How to Start a Startup: Finding Product-Market Fit

Segment is a b to b company, so that's probably why none of you have ever heard of us. But just to give you a little sense, we're about 150 people and grew from about four people three and a half years ago. So growing quickly and hopefully I can shed some light on finding product market fit for you. And I thought just start by sort of looking back to Alan Kay's lecture last week.

I think he had some pretty incredible advice around how to do really amazing research by sort of looking into the future and imagining what that future might be like. And in particular, had this diagram of sort of exploring the pink plane and sort of testing out different ideas there. And then at some point having a breakthrough and realizing that actually there's a blue plane, right?

And you can sort of go explore an entirely new space. And that that's like a key breakthrough for sort of understanding how you can really invent that future. And in particular, he had this idea of sort of going into the future and imagining yourself there. So he had this Wayne Gretzky idea of skating to where the puck should be or will be.

And sort of going there, grabbing that future, and then pulling it back to the present. And the way that he talks about doing this is, I think amazing for research. He talks about basically going and sort of imagining that future world. But I'd actually wager that not a single successful company has actually been founded by doing that. I think that's, again, awesome for research.

But when it comes to founding companies, it actually has nothing to do with sort of imagining your vision for the future and what that future could be. It's not about sort of how you wish the world was, but it's actually about what customers want.

And I think a lot of companies get marketed post facto of like, hey, we had this great idea and here's how we deductively logics out what customers were gonna want and then we built the thing. But in reality, that's not how it works at all, right? In reality, it's a very inductive process. You're going back and forth with customers and you eventually find something that works.

And so I wanted to talk a little bit about that process today and just how critical it is. And actually how difficult it is too. So one of the most common mistakes that startups make is to build something that no one at once, right? Or solve problems that no one has. And so that Wayne Gretzky method for sort of going into the future and imagining what that future might look like.

Again, it's a good idea for research. It might even be a good idea for venture capitalists to sort of imagine what the future is like and sort of put startups into different buckets of what building that future might look like. But I actually think it's a really bad strategy for founders.

And the reason is that most founders can actually pretty easily build something that looks like it's from the future or is from the future to some extent. It's easy to solve the technology problem there. But it's actually really difficult, that's not really what you need to do, right? You don't need to build something that is your vision of the future.

You actually need to solve a specific problem that customers have today, here, now. And most startups actually fail to do that. Most startups actually build something that looks vaguely futuristic, but is not in fact a real problem that people have today. And it will kill the company every time, right? The market always wins. So we're gonna dig into that a little bit more.

And this sort of problem of finding product market fit stat eighty percent. Eighty percent of all founders fail to find product market fit. So four out of five attempts to find a company just fail at the sort of earliest stage of even finding a problem that you can solve in a unique way.

And the last one out of five, we're gonna sort of struggle through the remainder of actually building that company up from there. But that's just the stats. I'll share our own story of finding product market fit, but the short version is that it actually feels, when you're not finding product market fit, it feels like sort of a bottomless emotional free fall.

Not to get too dark, but when you're failing to find it, it sort of becomes a strange obsession. And it could really make you sick, actually. To get a little too personal for a second, in 2012, in the midst of our search for product market fit, I lost 10 pounds in three weeks. And then went to the hospital twice for panic attacks. I haven't had a panic attack before or since then.

And I think, it's not just me actually, I think Sam, I don't know if I should show this or not, but when he was founding Looped, I think he basically forgot to eat properly and ended up with scurvy, if I remember correctly. Seems like there's somewhere. So basically be warned, finding product market fit is very emotionally a grind.

And the reason it is, is that you really, really desperately want to find that fit, right? You really wanna figure out what is going to work. What is something that customers want? We're all wired to want to succeed and help people like that. And so you're so intent on finding this thing that you sort of convince yourself into seeing mirages of it.

And basically you convince yourself like, this is the thing, we're almost there. It's like, this is something that people really want. And so this is a picture of myself with my three co founders, Elliot, Calvin and Ian, in the summer of twenty twelve, I think. And this is in the midst of sort of our deepest false hopes that we had found something. So we'll dive into that story.

And obviously, I'm here today because it worked out. I wouldn't be speaking if we had just disappeared into darkness. But yeah, today we're about 150 people and growing rapidly. Yeah. How can you make sure you're finding a big market and not just a small niche that will not grow? Yeah, good question.

I think PG's advice on this is good and valid, which is that it's actually harder to find the first problem and solve any problem well than it is to find a route out. So finding a route out from some initial foothold into a broad market is actually not that hard. Sounds hard, but once you find any foothold, you can pretty much find something. And I can cover that a little bit in a bit,.

but yeah. Is that because you have more leverage? Because you have some customers.

Yeah, it turns out that once you solve a problem for a customer, they'll keep bringing you more problems. Right, like the most efficient thing for them to do is just say like, well I have this other problem that's also adjacent to it, can you solve that? And they're like, oh sure, let me solve that. And you just keep solving adjacent problems.

So once you find one thing, it's actually almost trivial to find the next thing, and the next thing, and the next thing. Especially in selling to other businesses where you have someone who can just tell you more stuff. Much harder in consumer. I'm the wrong guy to talk to you about consumer stuff, I don't get it. Cool, so but back then, we were just four dudes in an apartment.

We were failing to find product market fit. We were convincing ourselves that maybe we had it or we were on the cusp of it. And we were writing a lot of code. I saw someone back there was writing code earlier. We were writing a lot of code and we had no customers. That's the wrong order of operations. And so we're tricking ourselves into this.

And in reality, what the good thing that was going on here, the reality was that we were a bunch of cockroaches. And the reason is that it's very important pre product market fit to basically save as much cash as possible, spend as little as possible, and extend your runway as long as possible.

So a lot of founders make a mistake of spending a bunch on sales or marketing or other things as soon as they have an idea. But in reality, until you find product market fit, until you find something that people want, you shouldn't be spending any time on that. You should just be spending time talking with customers and iterating.

And you really wanna constrain your runway or constrain your burns so that you can have a really long runway. So that's what we did. We kept our burn really low. I think we paid ourselves the minimum allowable amount by law, which was like 20 or 30 k a year. We lived in our apartmentoffice and the company paid for part of it as an office. It was the minimal thing.

And we stretched out our runway through as many ideas as we could. And so to sort of make this process a little bit more explicit, step one is that you build, launch, and sort of iterate on several different ideas. And this is where it's really important to be a cockroach, where you're sort of conserving everything you have. Then suddenly something magical happens, we'll talk about that.

And this is product market fit, And it really does feel magical. Hopefully I can illustrate to you and help you feel that. And then three, product market fit sort of suddenly turns you into a unicorn slash cockroach. And rather than just surviving after product market fit, everything gets suddenly easier, right? You can, not easy, but easier.

Customers show up and buy your thing, people wanna join your team. You're still pushing the boulder uphill, if you will, but you're not totally constrained on progress, right? You can actually feel forward momentum for the first time. It's not like one step forward with the product idea, full step back when a customer doesn't care.

You actually can keep iterating on a product that's starting to work. So let's take that middle portion and let's deconstruct it a little bit. So first, we're gonna deconstruct what we call category leaders. So these are really large companies that have been very successful. And then we'll get to sort of the heart of why product market fit is so important at the very beginning.

And then we'll talk about what bad fit feels like, bad product market fit. And then we'll talk about what good product market fit feels like. And we'll try to do that through stories because I want, the goal here is for you to walk away and be able to more easily identify which is which with your own ideas.

So category leaders, the reason we care about category leaders is that they're much, much larger than basically the rest of the companies out there. So I'll give you an example. Amazon and Facebook are sort of consumer companies that you might be familiar with. Salesforce is a company that sells to other businesses. They provide sales software basically.

And the reason that we're interested in them is that they're huge, right? They're often 10 or a thousand times larger than the next competitor in the space. So Salesforce, for example, you have probably heard of Sugar CRM and Zoho are probably companies you've never heard of. They all do roughly the same thing. And so we wanna dig into how can you build a category leader?

What's the layer underneath that? And basically what it comes down to is building a platform. Where it's not just a product that you're selling, but where the data inside of your product is actually useful for other businesses to build their business on top of yours. And that's what Salesforce has done, that's what Amazon has done, that's what Facebook has done.

And so if you look at Salesforce, have something called the App Exchange. And the App Exchange sort of reveals all the data inside of Salesforce and allows other companies to build marketing and sales products on top of that. Similarly, Amazon has the reseller program, right? Where now there's tons of other businesses built top of Amazon. And so the key here is having some sort of platform.

Eventually, when you get to scale, having some sort of platform that other companies are building on, selling, and by nature that pulls people into your ecosystem. But how do you build a platform like that? I know Peter Thiel may not be the most popular right now, but his opinion is that to build a sustainable and compelling platform, you really need to get to 100,000,000 in revenue.

And the reason is just that you need to be at a scale where someone actually can capture a couple percentage points of your customer base and build a real business themselves. Right, so if they can capture a couple percentage points, say 2 to 3,000,000 in revenue, that's a real business. You can build something on top of that. So to sequence our way here, you wanna build a category leader.

To do that, need a platform. To do that, you need 100,000,000 in revenue. So let's keep digging. 100,000,000 in revenue is tough, right? So let's keep digging down. I think you met Jason Lumpkin a couple weeks ago, am I right? Or maybe he's coming soon. He's written some amazing stuff about building software as a service businesses.

Would highly recommend reading all his answers on Quora. And he basically breaks down the path to 100,000,000 in revenue in sort of three different steps. He says, zero to 1,000,000 is impossible, one to 10 million is improbable, and 10 to 100 is inevitable. And he says that 10 to 100 is inevitable because at that point there's just so much momentum.

You have customers out there who are singing your praises. They're buying, their companies are gonna buy more. And it might take you a while but eventually you're gonna get from 10 to 100. One to 10,000,000, I think, is basically always a brutal grind for the founders. And the reason is that you're running a real business. You have real customers, you have some scale.

Your customers have reasonable demands about sort of how the quality of service that they expect from the product. But the problem is that pre 10,000,000 in revenue, have a really tough time attracting a world class management team. So you can't hire a great exec team yet because the large enough market isn't there.

And so what you have is basically all the early crew sort of like holding the ship together and trying to make sure that it's gonna work. So that's a very tough period, I think, for most founders to scale through. And then 0 to 1,000,000 is impossible because this is finding product market fit and 80% or more of people fail at that first step. And so the question is, how can you become not?

How can you actually make it through that impossible section and become one of the ones that succeeds? And one of the things that people talk about as investors or founders is how important it is to learn from failure. And I recently read a pretty good study talking about the stats of sort of actual analysis of failure and success in startups and finding product market fit.

And basically the research shows that you're actually no more likely to succeed the second time around if you fail the first time. So if you fail in finding product market fit the first time, your odds of success are still 20 or 22% the second time around.

But if you succeed in finding product market fit, the chances of your success the second time around go from 22% to 34%, which is still miserable. But is at least 50% better. And so what I think that means is that there's actually not that much information encoded in failing to find product market fit. You don't actually learn that much.

But there's actually quite a bit encoded in feeling the success of actually understanding what did work. And so when we were struggling to find product market fit in 2011 and 2012, I felt this really acutely. We had failed multiple times at this point, but I still didn't feel like I really knew what I was looking for, right? What is this mystical product market fit thing? So frustrating.

And we kept seeing glimmers of hope. We kept convincing ourselves that this, that or the other thing was a visitor chatting with us on our site or whatever was a big deal. Our vaguely interested sales prospect was product market fit. And so without any positive product market fit examples, we didn't really know what it looked like. And so we could sort of convince ourselves of everything.

And the way I think about it now is I really desperately, if you imagine like a machine learning model, I had a bunch of negative training set examples. And I had no positive training set examples. And so of course, my machine learning algorithm was like, I don't know. And so I'm now gonna walk through three stories. I'm gonna show you two examples of failure, actually five ish stories.

Two examples of failure, and then three examples on the positive side of times that we actually did feel product market fit. And again, my goal is for you to actually feel what this feels like so that you can identify it in your own product. So today's segment is a customer data platform. But we actually started as an education tool, and it was actually designed exactly for lectures like this.

So this is us coding in our Mountain View apartment in the summer of twenty eleven. And the idea was that as a professor standing up talking to a class, you have no idea if anyone in the audience actually understands what you're saying. And so we were students at the time at MIT and Rhode Island School of Design.

And we said what we really wanna do is give students a button to push, where they can say, I'm confused, right? Or I get it, either one. And the professor would see this graph over time of how confused the students were. Might be helpful to me right now. And so we built this. We wrote hundreds of thousands of lines of code. It had commenting and notes and all sorts crazy stuff.

And we actually came to Stanford's campus. We convinced, I might have even been in this hall, convinced some professors who would run up to them after class. This is a picture from Berkeley. We pounced on this professor right after class. And we were testing for product market fit, right? Were trying to convince, hey professor, you get any feedback from your class during this class? No.

Okay, well we have a solution for you. So we were hustling to try to get people to actually use this tool. But we were mostly sort of ignoring any test of real product market fit there. And so professors would agree to test it out for a few lectures sort of out of pity maybe for some students from MIT who were trying to help.

And so basically, we thought that this was product market fit, it really wasn't. And I'll show you why. Because if you stand in the back of the classroom and look at what people actually had on their screens, none of them were using the product, right? People were using all these different things. This is that same class at Berkeley the next week, by way. It was horrifying.

Basically, as soon as students opened their laptops, they all went and did other things. And so basically, a laptop into the classroom was the most distracting thing you could conceivably do. So as you can imagine, this was pretty horrifying. One of the more embarrassing things that could have happened to us. We had just raised 600 ks coming out of Y Combinator demo day.

And we had sold this vision of like, this is how the future of classrooms is gonna work, right? It's gonna be digital, it's gonna be online, much as this is a MOOC, etc. And it was a great vision, but again, the market wins every time. It doesn't matter what your vision is, it matters what the market actually wants. And in this case, the students didn't care, right?

The students didn't actually get that much value out of using the tool. And actually, if you go back, we should have had an even earlier warning sign, which is that the professors didn't really wanna use the tool either, right? When you go and talk to the professors, they would sort of out of pity agree to test it for a few lectures.

But that is not the same thing as product market fit, where they're like, holy crap, that solves this problem that I have. And so sort of bullying customers into using your product is not anything close to product market fit, even if they sort of reticently agree to do it.

And I think being dismissive of users and having your clear vision of the future that isn't necessarily solving a problem for your customers is a pretty stunning failure on our part. And it's like a key thing that founders do again and again and again in their sort of search for product market fit.

So then we had to do the awkward thing, which by the way is the right thing of calling back all the investors and saying, this was like four weeks after they'd signed the checks, By the way, it turns out this is a terrible idea, we're gonna do something else. Do you want your money back? And in most of these cases, the investors did not take their money back. They said, we invested for the team.

Go find another idea, we believe in you guys, go find something else. So we said, okay, let's do it. And we were all committed, very committed to working together as a team of four founders. So we shut down the lecture tool, we went and sort of shut down all the classrooms. And then we went back to the whiteboard. And we said, what is something that is sort of interesting here?

And we had always felt like we should have been able to determine that we didn't have product market fit, that the product usage wasn't there from our actual data. The way that we actually figured this out, right, was we went and we stood in the classroom back where Sam is. And looked at what was on all the laptop screens. And that was how we figured out whether we had product market fit or not.

But we should have been able to do that with the data. We should have been able to just look at the analytics and figure out not only are people using it or not, but are anthropology classes using it different than computer science classes. And so we decided to build basically an analytics tool, which it turns out is a bad idea, in case anyone was considering that.

And so the way that we approach this is, how many of you have read the book Lean Startup? Wow, that's actually awesome. You all are way far ahead. So as Lean Startup talks about, you wanna get out of the building and actually talk to customers, right? So we read that right around this moment and we're like, okay, we're gonna go out and talk to customers.

So we did that and we tried to validate our idea. So we'd take people out for coffee and we'd pull people from companies and sort of try to figure out if they were interested in analytics products. And I'd say again and again they were vaguely interested, right? And they had willingness to meet and chat with us and they said they wanted product updates as things came out.

And so we thought this must be it, right? This must be product market fit where people are interested in what we're doing. Again, this is not product market fit. This is idle interest, very, very big difference. And so based on this sort of idle interest, we got very excited and we spent about the next six months just writing codes.

And now this is in a new office, that's my co founder Calvin and Ilya. As you can see, there's lots of code on our screen. Again, wrong order of operations. And I had gone on one sort of sales trip to visit potential customers. And they were all pretty happy with Mixpanel and Google Analytics, but they had these sort of edge case features that they were hoping that we could solve.

And so I sort of tricked myself into believing that these little edge cases that we might be able to solve were actually a really wide gap that we could fill as a product. And so I came back and I would sort of pitch my co founders and we would keep sort of believing that we were almost there. If we just ship one more feature, one more thing, we're gonna get to product market fit. Again, bad idea.

Give you another one, we used lots of little positive interactions like this. You can also read this not as a positive interaction, but every once in a while some straight person would visit our website and they'd open a chat. This is idle interest. Hey, what segment? And this is a complete transcript of that website chat. You can see it's 3AM, so we're up late coding.

And this person is interested. So maybe this is product market fit. Again, this is not what it looks like, this is just idle interest. So it's now December 2012. We've been at this for about a year and a half. And we decided that something was wrong, right? Clearly this was not working. And so we went back to YC, we emailed Paul Graham.

And we said, hey, we think we should catch up and sort of explain what's happened over the last year and a Okay, great. So we go, this is us in front of the old YC building. And we're walking around the little cul de sac by YC on Pioneer Way. We bring him up to speed, okay, we spent half a million dollars, like here's everything we've sort of been through over the last couple of years.

And as we're walking around, he comes to a stop and looks at us. And he says, so just to be clear, you've spent half a million dollars and you have nothing to show for it. Totally accurate. And super fair and sort of shocked us into like, oh shit, yeah, we gotta do something. And so that was the moment where we realized we had hit rock bottom.

But we still had 100 ks left, so we still got one more shot, right? All right, so that was all the product market failure cases. Now you're gonna see some successes. But let's rewind. Let's go all the way back to the first week of YC. And in that first week, we had been like, well, we have this classroom lecture tool and we should have analytics on it, right?

So we looked at the different analytics tools, because metrics, Google Analytics, Mixpanel. And we were looking at what's similar here. And we saw basically they have different graphs and different APIs. But it's actually the same data going into all these tools. It's just they give you different stuff out the other end.

And we were like, well, we don't really wanna make a business decision here about which tool we wanna use. So we'll just solve the engineering problem because we're engineers. And we'll just build some code that sends data to all three and does this automatic translation. So we put one data point in, it gets translated into three API calls that go out to all three services.

Cool, this was like 100 lines of code in the hundreds of thousands that we wrote, right? Set that aside. And about four months later, it gets improved a little bit. Four months later, it gets improved a little bit. At that point, we are trying to sell our own analytics tool, right? Akin to Mixpanel and Google Analytics. And we keep encountering the sales objection when we're trying to sell it.

Which is, I already have Mixpanel installed. I don't really wanna install your tool. It seems like a lot of work. So my co founder Ilya has this great idea. He says, what if we take that little library we wrote a year ago that we've totally forgotten about. And we add ourselves as the fourth service that it can send data to.

And then every time someone hits us with that objection, we hit them back with the open source library. And we say, okay, great, now you can try both in parallel. And we use it as like a growth hack, basically, to get customers to start adopting our tool. Okay, great, we start doing that, start sending it out. People start replying. This is awesome, I love the library. I'm definitely gonna use it.

A few weeks later we follow-up. Hey, we saw you're still not sending any data to segment. io, what's going on? And they're like, well the library is fantastic, I just don't really wanna use your analytics service. Should've taken note right then. But a few months go by, people start starring this on GitHub. Maybe gets up to, it was a big deal for us at the time, like 30 stars.

And I think maybe there was one pull request issued. And then fast forward some more, people keep sort of paying attention. It's the first time we'd ever felt like pull. Like people were just finding this thing and doing something with it. And so fast forward, we have this conversation with PG. And the next day, we sit down and we're like, all right. We need a new idea, right?

And so my co founder Ian is like, you know what? I have an idea. Remember that analytics JS library that has been sort of idling on GitHub? I think that could be a big business. And I was like, you've got to be kidding me. That's the worst idea I've ever heard. First of all, it's open source. And second of all, it's five eighty lines of code.

Who the heck is gonna pay for that, right? How do you build a business around that? It makes no sense. And so we were fighting and fighting and fighting. And I went home and I was racking my brain. So like, okay, how can I kill this idea? It's really bad. And it's gonna sink us.

We only have one more shot. And then, so I came in the next day and I was like, all right guys, here's what we're gonna do. We're gonna build a landing page. It's gonna be an awesome landing page. It's gonna be beautiful. We're gonna put it up on Hacker News. It's gonna pitch the product. And it'll have an email sign up form at the bottom.

And we'll use this to just test whether it's a good idea or not. They agree, like, okay, great. So I'm like, all right, totally done. We get ready to launch on Hacker News. I'm starting to think about other ideas and it goes straight to the top. So it gets about 300 up votes on Hacker News, gets a few thousand stars on GitHub.

We have people reaching out to us on LinkedIn demanding access to the beta. This guy says, what does a brother have to do to get bumped up on your beta list? And there were others like this, right? Holy crap. So full stop, right? Compare this to everything previously, everything changed. This is what product market fit looks like. Where it's not just a single metric slowly starts moving.

It's not just a few random conversations where people express vague interest, right? Literally every single metric went totally haywire. And with our lecture tool and our analytics tool, we've been sort of searching in the dark for what features to build next. We did not have that problem anymore, right?

There were thousands of people who had signed up and they're like, your seven integrations are good but I need these 10 more. And I'm deploying it tomorrow, I'm like blah blah blah blah blah. And we're like, holy crap, okay slow down. And that's actually one of the key things.

One of the key things is that it flips from being something that you're pushing against the customer to all of a sudden the customer's running away with it. And you're like, wait, but hold on, wait, it's not quite ready yet. And so another example with our analytics tool, had this sort of sad unanswered questions and chats. No one really seemed to care about what we had built.

But now all of a sudden we had thousands of stars, people were issuing pull requests. We got like 10 pull requests in the first forty eight hours or something like that. And I guess the other key thing is with our lecture tool and our analytics tool, had had this huge vision, right? We had a vision of like, here's how the classroom should operate or like, here's how companies should do analytics.

And then we went about trying to build a product that fit that vision. But this was the total opposite, right? This is like a little tiny library that we built for ourselves that solved a real problem, had no vision associated with it whatsoever at the beginning. Now it does, because we have something that we really wanna go accomplish.

But at the beginning, it literally solves the tiniest of tiny problems. And so to your question earlier, right? This is that tiny little foothold. And again, it's an open source library with five eighty lines of code. That's a foothold, right? And since then now we've expanded greatly into doing all sorts of things and solving adjacent problems for customers.

But the key is that again, the market doesn't care at all what your vision of the world is. The market wants what it wants and it will win every time. So if you walk away with sort of one thing today, I think it's, let's be incredibly clear that basically product market fit doesn't feel like vague idle interest. It doesn't feel like sort of a glimmer of hope from some early conversation.

It doesn't feel like a trickle of people signing up. It really feels like sort of everything in your business has gone totally haywire. There's this big rush of adrenaline from customers starting to adopt it and sort of ripping it out of your hands. And it really feels like the market is dragging you forward.

I think that Dropbox founders said this best actually, that product market fit feels like stepping on a land mine. And you really, you can't mistake the two. So if you are at all questioning whether you have product market fit or not, you don't. So obviously that didn't stop us from making this mistake. Just to make sure that, wait this is backwards. No, no, it's not. All right.

So I thought class metric for sure had product market fit, right? Big vision. The market said no, market doesn't care what you think. I thought segment IO for sure had great product market fit. Again, market said no, market doesn't care, market wins. And even on our third attempt when we did find product market fit, I thought for sure that this is too tiny to matter, right?

But it actually solved the real problem. And the market demanded it and sort of ripped it out of our hands. And either that goes to show sort of how obtuse I am or how hard it is to actually find product market fit. So how come people wanted to pay for something that was open source and only a couple of times to pay? It's a good question. So it turns out that the open source library by- Sorry.

The question is, why would someone pay anything for an open source library that's five eighty lines of code? It's a good question. It turns out that the open source library by itself doesn't totally solve the problem.

So the actual problem that we found out that we were solving after we launched it was that marketing teams keep coming to engineering departments and saying, I just signed a contract with ExactTarget, an email marketing tool. Or I just signed a contract with Adobe Analytics and here's the docs. And the engineering team says, what the heck? I have a roadmap.

I need to be executing on this other thing. I can't do this analytics implementation. And so what really needed to happen and sort of what analytics JS could solve, the problem that we could solve as a hosted version was allowing engineers to do a single implementation of collecting that data once. And then letting marketers just push buttons in our interface to send the data wherever they need it.

But the open source library doesn't quite solve that problem. Engineers saw that it was the right abstraction, but if a marketer needed a new tool and you're using the open source version, the engineer still has to go compile it. So in some ways we got lucky, right, that the open source version doesn't fully solve the problem. Cool, so I'm gonna steal gratuitously from Allen K's slides again.

And I think finding product market fit feels a lot like finding the sort of blue plane when you're in the pink plane. And I wanna give some other examples of finding product market fit after finding that initial product market fit.

And so the key difference from that initial breakthrough from what Alan Kay was talking about is that rather than removing yourself from the world and trying to imagine what the future is like, you actually need to go out into the world and research what problems people really have.

But then once you find that product, once you find that sort of blue plane, then things actually get enormously easier, right? That blue plane is basically a foothold into a totally new perspective. And I think LNK talked about the value of perspective and context. Should we get this foothold into a new way of thinking about the world, a new way of solving some problem for someone?

And so, not only do you know what good fit feels like, but you now are operating in sort of green pastures. And you're approaching problems in ways that all the incumbents in the pink plane don't think about the world. I wanted to give you two examples of finding product market fit since that initial win for us.

So short intro to what Segment does, we basically help you collect data from mobile apps websites. We pull it up to Segment and we fan it out to all the different tools that you need. And that's all you really need to know. One of the places where we could send data was Amazon S3, right? So this is basically just a place to put all your log files.

And we started to notice that all of our business tier customers were using this one integration. They were all sending their data to S3. But you have to do something with the data once, don't just collect log files, you do something with log files. And so we're like, what the heck is going on here? And so we went and visited five of our largest customers in New York, it was about three years ago.

And we said, okay, you're using the S3 integration, but what the heck are you using it for? And for five out of five customers in a row, they said, well, we have a data engineering team that's taking data from the S3 bucket, converting it into CSV files and managing all the schema translation, and then they're uploading it into a data warehouse, like Redshift.

And the first time I heard that from a customer, said, okay, that's interesting. I took a note, went to the second meeting, customer said exactly the same thing. That's weird, okay. Take a note. Third conversation I was like, right, is getting ridiculous. Did you guys talk ahead of time or what happened here?

And by the fifth time, it's like, okay, well obviously I know what we need to build, right? We just need to build a connection from this straight to Redshift. So then the question is, we went and built that. And just to show you now, sort of now we have a company that actually is here in millions of dollars in revenue. And so we have a real product that real people are using.

And so what does product market fit look like at that point? Right, so we're introducing a second product basically. Well, it looks like this, right? So you can tell when we introduced Redshift. And basically, again, almost every metric in the business goes nuts, right? So it's very, very clear whether or not you have something that is really transformative for your customers or not.

One more story and then we'll open it up for Q and A. So this is maybe about five months ago. We had five ideas for products that we thought might be exciting to our customers. And so I went to visit a customer up a large company up in the Pacific Northwest.

And sat down with a data architect there and I said, okay, here are the five ideas that I wanna run through and see if they're interesting to you. So I went through the first idea and he was like, yeah, you know what? I totally get it. That sounds super valuable. And I went through the second one and he's like, that's really cool. That's cool that you can do that. That makes a lot of sense.

And then third idea, fourth idea, same kind of thing. And so this is how I would summarize that. That's great. I totally understand what the value is. Means, yeah, that would be great. Right, like doesn't care is what that is code for. That's someone being nice. Then on the fifth idea, I said, hey, here's what we can do, you know, blah blah blah.

And he said, wait, sorry, you can do what? And I re explained it and he said, interesting. He turns to his friend and he says, hey, you set up a follow-up meeting with this team, this team, and this team? We also need to tell Joe about this because it could affect this other thing and like that again, that is the feeling of product market fit.

Which is like, you're like, wait, wait, no, no, no, it doesn't exist yet. These are ideas we might like all of a sudden the customer is just gonna rip it out of you. And so now you're on a tight timeline because the customer expects that it already exists. So again, that's what product market fit actually feels like.

And I think if you want to find product market fit and build one of these category leading companies, become one of the one out of five founders that actually does succeed in finding this. I think you just need to be really honest with yourself. That the sort of glimmers of false hope you have are not the same as customers actually ripping something out of your hands.

And so, yeah, you just need to be honest with yourself. That's the message. So, questions? Yes, Sam.

Certainly agree and it's been my experience that that is a product market that is like, but when you're trying to find it, I even like.

have guideposts as to what kind of ideas to try.

When you're just sort of casting around looking for ideas.

I actually think the bigger problem is not necessarily having the ideas. I think everyone has lots of interesting ideas. I think the bigger problem is not killing the bad ideas fast enough. I think actually I have the most respect for the Codecademy founders in this respect. I think they tried like 12 ideas in seven weeks or something like that in the summer of YC.

It was something totally absurd, but they legitimately tried them and they killed them so fast. And then like four days before demo day, they started a new idea, which was Codecademy and then it worked. And on Codecademy, on launch day, on demo day, they had like 300,000 users or something like that. Again, that's the landmine effect of like nothing, nothing, nothing, nothing, nothing, nothing.

And they were so good about killing the ideas, they had no problem throwing out like something that wasn't gonna work. So yeah, I'm not sure. I mean, I don't think there's any magic to finding the right idea. I feel like if you just kill the bad ideas fast enough, you'll probably find something.

Yeah. Talk a little bit about pricing. So this seems like the you know, start with 500 lines of code and solving, you know, a a significant relatively small, like significant but small problem. I don't know if that's the way to describe it. How do you go about pricing something like that when you're doing that customer discovery?

Yeah. So we didn't The question is like how do you go about pricing something like this where it's 500 lines of code? It seems like it solves a small problem for people. We thought it was a small problem for people and we underpriced hugely for a long time. It turns out that that problem that we saw, that the 500 lines of code solves is actually really valuable.

Like We have lots of customers now that pay over $100,000 a year to solve that problem. And there's more to the product now than the 500 lines of code. A lot more, but it's nevertheless is the size of the business problem has almost nothing to do with the amount of code written, right? And I think it did take us a little while to like revalue things in that respect.

But to answer your question most directly, we spent the first year just accumulating customers. So we just had lots of people adopting it. We got to maybe like a thousand or 2,000 companies sending data through segment. And then we tried experimenting with pricing.

And then I'd say the biggest kick in the butt we had to actually get to the right point here is we had a sales advisor who said, we'd go, there were reasonably sized companies using us like Live Nation and RDO and stuff like that. And so we would go to sales meetings at these companies and sales advisor would basically get me pumped up ahead of time.

He'd be like, Peter, you have to ask for a hundred and $20,000 a year. And I'm like, that's crazy. Like, what are you talking about? And he's like, Peter, if you don't ask for a hundred and $20,000 a year, I'm quitting as your sales advisor. It's like, well, alright. Here we go. Right? And so I would ask, I'd turn beet red and then like, they would negotiate it down to like 18 k a year.

But if you keep doing it, eventually someone was like, well, seems reasonable. Yeah. So and you have to keep testing the value like that, right? Because you don't know how much value you're delivering until you start asking for money. So I think if I had to do it over again, I'd start asking for money earlier and I'd be a lot more comfortable with it.

If you're solving a real business problem, people are gonna be happy to pay for it.

I'm not sure I totally answered your question, but yeah. How do you know that you're asking the right people about your product? Like, what if there should should maybe be just a small shift in who you should be asking that you're not realizing? How did you? Yeah, so the question is how do you know whether you're asking the right people?

And how do you know whether you should slightly shift who you're talking to versus shift the product? Yeah, this is actually why it's so hard to find product market fit the first time and why it's so much easier the second time once you have some product market fit.

Because once you do have a defined customer set that you sell to, you can pretty easily figure out by going back to the same people whether or not you're solving an adjacent problem for them. But it's really hard. The thing that makes it super hard at the beginning is it's like you have two things and you can either slide the product or you can slide the market by talking to different people.

I'm not sure that there's a magic rule to know when to slide which, but I think founders get slippery with themselves. They aren't totally honest with themselves about which thing they're doing when. So I it's most important just to recognize that like, okay, if we make this shift, we are shifting the audience versus shifting the product.

Because I think otherwise you can shift the product and the audience simultaneously and think you're doing well, but then realize you're not. So I'm not sure that there's like a slam dunk solution to that other than just being really honest with yourself about which thing you're moving when. Any other questions?

Last chance? Yeah. So you mentioned that, like, you guys, like, were trying to, like, find profit market that before you guys find it, there was a lot of moment that, like, oh, kill this product, kill this product. Like, how do you encourage, like, people in your team to be, like, oh, let's keep focusing on the like, about discovering your next thing.

Like like, what do you like self talk and then like, what do you talk to other people about it?

Yeah. So I think there's a pretty big difference between finding that first product market fit, where you can like kill a product, immediately move to a totally new audience. Codecademy tried a whole bunch of different stuff. With a whole bunch of, speaking of switching audiences, they went from SMB to programmers to restaurants all over the place.

Later on, when you actually are building a company around it and you have product managers and each product manager is searching for a big breakthrough, it's a little bit easier in that you can't shift the audience anymore. The audience is fixed.

And so now, it's slightly more straightforward problem for sort of helping a product manager understand how to go talk to customers and sort of reveal what problems those customers have and then actually solve them.

So it's mostly training in that loop and it comes from talking to either larger customers or your best customers or your worst customers and sort of like trying to push the boundaries around like the core of very happy people have to like what other problems you can solve for them.

Yeah. When you talk to like your customer, what do you ask them? Like what's your script?

You basically just So the question is, you're talking to customers and trying to sort of understand what their problems are, what's the script? I think the biggest mistake is trying to pitch your existing ideas. Like there's a place for that. Right, when you have some product market fit and you wanna test some of these things.

But I think most founders, and certainly we made this mistake early on of pitching rather than trying to sell, rather than actually trying to understand what their problems were. So now when I talk to a customer, I just start by asking what their business problems are. Right, like, hey, person at retail company, do you spend a lot on Facebook?

They're like, oh yeah, yeah, we spend a lot on Facebook. I'm like, oh, well, how do you measure whether that spend is efficient or not? And they're like, well, we don't really know. Okay, well is that a problem? They're like, yeah, yeah, that's a big problem. Like, okay, well, like, tell me why you haven't solved it. And they're like, well, we haven't solved it because like blah blah blah.

And you just start digging in to like these problems. And then you're actually really set up to do a sale then, right? You're like, well, I have just the thing, right? And they're like, holy crap. But but if you don't have a product yet, now you know exactly what can, what problem you can fix. Right? So I think it's more about listening and digging than it is about like pitching an idea.

Do you find these customers? How do you be like, hey, this is my customer. This company, not this company. Yeah, so the question is how do you find these customers?

At the beginning, it's hustle. It's just like emailing people cold. It's getting intros through everyone you know. It's like scratching and clawing your way through your social network and through introductions. After you have customers in an area, then it gets easier because you have people coming to you all the time, mostly if you're inbound.

And so then there's like a steady stream of people to talk to. But the initial piece, that's why people talk about hustle being such an important founder quality is because like, no one's gonna help you. You just gotta go find them. Right? LinkedIn, investors, friends, it's whatever you can claw together. Yeah. Yeah.

So at the beginning, when you like shoot for these customer, like, when you call emailing them, like, how many percent.

of people actually come back to you? The question is when you've cold email customers, what percentage of people come back to you? I don't remember, that was a while ago. Very low, like single digits percentages maybe. You're gonna send a lot of emails that are unanswered. That's the nature of sales.

Honestly, if you're selling in a business to business kind of environment, you're gonna send a lot of emails that go unanswered. Sales is basically the exercise we get in the door slammed in your face nine times out of 10, right? Yeah.

Yeah. What's your vision for a second? Where do you think it will be five years?

Let's go back to the diagram. So what we have today is basically sort of stream processing. So we have both the ability to collect data across a broad section of stuff here, as well as the ability to fan it out to a whole bunch of different places. And so what we wanna do is basically provide a platform that all of these tools can build on top of. That's a super short version.

So you can imagine basically every team in a company needs access to customer data, and we wanna become the platform on which those tools are built. Whether that's email marketing, or push notifications, or analytics, or help desks, or CRMs, or payment systems, fraud detection, etcetera. All of those things operate on a core set of customer data.

And that's the customer data that already flows through Segment by nature of us being that integration connection layer. And so we just wanna expose that data to partners to build on top of it. So when I talked about building a platform at the beginning, that's the next step for us. Peter, are out of time. Thanks very much.