The original growth hacker reveals his secrets | Sean Ellis (author of “Hacking Growth”) | Lenny's Podcast: Product | Career | Growth

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

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.

Say someone is listening and they're like, okay, man, I'm getting like 10 percent.

I don't know what to do.

What do you find often works?

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 you're 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.

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

It's usually much more a 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.

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

In my experience. 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've dived deep into two topics.

One, how to know if you've got and two, how to figure out how to grow once you 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 future episodes and it helps the podcast tremendously.

With that, I bring you Sean Ellis.

Sean, thank you so much for being here.

Welcome to the podcast.

Thanks, Lenny. I'm super excited to be on with you.

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?

Sounds perfect. Yeah, let's do it.

Okay, amazing. Let's talk about, first of all, the Sean Ellis test slash something people call sometimes the product market 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 with 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?

It's a simple question that helps you figure out, does anyone consider your product that must have or ideally who and how many people consider it?

But ultimately, it's about trying to figure out, is your product that 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, if I 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.

And 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.

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And the idea is that if 40 % or more of people say they'd be very disappointed if they can no longer use the product, you essentially have product market fit.

I would say it's a leading indicator of product market fit.

The lighting indicator is do they actually keep using it?

So probably retention cohorts are more accurate.

But the problem is your time at Airbnb, how long 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 actually even need a good analytic system in place to be able to see if product market fit exists.

And so the 40 % was not something I originally had in there.

Also, 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 it 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.

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 is 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?

Can you just speak more about that?

When to use this and when it's most useful?

Yeah. And 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 at any stage.

It's helpful to understand who your must -have users are.

But essentially, once you have an MVP, 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.

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

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 back up 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 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 upfront, 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 really 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 continue 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.

Shawn, 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 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.

Yeah. And I was coming at it from a marketing perspective initially.

Over time, I positioned 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 an 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.

And just hearing that you can move the 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.

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

Okay. I want to put a pin in that and come back to that because that's a really important topic.

I'm going to come back to, say someone runs the 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?

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 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 of 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 to get really good context?

So I actually came up with this question when I was working with an early YC company called Zobney and just inbox spelled backwards.

And when I ran the question, basically the people who said they'd be very disappointed without the product were focused on Zobney 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, 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 question mark, 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 Zobney and then a description of what Zobney

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.

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.

Start drilling in, start peeling back that onion and just deeply understand them and make sure that your product roadmap is doubling down on the things that are important to your must -have customers.

Your 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 in your engagement loop is about just reinforcing how to get people to experience that benefit more often.

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? 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 way we're 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...

Yeah. And before I ever heard the term product market fit, I remember the conversations back at Log me In and the mid 2000s of 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 the 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.

How often do you 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?

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 Yall.

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 that 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.

And 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 kind of use this approach to try to dial in their growth engine.

And I ran the survey thinking, 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.

And 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 I 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 that they could no longer use the product.

I've never seen that.

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 dig into it, again, it comes back to that nearly all 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 in the kind of the CMS kind of site 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.

I mean, but for kind of fast forward and on 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 and all of the other things I think about in Go to Market for an early stage product still were relevant, but I think they were a little stronger on the percentage should 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 switching costs I think can factor in there.

So it's a function of both switching costs and utility of the product.

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 how the timing on the best time to ask this question of your users?

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 activation moment.

They've used it twice at two plus times and they've ideally used it say within the last week or two weeks so that 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.

Got it. So basically it's people that have activated whatever that means to you and have been using it for a couple of weeks.

Not people landing on your homepage, not people just signing up, not people months later.

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.

Yeah, in an experimental group.

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.

One came in from Shreyas Doshi, a popular guest of the podcast.

One of the ones that I listened to recently.

Amazing. Yeah. 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 here's when it's not going to work for you.

I think one -off products would probably, how would you feel if you could no longer watch the movie you just watched?

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.

I'm focusing on feedback of people who love it.

Also then through a separate lens, looking at people maybe who would be my detractors.

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 would be amazing.

But it sounds like not many.

What I'm hearing is it's generally widely applicable.

Yeah, I think it is, at least from my perspective.

It's been really useful for me anyway.

Awesome, okay. And then the follow -up question from Shreyas is, and I kind of asked this but I'm curious if there's anything more here.

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?

Are there any other caveats of cool, I got 40 %?

Is there anything else you should know?

Okay, but maybe check this one thing.

Yeah, 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.

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.

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 a 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.

Like 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 it's 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 and retaining and monetizing people, you're going to really struggle on the customer acquisition side.

Yeah. Cool. And we'll talk about customer acquisition slash growth.

Another question I wanted to ask a couple listeners asked is the 40%.

So I had a JAG from NewBank on the podcast.

I think you may have worked with them and they use 50 % of their threshold because apparently, Brazilians are very nice.

And they - Yeah, optimistic.

I didn't even notice that.

Yeah. So I guess the question is, do you find instances where you should increase that percentage and slash in B2B is anything indifferent?

Do you change the percentage in B2B?

Any advice there just like when you adjust the threshold?

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 when I'm using it, I'm trying to just...

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 guarantee like, 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 a question, I used to just use a normal satisfaction question.

When I was working at Zabni, I would...

I'm just like 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 Zabni, 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.

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 Zabni.

But then I went to Dropbox right after Zabni.

And I'm 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.

So that's the origin story right there.

Yeah. Wow. That senior managers are just very harsh.

And they don't need anything.

And you have to flip it.

That is so interesting.

Just like 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, ah, I don't need this app.

Who cares? That's the core of this is just that is hard.

I mean, especially when I first moved to Silicon Valley.

So first, 15 years of my career were not in Silicon Valley.

And so that was in Eastern Europe, and then New York, and then Boston.

You moved 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.

And so even interestingly at Dropbox, through the six months I was there, I would 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 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 kind of 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.

Awesome. So there's 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?

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 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.

What's a good sample size you look for just like, okay, this is actually good data.

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 just randomly made up a number and then I had people telling me, yeah, 30 is the minimum that you want on stuff.

Okay. 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 the failure is such a likely outcome that trying to reverse engineer that failure and 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.

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 just like, it's hard to know the size of opportunity, even though you know some people really, really like it?

Yeah. I talked about, I go to a multiple choice after I initially use open -ended questions to sort of 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 35 % way.

And so then having to like, do you want that like 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 like a really big market and that one'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.

Do you have any heuristic of which you often recommend or is it very dependent on the situation?

I prefer kind of 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.

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 in line in the product, in email, something else?

I've used a lot of different tools.

I actually had a survey business that I sold to Private Equity years ago and that was an on -product.

It's called Qualaroo that's like kind of an inflow survey tool.

I think just like 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 kind of a really crappy customer experience at least at that time.

That's been almost a year now or actually a little over a year.

So I'm really sensitive to like, is it a good survey experience for the consumer itself?

But yeah, I don't think I'm stuck to any one platform there.

Such an important topic, just like, 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 like 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 cohorts, then start looking at that, forget about the survey?

Yeah, what I would say is, but retention cohorts don't give you any of the qualitative insights into the why.

So that's why I would 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 like New Bank, it'd be a 50 % or, you know, I spent a few years, two of the companies I launched, we launched in Hungary.

And I would say it's kind of the opposite end of the spectrum of Brazil, maybe more pessimistic than the average kind of 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?

Awesome. And speaking of New Bank, if anyone wants to see how a company has actually operationalized this in the way they operate, there's an episode that we'll link to in the show notes where every new product at New Bank they build before they launch it, they wait for a 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.

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

Wow. So if you think about it, how would you feel if you could 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.

Oh, wow. But yeah, they were doing it, I think, from pretty early on in the business.

The reason they can do this is they have a lot of users, they have millions and millions of users, so they can ask some small percentage of people's 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.

Yeah. Okay. Last question, I promise, along these lines, say someone is listening and they're like, okay, man, I'm getting like 10%, I'm getting 15%, I don't know what to do to increase my product market fit.

You should just like a strategy of just dig into the people that are very disappointed and see what they have to say, but any other advice slash what do you find often works in helping people move from say 10 % to 40 %?

Yeah. So one of the things that's kind of cool about almost like open sourcing this survey approach is again, watching how NewBank has evolved their usage.

But one of the other companies that I think used it in an interesting way is Superhuman.

I'd 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 like I'm kind of 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?

But so one of the things I've always said is just ignore the somewhat disappointed, 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.

And then, but what Superhuman did, and the reason that, 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 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.

And that 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 kind of 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 kind of break it for the must have users?

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?

No. I mean, that's the same thing.

Like I said, I wasn't initially involved with Newbank, I wasn't involved with them.

And that's the benefit of...

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 KISS Metrics 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.

And it was all just, yeah, free.

I think KISS Metrics is kind of using it as maybe Legion.

And for me, I just wanted a way to kind of 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.

That's awesome. I think that post is one of the most popular in first round, really had an impact on a lot of people.

Yeah. 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, it sounds like another survey has multiple choice.

Here's like - Yeah, two different groups of people to be clear.

Two different groups.

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?

Yeah. And then you'll see, we have like eventually the survey .io got closed down, but essentially the template that I typically use 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.

Okay. Anything else on this topic of the Sean Ellis test, product market fit test before we move on to growth strategy advice?

No, I think that's right.

Yeah. That's right.

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, like it's not just, you have this threshold, let's move, let's grow.

It's like this is just, 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 talking about growth.

So 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.

I imagine many of the stuff we've talked about.

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 that what I thought of it was much 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.

That's a really good clarification.

So how did you actually initially frame it?

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 sort of like textbook marketing, 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 be really focused on how do I acquire customers to an experience that's going to make them want to keep using this product.

And so I, yeah, 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.

Is there another term you think you should have used?

Do you always think that I should have called it this?

Is there anything that you've had in your mind?

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 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.

That's a fun story.

Thanks for sharing that.

Okay. So talking about growth and helping companies figure out how to grow.

So say you go to a company, they're getting 40, say 2%, 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?

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 it.

Initially, it was awareness.

Then maybe the more developed way was like, oh, let's at least focus on profitable acquisition.

But in my experience, the hardest part is 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, sounds kind of theoretical here, but I can go into the details on how.

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 metrics 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 metrics?

So that's where you start to actually build, I call it a value delivery engine, but it's what is our onboarding look like?

What's that aha moment, that activation?

What does the engagement loop look like?

Is there referral? Try to capture it as it is today.

And then from there, thinking about where are the biggest opportunities for improvements.

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 is so focused on the roadmap.

We're two features away from not even needing marketing anymore.

This thing is going to take off.

And then the marketing team is 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 involve 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 like 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 before I get involved with a company.

Robert Leonard 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?

Only then do you start to go big on acquisition, top of funnel growth.

Sean O 'Toole 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.

Robert Leonard This is fascinating, because I think a lot of people probably do the opposite.

Start driving a bunch of growth to our product, then we'll fix onboarding, then we'll figure out how we're making money, and referrals comes along there.

I think this is really important for people to hear.

Again, the reason you invest first and focus a lot on onboarding slash getting people activated is because that is very correlated to retention and I'll be a very disappointed customer.

Sean O 'Toole Yeah. 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 get them to that aha moment, they're at high risk of being lost.

So a lot of people focus on, oh, 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, you can collapse that time to value.

I gave you a couple of incredible examples of when we, 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.

Then I dug into the data and I saw that 95 % of the people signing up for LogMeIn, so LogMeIn free, at the time, free remote access for your computer.

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.

And so 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 sign up to usage rate.

And so in three months we improved the sign up 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.

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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 like three or four things that you think people should definitely try to help improve activation in their onboarding conversion?

One of my favorite quotes is a quote from a guy Kettering, it was early, like 100 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 getting using your product effectively.

And so, yeah, I'll just give you one example.

We had one channel, like kind of after we made a lot of these changes and had already driven a ton of improvement in the log me in onboarding, we found a demand generation channel that was like really cheap and that the economics look great.

But at the just the download step, we had a 90 % drop off rate.

And so, we AB 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, well, these people are registering, why don't we just ask them why they signed up and didn't download the software.

And so, we don't want to do it in two kind of a creepy way.

So, we just said, 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, yeah, 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, I just, I just, 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 when, especially in a demand gen channel where they hadn't sort of seen a radio or a TV advertisement from our competitor, who was a premium only product.

These are people who were kind of discovering the category for the first time they were getting there.

And so, our next test, once we, once we articulated what the problem was, our next test gave us a 300 % improvement in the download rate, which was a, we gave them a choice.

Download a trial of the paid version or download the free version, put the 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 a 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 like, no, the instant messengers are downloadable and they have hundreds of millions of customers.

So, let's study there, 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...

There was... I wouldn't say there was one big gain.

It was a bunch of small gains.

Awesome. Okay. 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 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? I mean, your two big levers on driving a conversion are increased desire, reduced friction.

And so, yeah, you definitely want to increase the right desire.

And then sometimes it can also just be reminding people along the way of what benefits you're going to get.

Of course, 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 kind of 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.

The other element of this is coming up with an activation metric and aligning on here's what we consider someone 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?

I tend to start qualitatively.

So, just when do I think they've had a good enough experience with the product to really know it?

And so, in the case of LiveMeAno, 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 that's 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 something that's value that can be experienced super early.

But I'll actually 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 the strategy that YouTube used to grow, but it was two years before YouTube introduced the approach.

Yeah, it feels like you basically created Zynga.

That's what I'm hearing there.

Okay, 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 like the thing that helps your business grow.

And something I'm 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 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.

And does that resonate?

Does that feel right?

And I wouldn't say it's necessarily one or the other.

I think bounce is a really interesting example where SEO was super important for bounce, or is super important for bounce.

So people who are essentially saying, luggage storage, Paris, luggage store...

Most people when 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.

So yeah, one would be...

I actually think 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.

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 and all the restaurants store dash, I think probably grew through that.

Yeah, 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.

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 of probably B2B, you're probably going to have to do a sales team.

I guess just to help them pick, here's where you have a big opportunity.

Again, it 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, oh, man, this product.

User get user is going to be just like 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 log me in in some senses as solving two businesses that are solving similar problems in different ways, where log me in, 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, go to my PC.

They're creating all this latent demand.

And so it just made sense for us to disrupt them with a premium service and to insert ourselves in the flow of someone like, 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 Dropbox 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 going to some of these traditional category?

And 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.

So 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 in the next business.

But after enough times myself, yeah.

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.

I think that last point is really powerful.

And I'm just writing it down.

You said, so 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?

Was that the second question?

I think that's similar to your start and else 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 search Google for folder sharing.

There's so much there that I think it's easy to skip over.

I think the reason that you don't actually hear people taking the obvious route there a lot of times is because I used to be in the same thing that people tend to be either over -indexed on qualitative or over -indexed on quantitative.

So 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 like pushed me to survey and talk to customers all the time.

And at first, I was like, yeah, 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 them.

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, talk to a customer today when he would ask me.

And then I started finding that my experiments were so much better, the more I talked to customers.

Eventually, I became very much like the blend of qualitative and quantitative research leads to much better tests.

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 you've been sharing so far is very qualitative driven, very survey driven, talking to customers driven.

Yeah. And it's just really hard to run good experiments when you can't deeply contextualize what's going on.

I love this. By the way, I don't know if I knew this.

So you helped develop the Dropbox referral program.

I was there at the time.

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 Zobny.

And my friend who actually started Ring, Jamie Siminoff had previously had a company called PhoneTag, way before Ring.

And he had actually done a lot of the testing on kind of 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 Zobny and those conversations with him, I hadn't actually seen PayPal yet at that point, what they were doing.

But yeah, that was kind of like, yeah, 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 100 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 that yeah, I would still say like 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 in Albert Nee.

And he ended up dropping out of MIT to stay with Dropbox for a few years after that.

But yeah, he was kind of my right hand guy to collaborating on growth day to day.

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

Yeah. And 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.

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 as I've seen exactly what you just said, which is you need to already have strong word of mouth growth because referrals sits on that and gives you a little more incentive to share.

So maybe you agree with that, not agree with that.

Any other advice on helping figure out is there some kind of loop here that we can build?

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.

It took me a while to figure out exactly how freemium worked.

But to me, freemium to 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 vagrant or something maybe, and then you wouldn't have money to pay for it.

So there's a natural usage cycle to products, and you want to be able to maximize against that cycle.

And I think 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 only got credit for that person for using once in that month.

And even if they use 10 times, they didn't get 10 times the credit.

It was just like, Oh, that's cool too.

But they weren't measured on that.

And so I think it was 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 forever or get a lot of pushback.

I'm not sure they got one 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 a natural usage cycle to any product as well.

I'm glad you mentioned Northstar metrics.

I actually have a post -willing tune to show notes where I collected the Northstar 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 Northstar metric, 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.

I need just like a bullet point piece of advice for helping you pick your Northstar metric.

I start with the value that's uncovered through the Chanelis 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 Northstar 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 Northstar metric after 30 minutes if they have the right kind of raw ingredients and a checklist of what's important in a Northstar metric, like something that it's not a ratio, it's something that could be up and to the right over time.

So you can keep managing it and feeling good.

It should correlate to revenue growth, but not necessarily like revenue shouldn't be the Northstar 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 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.

Well, so I was going to ask about revenue and your opinion there, and so your advice is don't make revenue your Northstar metric.

Even Amazon, and again, this is just what I know of Amazons 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, $1 ,000 on a TV set with Amazon versus $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 the most valuable companies in the world.

So I think focusing on value, revenue should be a byproduct of doing things right.

It shouldn't guide your day -to -day actions.

To make this even more concrete for people, there's some Northstar metric examples you could share that you've seen that are good, like say from Ventbright 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 Northstar metric was Knight's book.

And so it's similar to Amazon.

It's not like the money Airbnb made from bookings, but it's like Knight's book.

And basically every experiment ran is like, is this increasing Knight's book?

Or is this decreasing Knight's book?

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. Yeah. Why is the timeframe important to you?

Why do you encourage that?

I just, daily active users, you saw the difference between monthly active users and daily active users could change behavior a lot of Facebook.

It gives you a quantifiable way.

If you're just taking an aggregate number over time, it always looks like it's going up.

So it's an engagement element.

How often are they engaging?

Yeah. Okay. Any others real quick?

Yeah. I mean, I didn't really think about Northstar metrics when I was at Dropbox in Eventbrite, 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.

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 - We're going long.

We're going long, which is amazing.

I think there's so much value here that we're collecting for folks.

So let me just ask maybe a couple more quick questions.

One is actually from Andrew Chen, who is currently partner at A16Z.

He wrote about growth for the longest time.

He helped popularize growth hacking for better or worse with his article on it being the future of VPO.

What is it? Growth hacking is the new VPO marketing, right?

Is that 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?

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 CPM focused.

And we could do really well, just with lots of testing and some creativity and how it all worked.

But now I would say most online marketers are very data and test driven.

They know they needed 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, 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, very few later stage companies have been able to make much progress in replicating that type of approach.

It's just gotten harder.

Basically, things are getting harder.

That'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.

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, thoughts.

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.

Oh, it doesn't just work like that.

Better tests are better than bad tests, but if you have to hold yourself accountable to anything, more testing would be better.

And so I think one 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.

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 fancy, complicated ways to prioritize.

In the end, it's just impact, confidence, and effort, and it really works and rarely is more work necessary.

On the other hand, I do also have a guest post called Dreyce by these two guys called Detailed Dreyce, 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 to work, basically doing this reach piece and spending the time to do it right.

And I think there's a what I think is 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.

Well, amazing segue to the final question.

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 just answered it, but can you tell me?

No, I'll touch on a couple.

One is that probably the funnest way that I'm using it today, like 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 chat GPT and say, how would Sean Ellis answer this?

It gives me an initial draft to make a couple of tweaks and definitely that allows me to answer a lot more.

So it helps to have a book that's indexed in there and lots of writing.

That is so funny. And is that the question?

That's as simple as the question prompt is.

How would Sean Ellis answer this question?

Yeah, because then a lot of times I will say Sean Ellis author of hacking growth believes that and then it'll obviously pull that part out in the answer.

Oh my God. So you're one step away from a Chrome extension or something that just automatically plugs that into your account.

Yeah, exactly. And I can even start to have my personal system 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 sometimes there's stuff that's 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 like product teams don't want to be at direction from marketing teams.

Market 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 let ego get in the way when it's dispassionate recommendations from a system.

And so 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 able to...

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.

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 light and round, which we'll go through real fast because we've gone very long and then want to let you go?

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 a guy Oleg Yakubinkov, 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, 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 in amplitude, but more importantly, being able to ask the right question.

And 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 for a challenging business, it's because they're not asking the obvious question.

And as soon as they ask, 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 they must have?

That's part of figuring out the must have benefit that then allows you to hone in on product market fit.

And yeah, right questions, right time, I think is a really important way to think about growth and even getting to product market fit.

I love this advice because I think it gives us a glimpse into how your brain has developed these really simple, 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 to something that a lot of people just kind of underthink or don't.

Maybe it's too simple.

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

Yeah, amazing. Okay, well, with that, Sean, we've reached our very exciting lightning round.

Are you ready? I am.

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

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'd like to recommend that one to them.

I've already talked about Nereal's Hooked.

I recommend that always.

And we'll just stick with two.

That's good too. Within Presenting to Win, is there one tip that you sticks with you of here's something that really helped me be a better presenter?

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 that - Wow. Yeah, 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?

Yeah. So I've been binging the Olympics.

I love that. Just watching people who work 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.

Oh, the story of the Blackberry.

Yeah. I mean, obviously, we all 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 you could no longer use this product.

Pretty sure most people would have said on Blackberry, it's the keyboard.

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 good and friendly in the beginning.

And then egos take over and things get a lot harder later on.

That was actually a really good movie.

There's also an amazing movie called Tetris for some reason.

I think of these two together about the story of Tetris, and there's a similar parallel to those two movies.

Awesome. I'll have to see that one.

Next question. Do you have a favorite product you've recently discovered that you really love?

I forget the name of it, but I think it's called Pack Gear Hanging Suitcase.

I've done almost 100 ,000 miles in travel this year and I have another trip scheduled for next week.

I love it because it basically has all my clothes folded in this little insert that goes in my suitcase, and then I just pull it out and hang it up and just makes travel way easier.

It's called the Pack Gear Suitcase?

Pack Gear Hanging Suitcase Organizer.

So cool. I'm 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?

Focus on reputation and learning over earnings has served me super well.

I'll give you an example.

I had two companies when I was doing a lot of this early interim stuff 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.

I offered a full refund to both of them with a thought that I have this reputation that's randomly pulled the number and said, my reputation worth $5 million.

Why would I possibly mortgage that reputation for $20 ,000?

One of them, I gave the check back to them and he was happy to take it.

He had said, you can make it up to me.

You don't have to give me the check.

Just make it up to me continue to help me for an unlimited amount of time going forward.

I was like, take the check.

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.

Unfortunately, the company didn't do that well itself because of the elusive product market fit challenges.

The learning there of just focus on learning and reputation.

Reputation opened the door to more and more learning.

As I got more learning, the reputation grew.

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.

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.

I don't want to overstate it, but on 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.

I can't remember what the previous product was called, but they started with the previous product.

When TikTok came, they were in place to be the initial growth team for TikTok.

They basically said all the early stuff we did to grow TikTok was based on your writing.

That was before the book came out.

A lot of just blogging that I had done, but it was really, really cool to get that feedback.

I've always said I have some really good wins.

I've said a lot of unicorns that I helped, but none of the really, really big guys.

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 band conversations.

It was good. At the same time, knowing that maybe if they hadn't read my stuff, Congress wouldn't be wasting their time on TikTok bands.

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 help them figure out product market fit, find product market fit, iterate, grow their product.

I'm 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?

Awesome. Sean Ellis .me is the website where I link to all the things that I'm doing.

That would be one place where there's contact forms on there if anyone wants to reach out.

Obviously, LinkedIn, people can contact me there.

I did mention GoPractice, so GoPractice .io.

A really cool way to learn growth through a simulated environment of being able to try to grow products.

Check out GoPractice.

Go to Sean Ellis .me.

When this comes out, I'll put a special offer on there for Lenny's listeners so you can save some money.

There's also a LLM AI.

I wasn't directly involved on that one, but there's some other really cool stuff that Oleg and the team are doing.

I've been data -driven product management, and the user growth programs are the ones that I helped with.

Awesome. 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?

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.

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.

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.

Awesome. Thank you, Lenny.

I really appreciate you having me on.

Bye, everyone. Thank you so much for listening.

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[Mastering Product-Market Fit and Sustainable Growth with Sean Ellis]-[The original growth hacker reveals his secrets | Sean Ellis (author of “Hacking Growth”)]

📋 Summary

The Sean Ellis Test: A Leading Indicator of Product-Market Fit

The 40% Threshold and Its Purpose

Moving Beyond the Score: Digging into the "Why"

Growth as a Function of Onboarding

Building a Sustainable Growth Engine

The Value Delivery Engine

The Role of Data and Qualitative Insights

North Star Metrics

Conclusion

🎯Key Sentences

📝Key Phrases

📖 Transcript