Y Combinator Startup Podcast - #93 - Peter Reinhardt

Episode Date: September 6, 2018

Peter Reinhardt is cofounder and CEO of Segment.  Segment helps companies capture data from every customer touchpoint and send it to the tools where it can be used most effectively.They were part of the YC Summer 2011 batch.The YC podcast is hosted by Craig Cannon.***Topics00:26 - What is Segment?1:56 - Segment’s first customers3:31 - Their YC application4:26 - Going through YC5:56 - Realizing their first product didn’t work10:56 - Launching Analytics.js12:11 - Experiencing product market fit17:21 - Debating whether to launch or build out the product19:41 - Evan Farrell asks - You mentioned in the SS lecture that you had to totally pivot to Analytics.js to find PMF, is it possible to purely iterate on something people kinda like to find PMF, or should it be clear from the outset if a new idea is something people want?20:56 - The importance of having a skeptic on your team23:56 - Customer interviews26:56 - Benjamin Liam asks - How did they know they have the right messaging to explain their product?28:26 - Idea generation33:11 - Danny Prol asks - What values and standards do you have in place for your team at Segment? And how do you actively build that culture into your company?37:26 - Ashwin Doke asks - How has GDPR impacted Segment's business model?39:41 - Andrew Pikul asks - Any advice he has on asking for more money than you're comfortable asking for. 42:11 - Juan Carlos Garza asks - How did YC help you to where Segment is right now?43:41 - Juan Carlos Garza asks - In an early stage, what's the thin line between ignoring a customer suggested feature or moving a customer requested feature to the core of your application?45:11 - Biggest learnings since YC45:16 - Important hires at Segment

Hey, how's it going? This is Craig Cannon, and you're listening to Y Combinators podcast. Today's episode is with Peter Reinhart, Peter's co-founder and CEO of Segment. Segment helps companies capture data from every customer touchpoint and send it to the tools where it can be used most effectively. They were part of the YC Summer 2011 batch. You can find Peter on Twitter at Rhine P.K. All right, here we go. The average person probably doesn't know what Segment is. So could you explain? For sure.

So Segment helps companies give their customers a better customer experience. And we do that by helping them organize all of their internal data about all their interactions with the customer. So for example, if you go to the bank, they interact with you at the ATM, at the teller, via a phone call center. They have a web app, a mobile app. They send you emails. They're interacting with you across this huge surface area. And they need to be able to coordinate that interaction. They need to know that if you encountered an error on the ATM,

the teller needs to be able to say, like, I'm so sorry you encountered an error. I'd love to be able to help you. And so what we do is we help bridge that gap of having a single record of all those interactions with each customer. Because previously companies would build all this in-house, or not at all, maybe. Yeah, there's sort of two worlds.

One is they would build it all in-house, exactly, and there'd be a rat's nest of data pipelines from one place to another. And so the engineering team would spend all their time building these data pipelines rather than actually building things for the customer. That's one world. The other world is one. where it really used to be a one-on-one relationship with a bank branch manager, for example,

and they might keep the information in a CRM, right? But if you are similar, it would be an optometrist, right? You go in, they have your past orders, et cetera. But now the world is moving much more to a Warby Parker kind of world where you're not interacting with a person. So a CRM doesn't even make sense. It's like not the right technology for understanding what interactions you're having with a customer.

And instead it's all these different digital channels. So that's where we come in. And your first customers, were they large-scale companies like banks? Or who did you get in the beginning? At the very beginning, we actually launched as an open source library on Hacker News. Yeah. And it took off there, blew up basically overnight. So to be fair, it was kind of like the long road.

Oh, yeah. No, no. Let's not skip the year and a half of dark times. Yeah, yeah. We shouldn't totally go over that. But okay. Yeah. So anyway, you blew up overnight on HN.

Once it went live on HN, it was. blew up overnight. And so our first customers were the folks hanging out on Hacker News. It was basically small companies for the most part, founders who were looking for better ways to instrument their web applications and mobile apps with this sort of analytics tracking. And so the initial growth was that was just completely unpaid customers, right? So they're just using the open source, whatever you put up on GitHub, right? So the strange thing about the open source library, which is sort of this data router. So you put in one piece of data, customer did X and then we turn around and transform it and fan it out to all different places downstream.

And what's funny about the library is if you want to turn on a new tool, if you want to send the data to a new place, you need to recompile the library and redeploy it to your website. So it doesn't actually remove, the open source library doesn't quite actually solve the problem, which is really a marketer or a product manager wants to use a new tool. So what happens is you really want to use the hosted version. Yeah. So almost no one actually uses the open source version as interesting side. Was that by design?

No, no, it's completely accidental. Really? Yeah. There's just no way to make a good open source product around it. Man, that's crazy. So, okay, so what did you apply to YC with? We actually applied as a classroom lecture tool. So the idea was to give students this button to push to say, I'm confused.

And did professor forget this graph over time of how confused the students were? We thought it was a really cool idea. We were college students at the time. And we had a bunch of professors who were excited about it at MIT and elsewhere. I'll never forget, in our YC interview, we were pitching this and PG was getting pretty excited. And then he, he, uh, turns to Professor Miller from, uh, from MIT who we had talked to and had given us the original idea for it and says, hey, would, would you use this? And Professor Miller says, uh, no, probably not. We were like,

what the hell? But we just rolled with the punches and said, yeah, well, you know, we talked to like 20 other professors and, and they were all excited about it. Oh, man. But then you went through YC with this. That's right. You're building it out, right? We went through the whole whole, whole YC with this idea. built it out hundreds of thousands of lines of code super complicated classroom lecture tool product and had like presentation view and people could ask questions it was very complicated we were actually even raised money at demo day with this idea about 600k finally we deployed it in the classroom as the fall semester got started after demo day it was just a total disaster all the students open our laptops and then all went straight to

Facebook so the way we discovered this is we were standing in the back of the classroom just counting laptop screens so it'd be looking over the shoulders of the students one, two, three. And we discovered at the beginning of class, about 60% of students were on Facebook, and by the end, about 80% were on Facebook. Oh, my God. In other words, they were supposed to be using your desktop app the whole time.

That's right. And the professor at the beginning of class had been like, can everyone please get out their laptops? We're going to use this new. All of a sudden, all these students are distracted by Facebook. So we had accidentally sort of put in an attention, attention bomb, if you want. Yeah. And you hadn't brought on any users during what?

So you were in the, wait, I wrote it. You were in the summer. 2011 batch. That's right, summer 2011. And you weren't testing during the batch? We tried testing, but there's not that many classrooms that are in session during the summer. Right? The school year starts in September. So we had beta tested in a few summer computer science classes at both Stanford and Berkeley. Yeah. But there was always technical difficulties and other things that sort of prevented us from getting like a real sense of what was happening. Oftentimes it was pretty yolo. I don't know. We didn't really get tests rolling until the fall. Okay. And so what was the like the come to

Jesus moment where you realize you had to change the product. Standing in the back of a BU classroom is an anthropology class. And I remember arriving at the 60% and the 80%. And we went up and apologized to the professor and walked out. And so at that point, you're just like, okay, we got to kind of shut this down or figure out what to do with the money. That's right. Well, we had just gotten wires for these checks for this money, like literally a week before,

right? So we called back all the investors and we were like, well, it turns out this is a terrible idea. So what do you want us to do with the money? And almost all of them said, well, we invested for the team, so go find something else. Okay. And, okay, next day. Next day, we're like, well, what are we going to do? And we realized, you know, we should have been able to figure out some of this analysis by not just standing in the back of the classroom. Like, we should have been able to see some of this digital. You couldn't see it in the analytics metrics at all. So we decided, hey, let's build an analytics tool. Let's build a better web analytics, mobile

web app analytics tool to compete with MixPanel and Google Analytics. The idea was to give really advanced segmentation because we also wanted to understand how some computer science classrooms at MIT were using it differently than anthropology classes at BU, et cetera. And we couldn't do that analysis in the tools we had. So that was the idea was to build an analytics tool. We spent about a year building the infrastructure necessary to do the analytics and really we're not succeeding in getting any customers during that time frame.

So you had, I mean, did you have a whole onboarding process? Was it like a landing page? What did it look like? Oh, yeah, we had a landing page. I was going on little sales trips. I was meeting with people trying. Oh, yeah, yeah. We were trying.

Okay. But it was not going well. Basically what would happen is people would say, well, I already have this other analytics tool installed. So like, I'm not that interested. You definitely, at the time you were not 10x better than Google. No, no. Yeah.

Were you at parity? we were at parity in certain dimensions and we were exceeded in other dimensions but there just weren't the dimensions that mattered apparently Right, okay So you just kind of like blow up overnight With Hackernews

And that like this is Well so pause We're not even This is just the analytics tool Which we realized in December 2012 Was failed So we're like well over a year Into the analytics tool

We're now have tried two ideas Both have failed Neither is clearly going to work at all Yeah We realize that we're screwing up So we decided to have office hours with YC again. We come back, walk around a little cul-de-sac by YC with PG. He sort of comes to the stop and says,

so just to be clear, you've spent half a million dollars and you have nothing to show for it. It's a good, gulping moment. Yeah, yeah, I guess that's true. And it was a good sort of come to Jesus moment, though. And you got to pause there and then rewind all the way back to the first week of YC. and it was in that first week that we'd been like

what we should have analytics tools on our classroom lecture tool so we googled it analytics and we found Google Analytics Mix panel and Kismetrics and we're looking at them and we're like we don't know

which one of these things we should use right like they're kind of all similar but Google Analytics is a little more marketing-y Kismetrics is a little more revenue-y mixed panels a little more product-y in terms of the sorts of insights they can give you and at the end of the day they all collect the same data

they all collect basically who is the customer and what are they doing? So we decided to write this little tiny abstraction that could send data to all three. It was like 50 lines of code among the hundreds of thousands for this classroom lecture tool. And then we decided we'll just send it at all three. We'll look at all the tools and we'll just pick the one that we need. So it'll give us a lot of optionality basically for free. Yep.

And then we forgot about it for like four months. Four months later we cleaned it up a little bit more. Four months later it cleans up a little bit more. As I mentioned, now we're struggling. At that point we're struggling with this question of, well, I already have mixed panel installed so I don't really want to use your analytics tool. Yeah. So my co-founder Ilya has this idea.

He's like, remember that little library that sort of abstracted away the differences between these tools and let us send data to all three? What if we added ourselves as the fourth service that it could send data to you? And then every time someone has that objection, we hit them back with an open source library that they can use to send to us and them. That seems like a clever growth hack. It like gets us around this problem. So we did that, cleaned it up, open sourced it.

And people started replying like, oh, this library's great. We'd love to use it. A couple weeks later, we'd fall up and be like, hey, well, we saw you're using, you know, the open source library, but all you have to do is copy paste our API key so that you can use our analytics tool. Could you just copy paste the API key? Yeah. No, like, eh. So we started just feeling like there's some traction on, on this little routing library, which is maybe up to like 25 stars on GitHub or something like that, like not much. But some people are issuing poll requests. And it's the first time we've ever felt sort of like pull from the market, if you

all, it was we weren't just pushing a bolder uphill. So it's a little different, but subtle. We had this conversation with Paul Graham. The next day we sit down. This is our second time with this. We're like, okay, we have 100K left in the bank. What's our final shot? And my co-founder, Ian is like, you know what? I think there's a big business behind analytics, JS, which is this routing library.

I was like, that is literally the worst idea I've ever heard. Like, it's 500 lines of code. You've grown a little bit. It's 500 lines of code and it's already open source. I have no idea how you build a business around that. Yeah. And so we fought about it all day. long. It was four of us. I was the most skeptical, I think. I was just literally like brutal,

brutal fighting. I went home and I was trying to figure out how to kill the idea. So wake half the night, finally figured it out, came in the next day. I was like, all right, guys, here's what we're going to do. We're going to build a beautiful landing page, really going to pitch the value of this analytics JS open source library. And it'll have a sign up form at the bottom so that we can get people to sort of express interest. Put it up on Hacker News and we'll see what happens. And I was thinking like, this will just totally kill it. Right. Nothing does well in Hacker News, right. So we'd build a landing page, put it up on Hacker News, and this is when we have this year and a half in the making overnight explosion. Yeah. And that kind of segues into your

whole startup school talk, right? About like basically real product market fit. Yep. And up to that point in your life, had you launched anything where the market, I mean, this is a market indrecent quote because he kind of coined the term. It pulls it out of you, right? That's right. I think it's an app description. I think that's an app description. I had never experienced it before. And it feels very much like losing control, right? Like previously you're like building a thing and you roll it out and you're building

a thing and you're pushing it out. And all of a sudden you like put a thing out there and people start running away with it and using it in ways that you didn't necessarily expect. And you're sort of like, what, whoa, whoa, whoa, it's just in, it's just in beta. Like, stop, stop. Like we need to fix these other things because otherwise it's like this feeling of losing control and almost like the market is dictating to you now. what the rules of the road are and what needs to get built.

So would you... It's a very different feeling. Yeah, would you differentiate that from overwhelming demand for one particular feature versus like, we're just going to take this and use it however we want, but there's a ton of demand there? Would you separate those two things? Not really. I think there's people always want more features.

Yeah. But the thing that flipped was people would previously tell us they wanted a feature, but not use it. Right. Whereas now people were using it, and they would want a second feature. And it's a super important distinction. I think a lot of founders get caught in this sort of like all the death spiral of user feedback, where they keep going and showing someone their product and asking them for feedback. They give them, you know, some feedback about how they could make it better, but they don't use it.

And then they bring it back with those fixes. And they ask if this is better and it's just like a death spiral or it never gets anywhere. But once someone starts using it, they'll have more requests. And that just means they're going to pay you more over time. Right. Yeah. I liked how you put it in the lecture where you're basically like, if you have to ask yourself, it's not product market fit.

Yeah, you really can't miss it. Yeah. And this was now six years ago, five, five, six years ago? Almost six years ago, yeah. Right. And you're still feeling the same way? Yeah. Yeah.

And since then, we've had a few more sort of secondary product market fit moments. Like what? About two years in, we discovered that all of our most valuable customers were sending their data to an S3 bucket, which is basically they were keeping log files of the raw data. which was a little weird because typically what people were using the data for was to send to an analytics tool and an email marketing tool

and a CRM and a help desk places where a business person is deriving value. Log files is a little different. It's a little weird. It's unclear what the use case is. So we went on this sales trip to New York, myself and our first salesperson,

Rath. We met with five customers that were using this S3 bucket. And we just asked them, like, oh, what are you doing with the S3 bucket? The first customer was like, well, you know, we have a data engineering team

is taking the data out of the bucket and converting it into CSV files and then they're uploading it to our data warehouse, which is a redshift cluster. So basically they were using it as the initial input into an ETL pipeline. I'm like, oh, that's interesting, but to the next meeting, second customer is like, well, we have a data engineering team who's taking the data out of S3 converting it to CSVM. We're like, are you kidding? Okay, drop the end. That's interesting.

And then the third, fourth, and fifth ones all said exactly the same thing. And that was the point at which I started becoming a conspiracy theorist. It seemed like some pre-meeting had happened. But they were all doing exactly the same thing. So it was really obvious. We just built a way to load data directly from Segment into a Redshift cluster. And that was a huge thing. You really felt that it was product market fit again.

Yeah, it was very explosive. So we'd grown revenue from zero to two and a half million in the first year. And then we launched this Redshift connector. And the next year went from two and a half to 10. But people weren't asking you for that. That's right. It was one step too far for them to realize that we could do it easily. Their mentality, I think, was that,

oh, Segment is a way that I integrate marketing tools. And so at Data Warehouse isn't a marketing tool. It's a BI tool. Surely Segment can't integrate that. It just didn't click. So I had to go find by asking. Interesting. And your growth, how has that happened?

Has it come through developers? Our Go-to-to-Market model is primarily through through engineers, yeah. We talk a lot about sort of the way that we've built our infrastructure over time. We obviously process a lot of data, so there's a lot of interesting infrastructure problems. I think now we're processing, you know, hundreds of thousands of user actions per second. So there's a lot of data going through there. We read about that.

That's generally interesting to the hacker news and engineering crowd. And yeah, typically an engineer is the one that brings us in. Sometimes I've really technical product manager, but it's someone who's like, yeah, this is going to solve this. weird rats nests data pipeline problem that I've got. And how much of it is open source still? A good portion of it is open source, but most of the value that we deliver is actually by running the hosted version. Right.

Because at the end of the day, it's not just the developer. Like you're saving the developers time, but it's these business people that really need it. Yeah. And frankly, most of the complexity is hidden away in how you actually operate and scale a data pipeline that is processing the data. Yeah. So, you know, our JavaScript library is open source, ROS, SDK, open source or Android SDKs open source.

You can sort of collect data from anywhere, and those collection libraries are open source, but the sort of core infrastructure pipeline is not. Okay. And so right before you guys launched on HN or this like small, tiny micro launch, whatever it might be,

were there other avenues that you were considering pursuing? Like in that debate, in the day before, were you thinking about other stuff? I think the debate was whether to build out the full product and then test for product market fit by trying to sell it to people versus this super, super lightweight MVP landing page that we would put on hack on news to see if there was interest in the

concept. Yeah. And what drove us towards the super, super lightweight test was actually the fact that there was a skeptical divide among the founders. And since the founders couldn't agree, the only way to answer the question was to go to customers ASAP and get an answer. Okay. It's tough.

Like the launching early thing is always a challenge Because I think there have been instances where people are like, yeah, we'll just launch us early, but because they're like 10% off of what that product ought to be or they're not very good at communicating it, they never really get the feedback that they need. Right.

Like how do you, how do you kind of balance that out? Like, uh, this is kind of like fully formed enough or we're communicating it clearly enough that we can launch it. Like how do you determine that? Usually that test is so cheap to run.

that it's worth running, even if you decide that it was inconclusive and you should go a step deeper. But I also think that the way you framed it is actually an excuse that a lot of founders use for not doing the cheap early test when in fact they should. Yeah. I get the same questions like almost every single podcast and I try to be a little bit of a devil's advocate here. But yeah, these are kind of like straw men arguments that gets it Frankly, I think the really big product market moments for every company are pretty unmistakable. Like the Dropbox founders have called it stepping on a landmine. I just, I really don't think you can mistake it.

It really happens in a way that you lose control. It's very obvious. Every metric goes haywire. People are talking about it a lot. It's not, it's not mistakeable for like, oh, you know, this person said that it looked valuable and was really exciting and blah, blah, blah. If they're not using it, like, it's not there. Yeah, okay. Okay, so there's a question from Twitter.

It's clear that a bunch of people have watched your lecture. So this first one from Evan Farrell, he asked, you mentioned in the startup school lecture that you had to pivot to analytics JS to find product market fit. Is it possible to purely iterate on something like that to find product market fit, or should it be clear from the outset if a new idea is something people want? There's two versions of this. I will say the Airbnb version of product market fit is much. much more iterative. They struggled for years and years and made slight iterations and iterations and

iterations and finally it caught on and obviously their runaway success. My feeling is that that's extremely rare and that again, this is a really dangerous place to be because you can stay in this iterative mode for years. Yeah. And it is unlikely that the iterations are going to get you to a good place. So I remember very clearly early on being really inspired. by the Airbnb story and it being a logical reason why we should keep plugging away at a bad idea. And I think we abused the Airbnb story to just keep stringing ourselves along on a bad idea. So I would be very, very careful of following the Airbnb example. I don't know many other companies that hit product market fit that way.

Right. And so how long do you give an idea at this point? I actually don't think that it's quite the right frame to think about it in terms of how long to give an idea. I think what you want is someone, either yourself or someone else on the things. sounding team who's a skeptic. So someone who is going to have enough context with whatever the specific idea is and whatever the sort of regime or market you're in, someone who's skeptical, who will question and push for the fastest reasonable test. So in other words, if you have an optimist and a skeptic and they both agree on what a valid test is, then I think you actually

end up with a good test. But if you have three optimists in a room who all agree on what a good test is, I don't believe that that's a good test. It did over skeptics, but yeah. Have you recruited skeptics or did you just kind of like luck into that? I think we locked into it the first time. Yeah. I do think we have some folks on the team at Segment, some early folks who are, who are skeptics, actually, about future product market fit moments that we've had.

And I think it's been enormously helpful. That's really interesting. How do you test for that, like in an interview scenario? We didn't test for it. We just got lucky again. Yeah, okay. So not even just with, yeah, co-founders, like with early employees as well. That's right.

Yeah. How interesting. Like, how hurtful can it be if someone is like, well, I really think you haven't thought this through. There's like these three things that you should really test ASAP because I don't really believe that you have product market fit here. Right. That's what you want.

You want someone who's going to be like pushing it and you're like, well, yeah, how would we? And then who's willing to collaborate with you on how you should reasonably test whether those things are the case. So the sorts of tests that we have run, for example, with this mindset recently, recently, even in the past year, should we switch from a technical buyer to a marketing buyer? Unclear how to test that.

Well, so this early skeptic who's amazing, her name is Diana, she was like, well, I'm just going to go to a conference with marketers and I'm going to try pitching a bunch of marketers. She just flew to Florida and pitched a bunch of marketers. Came back, she's like, nope. Not a good idea. And I read my own set of tests. So the hacky ways to test these things, I think, are very valuable in it.

And it comes from having skeptics and different perspectives of people willing to go test those things. Okay. And so I imagine these tests from skeptics occur on maybe daily, but probably like at least a monthly basis, right, in terms of you guys working on your product. Yeah, I'd say it's maybe more on like a per idea basis. So like if we're going to launch a new product,

then it's really helpful to have a skeptical perspective of like, here's why this might not actually be a good idea. And do you rely more heavily on data or actual customer interaction? In the early part of the product development process, it's all qualitative. It's all talking with customers. Okay, because this is the thing that bugs me more is like when people are just like putting up landing pages left and right and like thinking that they can like kind of a, I forget what it's I will call it. Like, what do they do at Disney? Oh yeah, like imagine your way towards us like winding down this path to finding it. And in fact, people are super inefficient with time. Yeah, they're just scared. Yeah. And when you actually go and talk to a customer, if you have that conversation in the right way, you'll learn a thousand.

thousand times more from that conversation than you will from putting up a landing page. And I think ultimately, we learned a lot more from talking to our customers after the hacker news landing page than we did from the landing page itself. Yeah, totally. So what are your tactics when you're talking to customers? Yeah, I'd say the main thing is most founders are not familiar with how a sales process is actually run. And you basically want to run a sales process.

So the sort of typical founder motion with running a sales process is the, they come in and they say, okay, I'm going to give you a demo and I'm going to get this like really shiny polished pitch. And then the customer decides at the end of that pitch whether they're interested or not. That's not actually how good sales works at all. The way good sales works is you do qualification up front. So you have some method of understanding the customer's problem better than they understand it themselves. And then you do the computation in your head as to whether your product is a fit for their problem. And there's a lot of methodologies for this. The methodology that we use at Segment is one called Medic, M-M-D-D-D-I-C.

it's literally just a list of sales qualification criteria. And this is what sales reps do. If a sales rep comes back and we're like, we're going to close, you know, this deal, the sales manager says, okay,

well, let's go through metrics. What are the metrics by which this company is going to judge whether or not the product works for them? And if the sales rep can't answer metrics, economic buyer, decision maker, decision process,

the identified pain and doesn't have a champion. If they can't have all six of those things, yeah, there's no deal. And so when you're searching for product market fit, you can just go through, all of those things by asking the customer a ton of questions. And you can grade whether or not you're actually going to build a product that will solve

their problem. Right. Well, this is, it kind of ties into this like skeptic versus like optimist idea, right? You have someone who's like a champion of the product. And in many ways, like maybe this is you like the optimist who just sees the world and they see this future and it looks awesome. It's amazing. But you need that skeptic who sees the world as it really is.

That's right. And a sales qualification criteria is a way of almost putting the skeptic out as a like structured process that enforces some level of skepticism. Yeah. I think it's so dangerous when you're the... Because I fall into this camp for the most part. Like, when you get good at sales, you can kind of sell many people on almost anything. But if that product doesn't exist yet, it's very easy to just kind of mold it in the way when

you're reading someone. You're like, oh, I can totally kind of want it to be like this. So I'm going to kind of go down this path. But then when you actually show them the product... And they're like like you said, they won't even install it. Then you see the world as it really is. Yep. And that's the thing.

And so you guys are just like going out and how are you still having these conversations with people personally? Sometimes. Yeah. For sure. Yeah. Yeah. Because this is one of the things that like people, I think in large part because

they're influenced by your startup school talk. They have so many questions about it. So Benjamin Liam asked like, you know, how do you even, how do you find that you have the right messaging around your explaining your product. Oh, man, this is super hard. I'm not even the right person to ask about this. Actually, Diana, who I mentioned before in RPP marketing, Holly, are the two people who have really refined our messaging over the years, and we're always trying to refine it. So I don't know how you know that you have the right messaging. You know that whatever messaging, you can sort of test whether alternate messaging is going to work, and you can do that qualitatively in

interviews with customers. You can try explaining it one way and skip their eyes light up. You can try explaining it another way and just sort of see what what resonates. I think a really talented early salesperson will also have this sort of pattern in their in their habit of how they pitch that they'll always be testing different ways of explaining the product. That was definitely true for the first salesperson that we hired. He was fabulous. It's just like constantly experimenting with different ways of doing it. So I don't know if there's, you never know if you have the best messaging, but you are constantly searching and testing for different ways of explaining it. Okay.

But again, like if it's about, you know, really finding a good product market fit, do you think that these like minor changes and how you communicate something will make the difference? I don't think minor changes in it will make the difference. Once you have product market fit, then sure, you can optimize the messaging. Okay. So then we should talk about idea generation because that seems more important than these like minor deviations. Yep. Where do you begin? Yeah, I think the best ideas that we've had come,

so there's a big difference between the first idea and the sort of like follow-on ideas. And the reason... So the first idea meaning like the core product and then the individual features. That's right. Okay. And not just individual features, you might have entirely new products that come along. But those are much easier, right? the problem with the first product and product market fit is that you can move the product

and you can move the market because it's fit between these two things. And so it's unclear and they move in some crazy multidimensional space. And so the issue is that to get them to both match up, you can always move either one. And in different conversations, in one conversation, you might shift the product and you might in a different conversation realize you need to shift the market. So that's super tricky. I don't think there's a repeatable way to do that. I think you just have to go very, very deep into a particular market and understand the problems that people have in that market.

So do you have a particular process for idea generation? Or you just get into something and you're like, man, you just go super deep. Yeah. For that first idea, you just have to go super deep. You just have to understand the market and the ecosystem and the customers upside down backwards better than they do themselves. Okay. So if you were booted from Segment today, do you know where you would start? you'd have to start with something that was interesting to you personally, and then you'd go dig in a deep direction.

I think that it becomes more repeatable when you are finding a second product. So at that point, you've mostly locked the market side, right? Because you already have a buyer, you already have a go-to-market motion. You already have like an area of interest, which for us, you know, is these sort of data pipelines and data infrastructure, customer data infrastructure. Then it's much easier because you know exactly who you need to go to and you know roughly the like type of question. that you need to ask. And then you can run a process which is a much deeper x-ray of the customer than you might be comfortable with, at least it was much deeper than I was comfortable with when we first got started. Like as an example, we recently were testing product market fit for a product

that we're going to announce at our user conference in September. And that's now in beta and it's doing really well. But the initial way that we were sort of testing fit there, we would go in and say like, oh, hey, do you have a problem with data cleanliness? And the person would be like, oh, yeah, yeah, totally. That's one of our big problems. Be like, I get cool, cool, cool, cool, like, you know, check data cleanliness. That is, and we might ask like two or three more questions, but like that was sort

of the depth. But the actual level of question needs to be like, okay, well, like, what do you mean data, like, how do you, do you currently invest in data cleanliness at all? And they're like, oh, well, yeah, we actually, you know, we have a team of like six people who do data QA all the time. I'm like, oh, well, those data QA people, like, where are they based? Or they're based in L.A. Oh, interesting.

So they have, like, real salaries. And they're not just like overseas. They're like real like U.S. salaries. Like, yeah, yeah. Okay, so what, like 80K a year, 100K year? Yeah. Yeah, that's about right. It's like, okay, so you're spending, you know, like 750K a year for this data

QA team. And like, tell me more about their process. Like, what are they QAing exactly? Oh, well, they're clicking this button in the app and they're like, well, which button? Yeah. And then are they, like in the, what do they do when they defined a bug? And so we would ask like literally 45 minutes of questions like this.

And now we actually understand their problem. And we understand what they're doing? We understand where their cost centers are. We understand how they're thing. And then we're like, oh, well, what if we did a product that did X? Yeah. Which is exactly what they just explained to us for the previous 45 minutes. And they're like, that would be amazing.

So like, okay. Now we, now this is, that was both sales qualification and discovery. Yeah. Which is a standard sales process. But now it's being used for product development. And that's such a good learning. Because people aren't going to tell you no. Like, I think a lot of people just get scared to, like, ask these questions.

Totally. And the customers will tell you. Yeah. Especially if you, if you take the champion part of Medic, the last one, the C, and you just start by asking, like, what's your vision for X thing that you do? Someone will tell you, you're like, oh, we, our mission is similar. Because that's why you got the meeting in the first place. That person is instantly aligned with you. They'll talk for 45 minutes about their problems before you have to tell them anything.

Yeah. I think that's one of the things that most people don't realize that, like, Many of the best salespeople don't talk that much. The best salespeople at segment ask why to the point of uncomfortableness from everyone else on the team, including myself. Yeah, interesting. Yeah, I wonder what the correlation is between sales and skepticism. It's probably pretty high and people who are questioning things and can see the angle. Yep.

Hmm. All right. Next Twitter question. So Danny Proll, first of all, he says, go Peter. And his question is about culture. So he says, what values and standards do you have in place for your team at Segment? And how do you actively build that culture into your company? Yes, we have four values at Segment that we're quite dedicated to.

The first is karma, which is we want to have a positive impact on the world. And that manifests itself in a bunch of ways. One of those ways is we really care about the customer having, sort of getting value out of our entire process. So you'll notice that all of our marketing materials, for example, are often like high, educational. We have a really high bar for what an piece of educational material looks like. Even in the sales process, we want to be helpful. If we're not the right fit, we'll tell you and sort of like refer you to the right places. Separately, we really care

about doing the right thing by the end user. This is still within karma. And that's from like a data privacy perspective. So we're very interested in helping companies understand all of their own first party data, so all their interactions with their own customers within their four walls. We're super uninterested in helping companies, data broker data between different companies, sketchily, we call it data gossip, it's gross. We don't want anything to do with it. There are plenty of other companies out there that do stuff like that.

It's going to go away and die eventually. So that's karma. We care a lot about that. The second one is Tribe, which is at a segment we're all there to support each other. We're all there to accomplish the same thing. And so what we expect is that, and what we value is that people really support each other both when they may be struggling with something, but also giving them, giving them crit. So really try to reward folks who are willing to go the extra mile to give crit when it may be hard.

It could be giving, uh, create across teams or up several levels or whatever. That's, that's, um, really something that we value. The third is drive, much more self apparent. We like to get shit done. We value people who are getting shit done. Uh, and the fourth is focus, which is not just sort of the ability to sit down and get stuff done, or power through something, but actually thinking carefully about prioritization, we've done a lot of research around how to make the office and environment where you can actually focus. So you can check out our blog. We've written about sort of sound decibel levels that we've measured around the office and how we've mitigated that. That did pretty well. That piece did pretty well, right? Yeah. And it was a surprising result for us

to discover the different parts of the office had very different sound levels that were not correlated with people talking, but we're just correlated with the sort of acoustic shape of the office. And so just moving people around into different places helped a lot, depending on how much noise they were willing to tolerate and sort of needed in their role. So anyway, those are those four values. They are literally the things that we value. And so we push them into all of the places where you would expect what you value to have an impact. So it's who gets highlighted at all hands.

We have a citrus prize, which is someone who's living, all the values, promotions, hiring. We have a strict interview in the hiring process. We have performance reviews. What do you mean a strict interview? Sorry, we have a culture interview where we literally have these four values and specific ways that we're going to test for them. When we run performance reviews, the performance review is literally four values. How are you strong?

This is what we value and therefore it's what we test and measure by. And I think ultimately it's that cycle of giving feedback and measuring by it that is what drives culture to stick. And has this been something that like came naturality? you like building culture or did you have to learn it? I don't think so. I think we learned it. We got to about 25 people before we realized that it was something that we should write down. And we went offsite, four founders went offsite.

And we tried to synthesize the values out of what it was that we really liked. Yeah. That was already happening. And what it was that we didn't like that we had seen already happening. And not just among the team, but amongst ourselves too. like what were we not proud of that we had done and what were we proud of that we had. And that ultimately was what got synthesized into those four values. And so those were just interactions with other people or like literally product building.

No, interactions with other people and interactions with partners and customers and things that we were proud of that we wanted to see more of. Right on. So next question. Ashman Doak asks, how is GDPR impacted segments business model? So GDPR, for those of who don't know, is a new EU regulation, which basically gives end users a lot of rights about the data that's collected about them. And first off, I think it's an awesome regulation, both as a consumer, but also wearing my segment hat. It's interesting in that it impacts the entire globe because if you are storing data about an EU citizen, it doesn't matter what jurisdiction you run your company in. You are still responsible to do that for an EU citizen.

The biggest impact broadly on the sort of overall ecosystem is it really negatively impacts third party data and third party data brokers because they have no real consent path to the user for sharing and buying and selling the data. Because we help companies purely with their first party data, it's not like an existential threat to us in any way. And in fact, it's something that we're really sort of aligned with for another reason as well, which is because we're routing the data out to all the different places where people are using it. We're routing it out to an analytics tool, to an email marketing tool, to a data warehouse, to a CRM, to a help desk, to add conversion pixels. If that user shows up and says, hey, I want you to delete me from your system, well, it's actually like 20 systems for most companies. And we're already plugged into those 20 systems. So it's actually now a feature of segment that we can go to those 20 systems and delete whatever user is requesting it and clean up that record across all those different systems. So for us, GDPR, one is aligned with our values philosophically.

Two is actually an exciting new feature sort of requirement that we can support and a sort of value that we can provide to our customers. So we're huge fans. Nice. That was a unsusper. I mean, it was a perfect answer. But people have been stressed out about it. My friend makes Instapaper and they had a big issue with it.

It's a big problem in publishing where they were relying on third party day. Yeah, especially these like little tiny. any products that are parts of really big companies. And they didn't necessarily know. And, yeah, now they're everywhere. Cool. Cool. All right. So next question, Andrew Pekulh, asks any advice that you have on asking for more money

than you're comfortable asking for? This is part of your startup school lecture where I guess one of your sales reps was forcing you to ask for more, a lot more. Yeah, we had a sales advisor who was, well, I got a backup a little bit. We were initially selling our product for $10. a month. And, you know, $120 a year. And we brought on a sales advisor. And his first advice was, well, you have to ask for $120,000 a year. And I was like, that's a thousand X. That's crazy. So we were going to the first sales meeting, me and him, and this is with the company called Zamoran.

And I've since told not this story, which he found amusing. But now was the CEO of Zamorin. And as we're walking up, our sales advisor says, okay, you have to ask for 120K in this meeting. And I was like, that's the most ridiculous thing I've ever heard. I'm not doing it. And he's like, well, if you don't do it, then I quit as your sales advisor. It's like, all right, I guess I'm asking for 120K. So we go in, we have a demo and everything. And he says, okay, well, what's the price?

And I say 120K. And I turned beat red. And he says, well, how about 12K a year? I said, okay, well, how about 18? And he's like, okay, fine. So from his perspective, he got 85% off. From my perspective, I got 150X. and it was a successful negotiation.

I think it's really hard to offend people with price, at least if you're sitting in the same room or on the phone. It's probably not a good idea to share pricing information via email. If you do that, then it's really easy for them to hang up. But if you're on a phone call or in person, there's a bit of a social contract to continue engaging, particularly in person you can recover. So I would encourage you to not be scared of offending someone with a high price,

but maybe just start in person, which is probably the most uncomfortable place to do it, but gives you the most opportunity to recover. Right. And the thing is, like, if it actually matters for your business, then that's just what it costs. Yeah, you're going to have to, well, and you have no other way of assessing the value. Yeah. Yeah.

And in fact, what will happen is when they say, that's crazy, then you say, why? And then they'll explain to you how they actually value the product. And then you say, okay. And then you value it according to their logic, and you ask for that price. And how long did it take you? Well, are you charging them 120 now? For sure. Yeah, we have customers to get way more.

value than that out of it now. Yeah, exactly. And so how many customers did it take you to reach that six-figure amount? A dozen at most. Yeah. So it was amazing. Yeah. Yeah.

Cool. Juan Carlos Garza asked, how did YC help to get segment where it is right now? YC was super helpful. The most impactful thing early on is just demo day. You're not going to find a bigger concentration of investors who are. excited about investing in startups, creates a compelling event, structures the timeline,

is incredibly helpful for a first round of financing that can easily get strung out and waste a lot of your time. That's the first thing. The second thing really is the founder network. There's not only a lot of reasonably high-profile companies now that you can learn from

are companies that are farther ahead that you can learn from now, but there's companies at all stages. So there's almost always a group of people in your area or in your market that you can learn from and share from. So there are tons of little groups that spring up, you know, like a group of enterprise founders that are all between like 70 and 100 people in San Francisco

and you can have dinner once every two months. Yeah. And that becomes an incredible support group and sort of way of learning about what's going on. Have you stayed in touch with people from your batch? A few, yeah, like Zach Sims from Cook Academy. Oh, right on. Yeah, I've heard of like these informal founder meetups happening quite often. Yeah, it seems to be great.

And it's a trusted network. There's no replacement for that. Yeah, totally. I definitely didn't get that from college. All right. Juan has another question. In the early stage, what's the thin line between ignoring a customer's suggested feature or moving a customer's requested feature to the core of your application or product?

I think what he's trying to ask? is basically like, at what point do you say, like, hey, this customer is requiring or asking for this feature? And we have to kind of hold the line because we don't want to become a custom dev shop. So should we integrate this or tell them to, you know, find someone else? The best defense against that is having a clear product vision for where your product is going to go long term. And if you have a clear product vision for where it's going long term, is a very simple question of, is this thing in that picture long term or not. And if it is in that picture long term,

then you can prioritize it to be sooner or later, depending on whether a customer is going to pay you for it or not. And if it's not, then it's not. And you probably shouldn't build it. Right. Yeah, that's like the infamous customers you don't want scenario where you just have to let them go. Yeah. So I guess the important thing is like imagine the entire timeline of everything you're ever going to build.

Feel free to move things around. We do this all the time. We move things around based on what customers actually want because it's a reasonable signal of what's actually more important. But I wouldn't add major things or remove major things from it just based on one customer. So since you've done YC and it's been several years now, what have been the biggest learning since? Oh my gosh, so many. A huge bucket or a huge area of learning for me is weird as is this is finance. I mean, I came from an aerospace engineering background and then we were doing software engineering for the first couple of years.

years. And so you just are completely unprepared for, for the like business side of, uh, of, uh, of things. So I, I've learned a tremendous amount about, about finance, uh, as we've raised money and, and, and, you know, learned to manage a business with a P&L and, and all those things. Um, not that you should rush into it, but it's a, it's a huge area that can be leveraged, I think. And you would have, if you were to do it again, hired someone earlier on, who knew what they were doing in on the finance side. I actually think we did a reasonably good job of that. So we, we, we hired a part time. CFO around the time that raised our Series A.

So we were about at about a million in revenue and we raised a $15 million series A. We had had a bookkeeper up until that point. But we were like, I feel like we should have someone like, you know, point us as to what we should be doing with the money. Maybe have like a plan or a model or something. So that was definitely the right time to hire a part-time CFO. And Jeff Berklin was super impactful over the years. What have been the other big important hires for you that have made like a huge difference? I remember of the exact team, a whole bunch of people.

But advisors maybe is an interesting category. Sure. Part-time CFO, I think, is in that bucket. We had an HR advisor who is really impactful. We've invested more in HR than most startups of our size. And I think that was the right thing. A lot of startups, like Uber, for example, do not and end up with paying really high prices for this later. I think it's a challenge, right?

Because if you go around and start Googling, like, should I hire a CMO, should I hire a CFO, should I hire X, Y, and Z? I think you can always find someone strongly advocating for any particular role. But the challenge is like, okay, you know, you only have so much money and so much time. And you can only find so many great people. So like where do you, and where and when do you decide to hire those like optimal people for this stage in your company? Right. And so, yeah, just kind of curious if there are any big turning point moments for you. It was a huge turning point around 10 million in revenue when we hired the first two,

sort of execs to the team. One was RVP of engineering and the other was RVP of people. They were the first people who had previously been managers. And RVP of engineering had managed a team of 150 at Dropbox. So we went from literally zero management experience aside from what had been picked up along the way growing from zero to 50 people to having someone

who really knew it or two people who really knew what they were doing. That was hugely impactful. And we should have figured out a way to do that earlier. 50 people in 10 million revenue or whatever it was was, was way too late for that. Yeah. Cool. If you weren't working on a segment right now,

do you have an idea of what you would? Oh, man. I get to occasionally invest in YC companies. Nice. And there's a lot of cool things happening there. I'm always blown away by those like breadth of things that are happening in the batch. This batch, there was a really exciting company

building in-space rocket engine and another that was doing industrial inspections by drone. I just can't imagine a world where we continue to have people in harnesses hanging off of wind turbines. I can't imagine that that continues for a long time. So that seems like an obvious market opportunity. So flying things. Well, I have a background in aerospace engineering.

Yeah, yeah. Yeah, yeah. Right on. Cool, man. So if people want to learn more about Segment, where should they go if they want to learn more about you? Yeah, Segment. Just go to Segment.com. Or you can tweet at me on Twitter.

I'm at Ryan P.K. R-E-I-N-P-K. Okay, cool. Yeah, we'll link it all up. All right, thanks, man. Cool, thank you. All right, thanks for listening. So, as always, you can find the transcript and the video at blog.

combinator.com. And if you have a second, it would be awesome to give us a rating and review wherever you find your podcast. See you next time.