Lenny's Podcast: Product | Career | Growth
00:02:26 · Sean Ellis, Lenny Rachitsky
[00:02:26] S1: Thanks, Lenny. I'm I'm super excited to be on with you. [00:02:29] S0: There's so much that I wanna talk about. There's so many directions we can go. But to keep it focused, I wanna spend time on two areas. I wanna talk about how to know if you have product market fit [00:02:39] S1: Mhmm. [00:02:39] S0: And what to do once you have product market fit in terms of figuring out how to grow. Yeah. And I know these things are very linked. I know you spend a lot of time on these things. How does this feel? [00:02:49] S1: Sounds perfect. [00:02:50] S0: Yeah. Let's do it. Okay. 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?
00:02:50 · Lenny Rachitsky, Sean Ellis
[00:02:50] S0: Yeah. Let's do it. Okay. 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? [00:03:19] S1: It's a simple question that helps you figure out, does anyone consider your product a must have or ideally who and how many people consider it? But ultimately, it's about trying to figure out, is your product a must have, which could be equated to having product market fit. And so the question is, how would you feel if you could no longer use this product? And I give them the choice, very disappointed, somewhat disappointed, or even not disappointed, or not applicable if 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 that's a really powerful vein to dig into when you when you discover that you actually have some people who would who would give a crap if your product disappeared.
00:04:08 · Lenny Rachitsky
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00:06:30 · Lenny Rachitsky, Sean Ellis
And the idea is that if you... 4040% or more of people say they'd be very disappointed if they can no longer use the product, you essentially have product market fit. [00:06:40] S1: I would say it's a leading indicator of product market fit. The the the lagging indicator is do they actually keep using it? So probably retention cohorts are are more more accurate. But the problem is, like your time at Airbnb, how long do you have to look at a retention cohort before you know that you've actually long term retained someone? And so with this question, can kind of find out day one. You don't actually even need a good analytics system in place to be able to see if product market fit exists. So, yeah, 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 was over time as I, 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. 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 if you felt too low, those products tended to suffer.
00:08:04 · Lenny Rachitsky, Sean Ellis
[00:08:04] S0: 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. [00:08:21] S1: Right. [00:08:21] S0: 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? Like how to... When to use this and when it's most useful?
00:08:21 · Lenny Rachitsky, Sean Ellis
[00:08:21] S0: 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? Like how to... When to use this and when it's most useful? [00:08:33] S1: Mean, for me in particular, when I come into a company, my my 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. So it can really be asked at a company of any stage. It's helpful to understand who your must have users are. But essentially once you have an even an MVP, very first MVP on the product, you can still get some useful feedback about the product if it's resonating with anyone. 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. So I'm like, I have six months to help them grow and they're only at 7% right now. Knows? 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? Fortunately, with the signal and the information we got from the initial survey, we were able to get them at 40% in two weeks. [00:09:50] S0: Wow. What did you do there just as a case study?