them’s likely to work. But I don’t want to just be under the pressure of having to come up with that once I come in, if I don’t at least see an angle from that before I get involved with the company.

Lenny Rachitsky: What I’m hearing is when you come into a company and they’re asking, “Sean, how do we figure out how to grow this thing?” you actually focus first on activation onboarding, and we’re going to talk about all these things. Then, after that, basically these are priority order for you. Then it’s flywheel engagement referral stuff to see if there’s a way to drive that. Then revenue. How do we make money with this and how do we make sure we’re doing this profitably? And only then do you start to go big on acquisition top-of-funnel growth.

Sean Ellis: Yeah. I may need to do some acquisition stuff before just to bring enough flow-through, but I’m not obsessing on how scalable is this. It’s just like, yeah, let’s get enough people coming through that we can start to take the slack out. Part of it comes down to that the acquisition side is so competitive now that if you’re not really efficient at converting and retaining and monetizing customers, you can’t find scalable, profitable customer acquisition channels.

Lenny Rachitsky: This is fascinating because I think a lot of people probably do the opposite. Start driving a bunch of growth to a product, then we’ll fix onboarding, then we’ll figure out how we’re making money, and referrals comes along there. So I think this is really important for people to hear. So again, the reason you invest first and focus a lot on onboarding/getting people activated is because that is very correlated to retention and this must-have customer, this, “I’ll be very disappointed,” customer.

Sean Ellis: Yeah. And they’re at highest risk of losing them at that point. They-

They’re at highest risk of losing them at that point. They’re probably a little skeptical about a promise that you put out there, but they’re intrigued enough to want to use it. But until you get them to that must-have experience, until you kind of get them to that aha moment, they’re at their high risk of being lost. And so a lot of people focus on, “Well, I better get their email address or their phone number.” But then you’re essentially having to reacquire them at that point. So to me, if you can collapse that time to value, I can give you a couple of incredible examples of when we [inaudible 00:54:38]

So at LogMeIn, when we initially tried to grow the business, I was stuck at being able to spend… I couldn’t spend more than $10,000 per month profitably trying to grow the business. And then I dug into the data and I saw that 95% of the people signing up for LogMeIn. So LogMeIn, at the time free remote access for your computer. And so you install software and you can control it from any other computer. So 95% of the people signing up never once did a remote control session. And so not surprisingly, then I had to get my monetization off the 5% who did that was really limiting my ability to find channels that worked.

Credit our CEO with this, that I shared the data with him and he basically told the product team, “We are putting a complete freeze on the product development roadmap.” So every single person from product, engineering, design and then also said to me, “Stop trying to find new channels.” The three of us on the marketing side are all going to focus on improving the signup to usage rate. And so in three months, we improve the signup to usage rate by a thousand percent. So we went from only 5% of people using the product to 50%. I went back, tried the exact same channels that previously only scaled to $10,000 a month.

Now they scaled to a million dollars a month with a three-month payback on marketing dollars invested. 80% of new users were coming in through word of mouth. So there was this major inflection point by just focusing on activation.

Lenny Rachitsky:

And yes, if you need AI-ready data for your SaaS product, then Merge is the fastest way to get it. So want to solve your organization’s integration dilemma once and for all? Book and attend a meeting at merge.dev/lenny and receive a $50 Amazon gift card. That’s merge.dev/lenny. What do you find often works in helping increase activation? I know there’s a million things that people do, but I guess what are three or four things that you think people should definitely try to help improve activation and their onboarding conversion?

Sean Ellis: One of my favorite quotes is a quote from a guy Kettering, who was a hundred years ago at GM running innovation. And he says, “A problem well stated is a problem half solved.” And so I think a lot of it comes down to not the things you try, but how you deeply understand the problem that’s preventing someone from using your product effectively. And so I’ll just give you one example. We had one channel after we made a lot of these changes and had already driven a ton of improvement in the LogMeIn onboarding. We found a demand generation channel that was really cheap and the economics looked great, but at just the download step we had a 90% drop off rate.

And so we A/B tested a bunch of different things there to try to improve that conversion rate, and then finally 10 plus tests, not able to improve it. Finally, someone said, “When these people are registering. Why don’t we just ask them why they signed up and didn’t download the software?” And so we didn’t want to do it in too kind of a creepy way. So we made it look like a note coming from customer service. This channel was sending 200,000 people a day, so 20,000 people were converting to registering. So we had essentially 20,000 people we could email and then 18,000 of them who didn’t download. And so we just asked, “Hey, notice you haven’t had a chance to use the product yet.

It looked like it was coming from customer support. What happened?” And the answer we got back and not a formal survey was, “Oh, this seemed too good to be true. I didn’t believe this was free.” I mentioned to you we were one of the first freemium SaaS products out there. And so people were skeptical, especially in a demand gen channel where they hadn’t seen a radio or a TV advertisement from our competitor who was a premium only product. These were people who were discovering the category for the first time they were getting there. Once we articulated what the problem was, our next test gave us a 300% improvement in the download rate, which was…

We gave them a choice, download a trial of the paid version or download the free version, put a big graphical check mark next to the free version. But when they saw we had a business model and a trial of a paid version, the free version was credible. And so that essentially made that channel work for us. So I think again, it’s that combination of qualitative research, looking at how others did it. We had this theory, our previous company had been a game company that didn’t require a download. So initially we had this theory that maybe just downloadable software can’t be in the millions of new customers a month and so we’re being unrealistic here.

But then we were like, “Are there any counter examples to that”? And no, the instant messengers are downloadable and they have hundreds of millions of customers, so let’s study their download and install process and see if we have any ideas that we could borrow from that. So again, some inspiration, tried some of those things, it was a combination of just trying a bunch of different stuff that ultimately led to, I wouldn’t say there was one big gain, it was a bunch of small gains.

Lenny Rachitsky: Awesome. So a few things for people to try if they’re like, “Hey, how do I improve my activation rate? How do I improve my conversion rate?” Just drill further into what is stopping people from progressing. Ask them, “Why did you bounce here? What did you think this was going to be? Why didn’t you end up using this?” Look for inspiration from other products, I think people probably already know that. You talked about earlier this idea of the positioning, having a big impact of just figuring out.

They want an antivirus software. Let’s make that very clear. “Hey we’ve got the best antivirus software, that’s what we’re here for.” So there’s probably just messaging that you find works a lot of times, right?

Sean Ellis: I mean your two big levers on driving a conversion are increase desire, reduce friction. And so you definitely want to increase the right desire. Sometimes it can also just be reminding people along the way of what benefits you’re going to get. In the case of LogmeIn, it was probably the most complicated funnel I’ve ever seen because you couldn’t even get to the aha moment while you’re sitting in front of the computer. You had to actually go to a different computer and to use the service to remote control the computer you’re in front of.

So it’s not surprising that there was so many steps where we could lose people, but we just weren’t that intentional about designing each of those steps initially. And it wasn’t until we thought through why would we lose someone at this step and studying the data, which steps were we losing the most people at? Then deeply trying to contextualize why are we losing them there, coming up with a set of tests that we want to run and then having a good way of deciding which one to test first and ultimately focusing the tests on the areas where we’re losing the most people.

Lenny Rachitsky: The other element of this is coming up with an activation metric and aligning on here’s what we consider so activated. I know this is very dependent on the product, but any advice or heuristic for how to help people decide this is our activated user.

Sean Ellis: I tend to start qualitatively. So just like when do I think they’ve had a good enough experience with the product to really know it? And so in the case of LogMeIn, it was pretty easy. If they didn’t do a remote control session, they didn’t use the product. There was no value along the way there. And then at least try to see if there’s a correlation to long-term retention of doing that. Causation is you need to do some experimentation to prove causation. At the very least, I want to see that correlation, but if I start with two or three ideas of what it might be and then go and study the data, that can help you focus.

But again, I don’t think there’s necessarily one exact right answer of what is that aha moment. There might be two or three different things. I think it’s that intentionality about picking something that’s experience-based and saying, “What is a likely experience that someone’s going to get a good enough taste of this product?” And then I do see some companies that are like, “Well, the activation moment should be, they’ve used it a hundred times.” That’s going to correlate to long-term retention, but it’s just not very actionable. It’s so far down the user experience.

So ideally if there’s a way that I could get them there in the first session, in the first day, that’s great. And so it’s sort of something that’s value that can be experienced super early. To give you an example from the first company I worked on was a game company, where I actually flipped it and basically instead of making a traditional funnel where they could play our games after they signed up, I made our games the advertisements. So basically we syndicated our games to 40,000 websites.

They started gameplay experience on the other website, then they would get a message that they now have a qualifying score and if they register, they’ll be in the drawing for the weekly cash prize and then we could pull them into multiplayer games on the site. And so it’s kind of the strategy that YouTube used to grow, but it was two years before YouTube introduced the approach.

Lenny Rachitsky: It feels like you basically created Zynga, is what I’m hearing there. So let’s move further down the funnel. So we’ve talked about activation, onboarding. The next phase that you focus on is basically some people call this growth loops, growth engines, flywheels. Basically it’s the thing that helps your business grow and something I am curious if this resonates.

I found there’s basically four ways to grow and usually one of these engines is responsible for almost all of your growth. So what I’ve seen is basically you’re going to go through sales, you’re going to grow through SEO, you’re going to go through virality, word of mouth or paid growth. Does that resonate? Does that feel right?

Sean Ellis: And I wouldn’t say it’s necessarily one or the other. I think Bounce is a really interesting example where SEO is super important for Bounce. So people who are essentially saying, “Luggage storage, Paris. Luggage storage…” Most people when they’re trying to find a place to store their luggage, they’re starting with Google, but at the same time, a huge percentage of the people who use Bounce are dragging their bag down a street over cobblestones in Paris. And then they pass a sign that says, “Store your bag here for $5 a day.” And it’s like, “Oh, no-brainer.” And so 10,000 partners around the world means that there’s a lot of people in the right situation on the demand gen side.

One would be, I actually think of kind of… I’m not sure how it would map to this, but demand generation versus demand harvesting. And so one of those examples would be a… Demand generation example, when you see the signs when you’re passing, it’s high context, right place. And then obviously the demand harvesting would be anyone who’s Googling. And so they do paid search and organic search there.

Lenny Rachitsky: Interesting. I don’t see that sign approach work often, but I definitely have seen it work. Like Yelp I think grew in a lot of ways of just little Yelp stickers in all the restaurant. DoorDash I think probably grows through that.

Sean Ellis: I think every business could be a little bit different, but for Bounce it makes sense that that would be a really good opportunity for them.

Lenny Rachitsky: How do you help a business figure out which area to bet on? Whether they should go paid, whether they should go SEO, whether they should hire sales. Sales is probably an easier one. B2B, you’re probably going to have to be a sales team, I guess just to help them pick, “Here’s where you have a big opportunity.”

Sean Ellis: Again, it kind of comes down as I’m going into it, I’m thinking what are the realistic customer acquisition angles for this business? And I want to have ideally two or three that I’m coming into it with, but it’s going to… Obviously Dropbox is a classic one of like, “Oh man, this product…” User get user is going to be just a classic. There’s file share built into it, folder collaboration. There’s so many pieces of it that cross from one user to the next. But interestingly, it was fairly similar to LogMeIn in some senses, it’s two businesses are solving similar problems in different ways. Where LogMeIn, we grew almost entirely off of paid search. And part of it again is that for us, we had a competitor that was spending tens of millions of dollars a month creating the category with a premium only product through radio and TV advertising. GoToMyPC, they’re creating all this latent demand. And so it just made sense for us to disrupt them with a freemium service and to insert ourselves in the flow of someone… What was that thing that I heard about on the TV commercial? And now they go and they Google it and same thing, but free. So we weren’t really pushing for differentiation, but just really trying to harvest that.

So I couldn’t do that at Dropbox. No one was looking for when I went there. And so we tried a little bit with search to see can we make it work on cloud storage or backup or kind of going to some of these traditional categories. Cloud storage wasn’t even a traditional category at that point, but backup was, and it was fairly expensive and there was just not that much demand there that way. And so it just made more sense to focus on the user get user loops at Dropbox.

I think basically for each business it’s just thinking about what’s unique for that business that is going to open up channel opportunities and everyone’s going to be a little bit, I think jaded from whatever the last thing that worked really well. They’re going to think they can apply it in the next business. But after enough times myself, I tend to get the most inspiration by just talking to customers and finding out how did they find it, how do they typically find something like that? And that starts to give me some ideas as well.

Lenny Rachitsky: I think that last point is really powerful and I’m just writing it down. You said, essentially one of your tactics is talking to users, asking them how did you find this product and how do you normally find products like this? Is that the second question? I think it’s similar to your [inaudible 01:21:02] test. It’s such a simple question, but it’s so powerful because how else will people find your product? They go to a place to find stuff like this, and I searched Google for folder sharing. There’s so much there that you just skip over.

Sean Ellis: I think the reason that you don’t actually hear people taking the obvious route there a lot of times is because, and I used to be in the same thing, that people tend to be either over indexed on qualitative or over indexed on quantitative. So it’s like analytics, I’m going to get all my answers from testing and analytics or I’m going to get all my answers from traditional customer research. And I was very much in that initial camp for the first five years of my career. I’m just going to measure everything and test the heck out of things and find stuff that works. But I had a VC who was our lead VC at LogMeIn who just said, “When was the last time you talked to a customer?”

Just pushed me to survey and talk to customers all the time. And at first I gave the smart-ass answer, “I don’t care what they say, I care what they do.” And he’s like, “No, you got to talk to him.” Then just to appease him, I would try to have a conversation every day because he was in our office a lot and so I could say, “Hey, yeah, I talked to a customer today,” when he would ask me. But I started finding that my experiments were so much better the more I talked to customers, and eventually I became very much… The blend of qualitative and quantitative research leads to much better tests.

Lenny Rachitsky: That is another amazing story and insight. It’s so interesting that people sometimes think of you as growth hacker guy experiments data, when most of the advice we’ve been sharing so far is very qualitative driven, very survey driven, targeting customers driven.

Sean Ellis: And it is just really hard to run good experiments when you can’t deeply contextualize what’s going on.

Lenny Rachitsky: I love this. By the way, I don’t know if I knew this. So you helped develop the Dropbox referral program?

Sean Ellis: I was there at the time. Basically, even when I first started talking with Drew. Before I came in, I was like, “I think the way we’re going to grow this business is by leveraging the really passionate customer base and that’s what we need to double down on.” And we had tried a similar kind of referral program at Zabni and a friend who actually started Ring, Jamie Simonoff, previously had a company called PhoneTag way before Ring, and he had actually done a lot of the testing on double-sided referral programs and having incentive on both sides, and he found that that worked the best.

And so between what we had tested at Zabni and those conversations with him, I hadn’t actually seen PayPal yet at that point, what they were doing. But that was kind of like… It seems like a referral program where we have incentives on both sides is the best way to go. Interestingly, six months before I was at Dropbox, I was at LogMeIn, and I really thought about having incentivized referrals at LogMeIn, but 80% of our new users were coming in through word of mouth. And I had a hundred million devices connected in on our system, and I was just so afraid of breaking this growth engine by adding an incentive that I didn’t want to risk it.

But at Dropbox it was so early. I would still say no experiment is one person. It happened to be when I was there, I had some insights that I brought in, but ultimately… The guy who built it was actually an intern named Albert Knee and he ended up dropping out, I think, out of MIT to stay with Dropbox for a few years after that. But he was kind of my right-hand guy to collaborating on growth day to day.

Lenny Rachitsky: Wow. I would say Dropbox is the referral program, and the PayPal referral program, as you mentioned, are the two most legendary, studied, copied referral programs out there.

Sean Ellis: Unfortunately, I think that what they don’t realize is that before the referral program, Dropbox had amazing referral rate. Companies that are trying to copy it are like, “Why isn’t anyone talking about a product? Let’s add a referral program with incentives.” To me, I think it’s a great accelerant when it’s already working, but it can’t fix it if people don’t want to talk about your product.

Lenny Rachitsky: That’s an awesome point and something I was just going to ask about and just coming back to this topic of growing engagement, growing referrals as a growth mechanism, what do you look for to tell you that there’s an opportunity there? And I’ll just answer it, partly I’ve seen exactly what you just said, which is you need to already have strong word of mouth growth because referrals kind sits on that and gives you a little more incentive to share. So maybe do you agree with that, not agree to that? Any other advice on helping figure out is there some kind of loop here that we can build?

Sean Ellis: Well, one thing I will say is freemium when we first started with it, as I said, we were one of the first with it, so it took me a while to figure out exactly how freemium worked, but to me, freemium towards having a free and a premium version of your product to really work in any business, it needs to be that your free product is so good that people naturally have word of mouth around that product. And then to be economically viable, you have to have a premium product that’s better enough and differentiated enough that people are going to upgrade to the premium product.

But I think a lot of times people are so worried about the second part that they make the free version not very good and then they’re surprised when word of mouth isn’t very strong there. So I think you have to essentially have two distinct products that are great on their own. So that would be the one piece, but then obviously companies that have any kind of collaborative layer to them are going to be more likely to work well with referral. And then I think on the engagement side, a lot of it comes down to just the nature of the product.

Like Airbnb, you’re not going to use it every day unless you’re like a vagrant or something and then you wouldn’t have money to pay for it. So there’s kind a natural usage cycle to products and you want to be able to maximize against that cycle. That’s where I was saying, coming back to the hooked model, I think is a really good way to help to have a framework to think about how do I improve engagement. One good counter example to that though of the natural frequency of using a product is Facebook when they change their North Star Metric from monthly active users to daily active users. I think, again, just having what gets measured gets managed.

Once Facebook was on a daily active user goal, the team suddenly had a lot more incentive to think about, “How do I bring people back every day and use this product?” Where when it was monthly active users, they kind of only got credit for that person for using once in that month. And even if they used 10 times, they didn’t get 10 times the credit. It was just like a, “Oh, that’s cool too.” But they weren’t sort of measured on that. And so I think it was sort of a random decision for Mark Zuckerberg to move from a monthly active to a daily active because they hit 1 billion monthly active users and they’re like, “Okay, let’s go for 1 billion daily active users.”

But it had a really big impact on making that product way more addictive to the point where obviously they ended up in Congress or get a lot of pushback. I’m not sure they went to Congress for that, but they got a lot of pushback for having a product that’s maybe too addictive. And the same thing carrying into Instagram and some of the other Meta products or basically anything that is highly engaging. So I do think the right incentives can actually help a team to focus on it, but there’s going to be sort of a natural usage cycle to any product as well.

Lenny Rachitsky: I’m glad you mentioned North Star Metrics. I actually have a post I will link to in the show notes where I collected the North Star Metrics of 30 different companies to give you some inspiration. I know this is a deep topic of its own, but just when someone is trying to pick their own North Star Metrics, which I 1000% agree, informs so much about how your company operates. It basically focuses everyone’s incentives to let’s drive this thing. And that changes so much of what you’re building. Any just bullet point piece of advice for helping you pick your North Star Metrics?

Sean Ellis: I start with the value that’s uncovered through the [inaudible 01:21:02] test. So with a company, I’ll say, “Okay, this is what the must have value is according to our most passionate customers, and we want to think about a metric that reflects us delivering that value.” And then I’ll give them kind of a framework of ways to think about a North Star Metric. But I think it’s really important for it to be a time capped group conversation. And if you give a team 30 days, they’ll take 30 days. If you give them six months, they’ll take six months.

But I think generally a team can come up with a pretty good North Star Metric after 30 minutes if they have the right raw ingredients and a checklist of what’s important in a North Star Metric. Something that’s not a ratio, it’s something that can be up onto the right over time. So you can keep managing it and feeling good. It should correlate to revenue growth, but revenue shouldn’t be the North Star Metric, but as you grow value across your customer base, you should be able to grow revenue at the same rate. And so there’s-

Revenue at the same rate. And so there’s some other things, but I think that would be the most important, is that it’s something that could be up and to the right over time and reflects value that you’re delivering to customers.

Lenny Rachitsky: Awesome. And I was going to ask about revenue in your opinion there. And so your advice is don’t make revenue or North star metric?

Sean Ellis: No. Even Amazon, and again, this is just what I know of Amazon’s as being but monthly purchases, but someone else might say Amazon, no Amazon’s is GMV or something. But I think monthly purchases is great because it maps to value that people are getting from Amazon. And so even if I spend say $1000 on a TV set with Amazon versus$3 on a or $10 on an electric toothbrush, Amazon from the consumer’s perspective delivered the same value. I needed something, Amazon helped me find that thing. And so units of value from the customer perspective I think is more important than overall revenue. But clearly with Amazon focusing on driving more monthly purchases, at least on their store side of the business, that has helped them become one of most valuable companies in the world. So I think focusing on value is, revenue should be a product of doing things. Right. It shouldn’t kind of guide your day-to-day actions.

Lenny Rachitsky: To make this even more concrete for people, are there some North star metric examples you could share that you’ve seen that are good? Like say for Eventbrite or Dropbox or any companies you’ve worked with? And I’ll share one real quick as you’re thinking about it. At Airbnb, our North star metric was nights booked. And so it’s similar to Amazon. It’s not like the money Airbnb made from bookings, but it’s like nights booked and it was really, and basically every experiment ran is like, is this increasing night booked or is this decreasing night’s book?

Sean Ellis: And so that’s a really good marketplace one. Uber obviously weekly rides. I’m always surprised with the Airbnb, that there’s not a kind of time piece on it, like the weekly rides that you have with Uber, but maybe it’s because it’s such an infrequent use case on travel that it doesn’t make sense to focus on. Yeah.

Lenny Rachitsky: Yeah. Why is the timeframe important to you? Why do you encourage that?

Sean Ellis: Just daily active users, you saw the difference between monthly active users and daily active users could change behavior a lot at Facebook. It gives you a quantifiable way, if you’re just kind of taking an aggregate number over time, it always looks like it’s going up.

Lenny Rachitsky: So it’s an engagement element of how often are they engaging.

Sean Ellis: Yeah. But,-

Lenny Rachitsky: Any others? Any others real quick?

Sean Ellis: Yeah, I mean, I didn’t really think about North star metrics when I was at Dropbox and Eventbrite, like the term itself, but I was thinking about what is a valuable experience with Dropbox and how do I get people to have that more time? But I don’t even know what they go with today, but maybe files in Dropbox, files access might be better than just files hosted. And then probably for Eventbrite, again, I would say weekly tickets or something like you could say weekly events, but then you have events that don’t sell any tickets where weekly tickets would be more likely to reflect, events are going to be happy if they’re selling tickets and yeah.

Lenny Rachitsky: Okay. Sean, we’ve gone through so much stuff. I’m trying to limit how many more questions we get through just so that we don’t,-

Sean Ellis: We’re going long.

Lenny Rachitsky: We’re going long, which is amazing. I think there’s so much value here that we’re collecting for folks. So let just ask maybe a couple more quick questions. One is actually from Andrew Chen who is currently partnered at a partner at A16z. He wrote about growth for the longest time. I think he helped popularize growth hacking for better or worse with his article and it being the future of VP of what is it? Growth Hacking is the new VP of marketing, right, Is the title. So he actually had a question for you that he shared with me. His question is, growth strategies have changed a lot over the past decade. What is the biggest difference now versus when you first started working on growth?

Sean Ellis: When I first started just being data-driven on customer acquisition was enough to win and being test and data-driven on customer acquisition. All the other companies were like CPM focused and so we could do really well just with lots of testing and some creativity in how it all worked. But that over time as, now I would say most online marketers are very data and test drive. They know they need to do lots of testing. And so to be competitive today, you actually have to be able to be super efficient at all parts of the business.

So again, like how you convert, retain, monetize, and that’s when it gets hard. Getting a marketing team to be data and test-driven is pretty easy. Once you start getting into activation and referral and engagement and retention, now you’re talking about the overlap between marketing, product if it’s B2B, bringing sales in there, customer success, and those teams are not used to working together. And so it’s really hard to drive the collaboration that’s needed to have an effective testing program across the entire growth engine. And that’s pretty much any business that’s been successful with it, implemented it super early in the business, and so very few later stage companies have been able to make much progress in replicating that type of approach.

Lenny Rachitsky: It’s just gotten harder basically. Things are just getting harder.

Sean Ellis: It’s gotten harder, but I think it’s possible. So it’s what I obsess about all the time, is how do you get cross-functional teams working together on growth now? And it’s still a huge advantage when you can pull it off.

Lenny Rachitsky: Okay. Totally unrelated question, going in completely different direction as we close out our chat. So you came up with ICE, the very popular way of prioritizing work, which is crazy. I did not know that until I started prepping for this conversation. What’s your thoughts on RICE, the intercom version of ICE, where R stands for reach, I believe.

Sean Ellis: Yeah.

Lenny Rachitsky: Thoughts?

Sean Ellis: So I think it’s an unnecessary addition, but maybe I’m just being protective of my original idea, that the I in ICE is impact and it’s essentially saying best case scenario, how much impact could we get from this? And reach is a super important part of impact. And so I think it’s already factored in the I in ICE. And so I think if there’s anything that I would be accused of, it would be being over simplifying things and I’m not saying them, but there’s a lot of people who approach things with, there’s got to be a more complex way to approach this and that’s just not me. And so yeah, more testing is better.

No, it doesn’t just work like that. I mean, better tests are better than bad tests, but just if you have to hold yourself accountable to anything, more testing would be better. And so I think one just quick note on ICE is that in order to be able to effectively run a high velocity testing program, you need to be able to source ideas from across the company. And that’s why I came up with ICE, that if you’re having people submit ideas and you can’t tell them why their idea was not chosen, they’re just going to get upset and you’re going to waste a lot of time. But if you have a systematic way of being able to compare ideas, it’s more likely that people will be able to get it and they’ll be able to come up with better ideas.

Lenny Rachitsky: I love the way you think, Sean. I have a post on prioritization where I basically just make the same argument that there’s all these complicated ways to prioritize. In the end, it’s just impact, confidence, and effort and it really works and rarely is more work. On the other hand, I do also have a guest post called DRICE by these two guys called Detailed RICE, which actually I think is a really good point where sometimes it’s worth spending like 30 minutes per idea to just really estimate how long will it take to avoid doing things that are just going to not work and very unlikely. So we’re basically doing this reach piece and spending the time too. Right. And I think there’s a lot of good value there.

Sean Ellis: Yeah. And what I thinks going to be really interesting is that over time, I think AI is going to actually change our ability to model out potential outcomes on experiments and start to, whether it’s a more informed way of doing ICE or replaces ICE, that ultimately probability of outcomes is something that AI will be pretty good at.

Lenny Rachitsky: Well, amazing segue to the final question. The actually final question is I wanted to ask you about any ways you’ve been using AI or ways you think AI will impact the work you’re doing or other folks are doing? And maybe you just answered it, but you tell me.

Sean Ellis: No, I’ll touch on a couple. One is that probably the funnest way that I’m using it today. Obviously I’ve done it for coming up with experiment ideas, but the funnest way I personally use it is I get a lot of people asking me for advice, and I don’t have very much time to answer with thoughtful answers to people. And so almost every question that I get, I go to ChatGPT say, how would Sean Ellis answer this? And it gives me an initial draft to make a couple of tweaks and definitely allows me to answer a lot more. So it helps to have a book that’s indexed in there and lots of writing.

Lenny Rachitsky: That is so funny, and that the question, that’s as simple as the prompt is how would Sean Ellis answer,-

Sean Ellis: Yeah, because then a lot of times it’ll say, Sean Ellis, author of Hacking Growth dah, dah, dah, believes that, and then it’ll obviously pull that part out in the answer.

Lenny Rachitsky: Oh my God. So you’re one step away from a Chrome extension or something that just automatically plugs that into your,-

Sean Ellis: Yeah, exactly. And I can even start to have my personal assistant maybe start to answer some of those questions as me, but I’m a little bit afraid to send something without reviewing it first because,-

Lenny Rachitsky: Absolutely.

Sean Ellis: Sometimes there’s stuff that’s pretty different from how I would answer it, but longer term, I actually think, as I said, I think the cross-functional challenge to growth is a thing that holds a lot of companies back from being able to implement this a bit later. Mostly product teams don’t want to get direction from marketing teams. Marketing teams don’t want to get direction from product teams, and maybe a growth layer can help to do these things, but I find that if AI is essentially saying, you’re underperforming in this area of your business, you should drive some experiments in this area. It’s a lot harder to kind of let ego get in the way when it’s kind of dispassionate recommendations from a system.

And so I actually think, I think the ability to come up with great experiments is going to keep growing with AI and identifying opportunities. And then obviously the analytical AI side of things is going to be really exciting in terms of being, I do find with most companies, once we get a real high velocity of experiments going, the bottleneck ends up happening more on the analysis side. And I think AI will help a lot with that as well.

Lenny Rachitsky: Super cool. These are awesome examples. Okay, Sean, is there anything else you wanted to share or leave listeners with before we get to our very exciting lightning round, which we’ll go through real fast? Because we’ve gone very long and I want to let you go.

Sean Ellis: Yeah. As I’ve gone through and done a lot of workshops and programs with companies, I keep coming back to this advice that I heard from guy Oleg Yakubenkov, which is it often comes down to asking the right question at the right time in how you figure things out. And he’s a former data scientist from Meta and so where he basically boils data science down to learning how to ask the right questions. And so I actually have a course with him called Gopractice.io, where that’s really the big benefit of the course, is to learn how to ask the right questions and yeah, you learn how to query them and amplitude, but more importantly, being able to ask the right question. I think it’s kind of cool to hear that from a data scientist from Meta, the importance of that.

But every time I’m going through exercises in my workshops, it almost always comes down to people who aren’t able to come up with the right or a good answer in a business. It’s because they’re not asking the obvious question. And as soon as they have, like why aren’t users downloading the software? Let’s just ask them that question. That would be one example from my workshop. Who considers the product a must have? That part of getting, to figuring out the must have kind of benefit that then allows you to hone in on product market fit. And so yeah, right questions, right time I think is a really important way to think about growth and even getting to product market fit.

Lenny Rachitsky: I love this advice because I think it gives us a glimpse into how your brain has developed these really seemingly simple ideas that end up being really powerful. And it feels like the advice is just think a lot about the question you need to ask because that’ll get you just something that a lot of people just kind of under think or don’t. There’s things, maybe it’s too simple.

Sean Ellis: Yeah, or they just jump right into the solution side of things where they’re not really trying to understand what’s going on.

Lenny Rachitsky: Yeah. Yeah. Amazing. Okay, well with that, Sean, we’ve reached our very exciting lightning round. Are you ready?

Sean Ellis: I am.

Lenny Rachitsky: All right. Our first question is, what are two or three books you’ve recommended most to other people?

Sean Ellis: Increasingly, I’m recommending a book called Presenting to Win that’s been around forever, but it really helped me with my presenting. And so of course when I’m out traveling, I’m often sharing the stage with other speakers and yeah, I like to recommend that one to them. I’ve already talked about Muriel’s Hooked. I recommend that always, and we’ll just stick with two. That’s good two.

Lenny Rachitsky: Within Presenting to Win, is there one tip that sticks with you of here’s something that helped me be a better presenter?

Sean Ellis: Ultimately, confidence in presenting comes down to having very well organized information that you’re going to present. And when you organize it correctly, you are much more likely to deliver it with confidence. And so he basically says, if I had a presentation to do and I had an hour to present, I’d spend 55 minutes creating the right presentation and then five minutes practicing it. But yeah, there’s a lot more to it, but,-

Lenny Rachitsky: Wow. Amazing. Okay. We’ll link to that book in the show notes. Do you have a favorite recent movie or TV show you’ve really enjoyed?

Sean Ellis: Yeah, so I’ve been binging the Olympics. I love that, just watching people who worked their ass off for years and then maybe have 30 seconds to do the thing that they worked hard for. So Olympics have been awesome. And then the movie, I actually just saw Blackberry, I don’t know if you’ve seen that.

Lenny Rachitsky: Oh, the story of the Blackberry?

Sean Ellis: Yeah. I mean obviously we all kind of know the story, but it was so really, I mean, it’s a classic example of product market fit and then not. Actually, it’s probably even a counter example to the dangers of the how would you feel if we could no longer use this product? Pretty sure most people would’ve said on Blackberry, it’s the keyboard, and until iPhone came along, the keyboard was super important and then suddenly it wasn’t. But yeah, it’s also interesting on egos and other things that everybody’s getting friendly in the beginning and then egos take over and things get a lot harder later on.

Lenny Rachitsky: That was actually a really good movie. There’s also an amazing movie called Tetris. For some reason, I think of these two together,-

Sean Ellis: Okay.

Lenny Rachitsky: About the story of Tetris, and it’s a similar parallels to those two movies.

Sean Ellis: Awesome. I’ll have to see that one.

Lenny Rachitsky: Next question, do you have a favorite product you’ve recently discovered that you really love?

Sean Ellis: I forget the name of it, but I think or it’s called Pack Gear Hanging Suitcase, and I basically like, I’ve done almost 100,000 miles in travel this year, and I have another trip scheduled for next week, and I love it because it basically has all my clothes folded in this little insert that goes into my suitcase, and then I just pull it out and hang it up and just makes travel way easier.

Lenny Rachitsky: It’s called the Pack Gear Suitcase?

Sean Ellis: Pack Gear Hanging Suitcase Organizer.

Lenny Rachitsky: So cool. Going to check that out. Two more questions. Do you have a favorite life motto that you often come back to that you find useful in work or in life? Maybe share with friends and family sometimes.

Sean Ellis: Focus on reputation and learning over earnings has served me super well that, and I’ll give you an example. I had two companies when I was doing a lot of this early interim stuff yeah, 10 plus years ago, and I had two of them where I talked to the founders afterwards and I could tell they weren’t that stoked on my contributions. And I offered a full refund to both of them with a thought that like I have this reputation that’s, like I randomly pulled the number and said, my reputation worth $5 million. Why would I possibly mortgage that reputation for$20,000? And so one of them, I gave the check back to them and he was happy to take it, but he had said, “Oh, you can make it up to me. You don’t have to give me the check, just make it up to me by continuing to help me for an unlimited amount of time going forward.”

I was like, “Oh, take the check.” And then the other one said, “No, no, I’m actually really happy with what you did. We’re fine.” But the two VCs who had made those introductions were the first two to give me term sheets when I went out to raise money for my company. And the pre-money ultimately ended up being valued at more than double what I had put my personal reputation at. So I, yeah, I think the, yeah, unfortunately the company didn’t do that well itself because of the elusive product market fit challenges. But yeah, the learning there of just focus on learning and reputation. Reputation opened the door to more and more learning. And as I got more learning, the reputation grew. And so yeah.

Lenny Rachitsky: There’s a really good corollary there with customer support. If someone just hates your product and wants a refund, just give them a refund and let them move on versus being upset.

Sean Ellis: Yeah, absolutely.

Lenny Rachitsky: I love that. Final question. You mentioned to me before we started recording that you were maybe indirectly responsible for TikTok’s success. Maybe share that story.

Sean Ellis: Yeah, I mean, I don’t want to overstate it, but I yeah, my trip around the world that I did three months ago, I think I wrapped it up. I met with the original founding growth team at TikTok. They’re based in Singapore and they had, I can’t remember what the previous product was called, but they started with the previous product. And then when TikTok came, they were in place to be the initial growth team for TikTok, and they basically said all the early stuff we did to grow TikTok was based on your writing. So that was before the book came out.

So it’s a lot of just blogging that I had done, but it was really, really cool to get that feedback that, yeah, I’ve always said I have some really good wins, a lot of unicorns that I helped, but none of the really, really big guys. And then to hear that, it felt really good to know that I played some kind of role in TikTok. Of course, almost the same week they told me that that was Congress having TikTok ban conversations. So it was good. And at the same time, knowing that maybe if they hadn’t read my stuff, Congress wouldn’t be wasting their time on TikTok bans.

Lenny Rachitsky: Oh man. Bittersweet. I hope they don’t pull you into some hearings. Sean, this was incredible. This was everything I was hoping it’d be. I feel like we collected so much wisdom here for folks to them figure out product market fit, find product market fit, iterate, grow their products. So happy we did this. Two final questions. Where can folks find stuff that you’re up to if they want to learn more and maybe work with you in various ways? And how can listeners be useful to you?

Sean Ellis: Awesome. Yeah, so Seanellis.me is the website where I kind of link to all the things that I’m doing. And so that would be one place where, and there’s contact forms on there if anyone wants to reach out. Obviously LinkedIn people can contact me there. And then I did mention GoPractice. So gopractice.io. Really cool way to learn growth through a simulated environment of being able to try to grow products. So check out GoPractice and maybe go to Seanellis.me. When this comes out, I’ll put a special offer on there for Lenny’s listeners so you can save some money.

Lenny Rachitsky: And there’s also a LLM AI kind of,-

Sean Ellis: I wasn’t directly involved on that one, but there’s yeah, there’s some other really cool stuff that Oleg and the team are doing. Data-driven product management, and the user growth programs are the ones that I helped with.

Lenny Rachitsky: Awesome. And then for folks, if they’re wondering, do you do advising? How do you work with companies in case they’re like, hey, I need Sean.

Sean Ellis: Yeah, I mean, so the sweet spot for me on companies that I go hands-on with are ideally pretty early just after they get to product market fit and now you know how to measure it. So if you’re kind of pre-scale, but you’re seeing that 40%, or even if you’re a bit earlier than that, we can start talking earlier. But to me, that’s my favorite time to get in there, build it right from the beginning. It’s so hard to retroactively do these things. And I’ll go in for three to six months and I’m all in full-time, one of the team trying to really help build traction in the business. I do one of those every maybe year or maybe every year or two because I purposely burn myself out and then have fun doing more lecturing and workshops and stuff.

Lenny Rachitsky: Awesome. Well, you might get a flood of requests after this comes out. Hope you’re ready. Sean, thank you so much for being here.

Sean Ellis: Awesome. Thank you, Lenny. I really appreciate you having me on.

Lenny Rachitsky: Bye everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at LennysPodcasts.com. See you in the next episode.

Glossary

English	中文
A16z	A16z
activation	激活
aha moment	顿悟时刻
Albert Knee	Albert Knee
Amplitude	Amplitude
Andrew Chen	Andrew Chen
Blackberry	《Blackberry》
Bounce	Bounce
ChatGPT	ChatGPT
Chrome	Chrome
CMS	内容管理系统（CMS）
CPM	CPM
demand generation	需求生成
demand harvesting	需求收割
deviation moment	偏差时刻（deviation moment）
DoorDash	DoorDash
Drew	Drew
Dropbox	Dropbox
engagement loop	参与循环
Eventbrite	Eventbrite
First Round Capital	First Round Capital
freemium	免费增值
GM	通用汽车（GM）
GMV	商品交易总额（GMV）
Gopractice.io	Gopractice.io
GoToMyPC	GoToMyPC
growth hacking	增长黑客
Hacking Growth	《增长黑客》
high-leverage opportunities	高杠杆机会
Hooked	《上瘾》（Hooked）
ICE prioritization framework	ICE 优先级排序框架
impact	影响力（impact）
Intercom	Intercom
Jag	Jag
Jamie Simonoff	Jamie Simonoff
Kettering	凯特林
Kissmetrics	Kissmetrics
leading indicator	领先指标
Lenny Rachitsky	Lenny Rachitsky
LLM AI	大语言模型（LLM）AI
LogMeIn	LogMeIn
Lookout	Lookout
must have	刚需
MVP	最小可行性产品（MVP）
nice to have	锦上添花
Nir Eyal	Nir Eyal
north star metric	北极星指标
NPS	净推荐值（NPS）
Nubank	Nubank
Oleg Yakubenkov	Oleg Yakubenkov
onboarding	新用户引导
Pack Gear Hanging Suitcase Organizer	Pack Gear Hanging Suitcase Organizer
PhoneTag	PhoneTag
PMFsurvey.com	PMFsurvey.com
pre-money	投前估值
Presenting to Win	《Presenting to Win》
product market fit	产品市场契合度
Qualaroo	Qualaroo
Rahul	Rahul
reach	覆盖范围（reach）
retention	留存率
retention cohorts	留存同期群
Sean Ellis	Sean Ellis
Shraaz Doshi	Shraaz Doshi
SlideShare	SlideShare
Superhuman	Superhuman
survey.io	survey.io
SurveyMonkey	SurveyMonkey
switching costs	转换成本
term sheets	投资意向书
Tetris	《Tetris》
user get user	用户带来用户
value delivery engine	价值交付引擎
VistaPrint	VistaPrint
webs.com	webs.com
Weebly	Weebly
Wix	Wix
word of mouth	口碑
Xobni	Xobni
Yelp	Yelp
Zynga	Zynga

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Reformatted by reformat_english.py