Nirav Tolia on Growing Nextdoor and the Path to Monetization | Blitzscaling 12

This is session 12 of technology enabled Blitzscaling, a Stanford University class taught by Reid Hoffman, John Lilly, Alan Blue and Chris Yeh. This class features a guest lecture by Nirav Tolia, the co founder and CEO of Nextdoor, who is then interviewed by John Lilly. This podcast has been produced by Greylock Partners. For more podcasts, class notes, slides and videos, please visit greylock.com welcome to Thursday's class.

We have Nirav Tolia, who I've known for about a billion years. I'm really tickled to be able to spend time with him.

We were in undergrad together.

Here we were. And one of the things that.

20 years ago.

25 years ago. Yeah, please don't. I'm internalizing it. Yeah. Hold on. So Nirav, one of the things people don't know about Nirav is he went to the high school that is on Friday, Friday Night Lights. And what Nirav and I will both tell you is it's pretty close to accurate. That's pretty much what it was like.

We both grew up in Texas, so we lived the dream.

That's exactly right. Okay, so we're going to talk about networks and growth, and we're going to hear Nirav talk about how his management has changed as we've gone. So why don't we just get started?

Great.

So thanks for coming. So you want to talk about Nextdoor and talk about how it started?

Sure. So I'm running this company called Nextdoor, which is a private social network for neighborhoods. And it's got a little bit of an unorthodox beginning because it's what we refer to in Silicon Valley as a pivot. I was working on another company. I was funded with that other company. I'd been working on it for two years, pretty high profile backers. And about a year in, we realized that our big vision for that company, which was called Fanbase, it was actually a sports company. We realized that that vision was probably not going to be realized, at least not by our implementation of the product. And so we gnashed our teeth for about a year and we tried lots of different things. And when it became very, very, very obvious that we weren't going to get there, our first impulse was actually to return the money to our investors. We were burned out. We were pretty defeated, mentally.

Well, you knew your investors pretty well, so you might want to give that back.

Yeah. I was lucky enough to be funded by Benchmark Capital and a guy there, Bill Gurley, who I've worked with since 1990, nine. So when we started Fanbase, it was 2008, and I'd worked with Bill for almost a decade at that point, and this was our second go round. And so I had a high degree of trust and a high degree of support, and. And it's a real privilege to work with guys like Bill and Benchmark. And I felt like to some extent, we'd let them down and we'd gotten a high valuation, we'd raised a lot of money, we had some press around the company, and it just wasn't going to work. And when you're in the middle of one of these things, you realize that you're putting 110% of your life into trying to get something to work. And when it's not working, at first you say, well, this is just the toil of an entrepreneur, and this is just what it's going to take. And I'm in the salt mines, and it's never as easy as it looks on tv, but then there's a day of reckoning when you realize that some of your core assumptions are wrong. And we started to realize that, and then we tested them and scratched on them and tried to iterate, and we came to a point where we'd really hit a brick wall. And I'll tell you a funny story. I thought to myself, you know, I'm just maybe too old for this. I'm burned out. I need to take a little bit of time off. I'm going to give the money back and then give this another swing. So I called Bill and said, let's meet. I think, you know, things aren't going well. Let's talk about next steps. And we had this breakfast meeting in San Francisco, and he brought me a poem. And the poem is if by Rudyard Kipling, which is essentially a poem about becoming a man or becoming an adult. And the implication of him giving me this poem was, are you really ready to quit here or are you ready to step up and give this another crack? And so he basically challenged my manhood, which is an effective way for a venture capitalist to get an entrepreneur to go back into the salt mines. And so we got back together with the team. We contracted it from 12 people to about seven. And we worked on a variety of different ideas over the summer of 2010, and ultimately Nextdoor emerged from that. Now, that was over five years ago, and it was pretty humble beginning. And it was a beginning that was marked by failure on another idea. And we feel incredibly lucky today that we. Our product is used by over 50% of American neighborhoods. We've raised over 200 million in funding. Our last round a year ago was at a valuation of over a billion dollars. And so it didn't start the orthodox way and it didn't start smoothly, but we're on a good path now.

I think we were talking to Nurev when he was doing fan base. It wasn't so much about how did you tell it wasn't working, except that you could just see Nurev and his co founder Sarah really just grinding at it all day long, just trying to figure out how to make it work.

We did pitch Greylock for fan base and they said no. That was probably a leading indicator as well. They came back and ultimately said yes to next week.

We said no to some things that have worked pretty well too, just for the record. But sometimes you get it right, sometimes you don't. But it's remarkable to me you've had a very, very strong base from which to work from if you work backwards to Stanford even. I remember, I think I probably first met you in 98 or 99 and you guys were running round zero, you. And could you just tell people what ground zero was and what. And more than that, what the environment like that caused you to want to start? That was like, yeah.

And when I come back to Stanford, I realized just how lucky I was to end up on the west coast in the Bay Area and at a place like Stanford because I didn't have ambition to work in technology. Both my parents are doctors and I always thought I would be a doctor like my parents, and I wasn't even technical. And so the fact that I've now spent my entire career working for and running consumer Internet companies is really part of a really lucky, lucky path that started at Stanford. And so I was at Stanford, was not really so happy pursuing the med school route, wondering what to do. And sort of at the end of my tenure here, the Internet started to pick up and it started to explode pretty quickly and exploded with names like Netscape and Yahoo and Amazon, and many that you don't know now because they don't exist, but some that are still around. So I was lucky enough to be an early employee at Yahoo, which was mostly Stanford folks at that point. So it was like going back to a dorm started by a couple of Stanford grad students. And so I was one of the first 70 employees there.

Wow, I didn't know that.

And joined in 96 just as the company went public. And it was an incredible ride there. I didn't know what I was doing. I had no training. I was not a superstar. I was probably the lowest guy on the totem pole. But early on, watching Yahoo and watching the success of the company, I started to think, maybe I can be an entrepreneur and maybe someday I can start something like this. And Silicon Valley fuels that. And even back then it fueled that. Of course, now it's happening every single day. And so as part of trying to figure out how to be an entrepreneur, a colleague of mine and I, we were both interested in starting companies. We said, you know, let's network and try to meet other people in Silicon Valley that want to start companies. And so we started by simply having dinner with four or five of our friends and talking about entrepreneurial ideas and experiences and just bouncing things off one another. And it went so well, because back then, if you were a junior person at one of these companies, you were in the cube farm day and night, you were in the office working like crazy, grinding, and you had no opportunity to talk about other things externally. Back then, all of the things that we have now, all of the incubators and TechCrunch type press and everything else that you guys have to tune into, what's going on, that didn't exist. You were really just inside your own company. That was the visibility.

You had mostly engineering, like liquidation preferences, like notes, none of that stuff. There was nothing.

There was no infrastructure on how to start an Internet company because they had just been started. There was no real history or record. And so we wanted to go out and meet other entrepreneurs that were interested in doing it. And so we had this dinner and it went really well. And we said, okay, let's have another dinner a month from now and maybe we'll each invite one person. And we did that. And that went really well. And before a couple of months, we realized that there might be a need for an organization. It wasn't formal, it wasn't a company, it wasn't really anything. It was just a loose community of entrepreneurs that were coming together. And within a variety of years, because there was such a demand for entrepreneurs talking to each other and learning from each other and networking with each other, within a couple of years, it became the once a month event that most entrepreneurs wanted to be at. And we followed a very strict model of invitation only invites. And you know, speaking about the class, we carried forward a lot of the things that we did in those first dinners. Even when we hit a point of scale where we were having dinners with many hundreds of people, we did the same kinds of things to institute quality Control. And so probably at some point during that time you were invited to one of those dinners. And the dinners, even at scale, even with hundreds of people, the format was for everyone to separate into small tables of five. And so we were trying to replicate that first dinner even though we were at a point of scale at that point.

Yeah, it's amazing to think just a historical footnote. Nirav did that with Naval Ravikant.

Actually, he was not part of one of the founders, he was one of the attendees. But there were four co founders of Round Zero and. No, that's where I met him. That's interesting. He became a co founder of mine for a company that we started together in 1999 called Epinions. That was just where I met him. Interesting.

You want to talk about Epinions briefly, because it's not your first rodeo scaling.

Sure, sure. Yeah. Nextdoor is actually the third company I've started. You heard about Fan Base, the one that didn't work. And there was one before then called Epinions. And I felt after a couple of years at Yahoo and seeing that employee base grow from 70 people to over 3,000 and really experiencing the ride of a lifetime, just being there and trying to soak up everything that was going on, plus running Round Zero, which is what I was essentially doing with a couple of other people running this thing that was scaling that was a little bit like a startup now. It didn't have funding, it didn't have revenue targets, it didn't need that kind of measurement. It had a lot of traction, though. It definitely had a lot of traction. And it felt like a startup and it felt like something that could accomplish great things and change the world and all the things that we want to do with startups. And so at that point I felt, okay, it's time. Even though in 1999, Yahoo was absolutely thriving and flourishing and the stock was at one of its highest points and many people thought I was an idiot to leave at the time I left and with a few people that I had met at Round Zero, started this company called Epinions, which was an idea that was Naval's idea, actually, not my idea. It was a great idea, brilliant idea. And the notion was looking at Amazon. In those early days, one of the differentiators on Amazon was the fact that there were product reviews written by real consumers, which was completely different than the editorially driven product review press that we had been used to. There was this old publication, you guys probably don't even know it, called Consumer Reports. And that's where most people got their data before they bought products. And then Amazon came along and said, you know what, it's good to hear from actual consumers. And so Naval had this brilliant idea of building a kind of marketplace or platform where people who had expertise about products or experience with products could write reviews about those products that they both loved and hated. And shoppers who were looking for information could go to this platform and get the information they needed to make better buying decisions.

And it grew quite large.

It was a darling of the dot com boom initially started relatively fast. In fact, we had an article in the New York Times Magazine called Instant Company about just how fast Epinions was scaling at the beginning. So it was blitz scaling even before that was a term. And it probably scaled a little too fast. And at some point we were over 100 employees. And then the dot com boom and bust happened and we busted along with it and we had to contract the company down to less than 20 people. So it was boom, it was bust. And then little by little and through some very, very hard work over a number of years, it grew to be relatively successful.

Yeah, yeah, I think more than relatively, you guys did very well.

It ultimately merged with a New York based company called Deal Time and then the whole thing was rebranded as shopping.com, which went public in 2004 and then was bought in 2005 by eBay for over 600 million in cash.

Overnight success after 10 years.

You know what was interesting about that is there was a lot of research that was done that I saw. I think it was done at Stanford that talked about the median amount of time from founding to liquidity event. And I think the median time was something on the order of five and a half years. And if we think about founded in 1999, I think epinions was April 99 or so and then public in November 2004. That tracked that median amount of time. Now I look at Nextdoor, which was really found in the summer of 2010, and here we are over five years and we are not going public anytime soon, at least not that I know of. That's one of the things that actually has changed in Silicon Valley. The way that we think about scaling companies. We are more ambitious than ever because the markets are larger, but our path towards getting public and being truly independent has expanded.

Yeah, I think the popular conventional wisdom is that it happens fast because you don't hear about this company and it shows up in the news and suddenly it's got billionaires minted or whatever. But I Think it's. I think the median time of liquidity has gone up. Yeah.

And I'll say a couple things about speed and the phenomenon that we see. Two things. One is there are companies that are almost overnight successes. And as an example, I'll say Instagram. And Instagram was not an overnight success because Kevin, the founder of Instagram, had started something before. But that product, Instagram was almost instantly well regarded and it was almost instantly one of the top apps on the App Store. And so everyone is looking for one of those where you literally have lightning in a bottle. You just happen to have created something that a lot of people really love. So you want to have one of those things. The other thing I'd mention about speed is sometimes fast up can mean fast down. And so the thing you have to be a little careful of is there are lots of things that get popular really, really, really quickly and then they lose that popularity and they come down almost as quickly as they went up. And a sector in general, not naming any companies, but a sector in general that was like, that was games, and specifically games on Facebook. There was a period of time when you were getting cows and other things thrown at you on Facebook or whatever people were doing in the feed. And it was the main thing that you saw on Facebook and now you don't see it at all. All those things are gone. So Facebook as a distribution platform for gaming companies has dried up as quickly as it grew into the dominant platform. Once again confused the coolness of an idea with the true market potential. And so people are starting things everywhere and I think that's great. When they go out and get venture funding, and particularly at the valuations that you're seeing, there's an implication that whatever that funding valuation was, the enterprise value of the company will eventually be worth 10 or 100 times whatever that thing is. And in most cases, a lot of these companies are really good companies that could be run by a person who funds it himself or herself. I think that's been one of the big changes in the Internet with Amazon web Services and a lot of the tools that exist. You can be an entrepreneur that's self funded or angel funded and then start a cash flow business. And I feel like a lot of these venture funded things are essentially cash flow businesses. They're not bad businesses, but they're not great venture funded businesses. And so when you start to realize my actual market is $100 million market, but I raise money at $100 million valuation and I need to get to a billion, you Start to do a lot of unnatural things. And I think that's where we're going to see a lot of trouble for.

Companies usually use venture because you feel like you need to fund growth to get network effects that have become unassailable over time, which I think will lead to the conversation we're about to have in just a second. I think that using venture to fund cash flow businesses is almost never right. You start to think about growth ahead of revenue, you start thinking about upside down unit economics. It's a whole bunch of problems.

Yeah. Specifically what people are saying is using venture money to acquire customers or acquire sales is the wrong way to use venture funding unless you believe there's a true network.

I think what happens in a contraction is that most people say, well, look, I'm a small cap company or I'm worth 100 million or $200 million or $10 million, not worth a billion or trillion, or 10 billion or 50 billion, it won't matter if the top of the market contracts. I think what surprises people is how fast it kind of cascades down and you start to see tightening at the top and then it tightens down pretty quickly.

I guess. Is there a better way to reduce.

The 100 to 20?

Well, you're doing that because it's the only thing you can do to stay in business. I think in general, what founders and CEOs need to think about is there's a right way to run a company and that way doesn't change that much in a boom cycle or a bust cycle. It's making sure that every head is extremely valuable and that you're not growing too fast. From a headcount standpoint, it's making sure that your assumptions are constantly being reproven. It's making sure that you have a long term strategy and you're taking all the small steps necessary to get to that strategy. A lot of the things that you do in a bust are really good things to do during a boom as well. And I think that's what the companies that survived the bust last time. That's what they learned. They learned that the way to operate a company or the way that we were forced to operate companies in the bust are pretty good ways to operate the company, even in a boom.

All right, so let's move to nextdoor. So you wanna talk about, Give us a sense of nextdoor today. Talk about maybe the. Let's start with the product. So talk about what the product is.

So the premise of the product is that while we have social networks to easily connect with friends and family. And that's Facebook. And to people that we're interested, and that's Twitter. And finally to our colleagues, that's LinkedIn. There isn't a social network that will help us easily connect and communicate with the people right outside our front doors. And the people right outside our front doors are typically our neighbors, the people who live in our neighborhoods, in our local communities. It's a little different for college kids because your neighborhood really is Stanford. And so Facebook is a perfect application or whatever, Instagram, Snapchat, whatever's being used on campus. But once you leave Stanford, you move to a new place, you won't know the people around you. When we started the company in 2010, we were really shocked by this statistic, which is almost 30% of Americans couldn't name a single neighbor by name. John and I will tell you 30%. 30% of Americans could not name a single. It's actually 28% of Americans could not name a single neighbor by name. And John and I know from growing up in Texas, that's not the way we grew up. We weren't necessarily best friends with our neighbors, but we certainly knew them and we relied on them. And I think if you think about your parents back home, wherever home is, they are part of a local community that they feel connected to. And when I think about my two young sons, both under three years of age, I don't want them to grow up in a world where most of their friends are folks that they're connecting to virtually on Facebook or through Twitter, that they've never met. I want them to feel like they have roots in the community. And so that was the premise of the company. It was a pretty obvious premise, but completely unproven because people had lost touch with neighborhoods. So the notion that there's even any value to connecting with our neighbors, that was an unproven notion. Now Here we are, five years later, we have over 80,000 neighborhoods that are using Nextdoor. That's roughly 50%. We think there are 165,000 neighborhoods in America. The median size of those neighborhoods is about 700 households.

Why don't we go into the stats? I think it'll be good to give people a sense of. Sense of the.

And while he's bringing this up, almost 50% of American neighborhoods, but over 90% of the neighborhoods in the top 40 cities. So in almost every major city, if you want to connect with your neighbors using technology, you're going to use nextdoor. And what's interesting about nextdoor particularly in the context of this class, is that it was not an overnight success. And it's still not an overnight success. It was a very long, hard road. Continues to be, but it's picking up steam. And so we've got a couple of slides here that we're bringing up and I'll talk you through these. But the basic notion is that when we started the company, because this thing, Fanbase, that we'd been working on because it hadn't worked, and with Fanbase, we had this grand ambition of can we create Bottoms up community to create a competitor for espn. That was the grand vision for Fanbase. We didn't get anywhere. When we started Nextdoor, it was much less about the grand vision. Now Halloween is a very neighborly holiday, so we've got the Halloween faces here. I'm not sure if there's any trick or treating going on here at Stanford, but, you know, once you get out, you'll realize there is trick or treating. But when we started nextdoor, we were probably a lot less ambitious with our long term vision because we'd just come off a failure. What we were very focused on was, can we just make this thing work in a small set of neighborhoods so we can get a proof of concept, what people commonly refer to as product market fit. So now we can go to the next slide. I'm going to go back as far as 2013. Of course, we started the company even before then. And you can see if we look at a couple of our key metrics, let's think of them as almost growth and engagement and then finally external validation. You see a couple of things, you see tremendous growth, but look at the scale of growth recently. And so this is blitz scaling from a metric standpoint. This is John's favorite essay. Do things that don't scale at the beginning.

Can you talk about that?

And if you get those things right. Yeah, if you go to the next slide, I think I have it. Actually, I may not. Yeah, I have it in the next slide. So our first year of Nextdoor, we had 176 neighborhoods. It took us an entire year to get 176 neighborhoods to use the service. And my co founders and I, we talked to most of the people that started every one of these neighborhoods. To start a neighborhood on nextdoor, you have to put in your address, you have to draw the boundaries of the neighborhood, you have to name the neighborhood, and then in some period of time, 14 to 21 days, you have to get nine of your neighbors to join and all verify their Addresses. So starting a neighborhood is not easy. If you think about 30% of Americans don't know a single neighbor, we were looking for those neighbors that knew at least nine others. That's how we could create that.

This is a little counterintuitive, because if you didn't get that done, you'd send a note and say, okay, good try. We're going to turn off your neighborhood for a while.

Started a neighborhood and you didn't have 10 people. It was called a pilot. And the pilot would expire originally in 14 days, and then eventually we extended it 21 days. And of the 80,000 neighborhoods we have, we probably have another 80 to 90,000 pilots that have expired. It was a quality control mechanism, almost a game mechanic, because we said to ourselves, look, when we're building these neighborhoods, we need to build the right foundation. And if someone comes along like John, and says, oh, I'm going to use this for my own personal gain, I'm going to call this John and the Boys in the Hood. I'm going to draw a boundary that's not very sensible, but that makes a lot of sense for me. And I'm just going to invite my friends that agree with everything that I say. Well, that wouldn't make for a very useful neighborhood. The people who typically know nine or more of their neighbors are the folks who care deeply about their local communities. They're the ones who care about Neighborhood Watch. They're the ones who care about neighbors getting to know each other. They're the ones who care about welcome. The new neighbors that move into the neighborhood, they're the ones that act as the social glue. And those were the ones that we were seeking. But it was very counterintuitive because if you think about it, it takes us an entire year to get 176 neighborhoods, and we know that there are 165,000 in the country. Well, you can do the math. How many years would it take us at that run rate to get penetration? It would take us a lifetime. Right. But we were focused on something different than establishing the run rate for growth. We were focused on quality, and that was very, very important for us. We go to the next slide.

So one thing. So you keep using this word neighborhood, which I think we all think we understand in our heads, but neighborhood's not at all an obvious thing when you try to draw the lines. Right. So you always had to figure out what they meant.

Yeah, there's sort of an interesting fork that we were confronted with early on in the genesis of this idea. And that fork was, do we try to model ourselves around Twitter? And the notion of Twitter is, well, you can tune into conversations based on who you like and who you want to follow. And it's not even symmetric in terms of you needing to get approval to follow someone's tweets. And we said, well, if Nextdoor were like that, you would just put in an address, and then you could tune in to all the conversations going on in some geographic radius or proximity to that address, and you could change that. Like, if I'm coming down here, I could say, show me all the conversations that neighbors are having in Palo Alto as an example. Now, the Facebook way, particularly the way that Mark started Facebook, if you remember, you had to have a university email address to join the Facebook for that university. So I had to use my Stanford alumni address to join stanford.facebook.com and that was very different because it made me feel like I was part of a community. Now, it was harder to get critical mass because it was just people who'd gone to Stanford or were at Stanford that were part of that community. But it made me feel some identity. And so we decided early on, every one of these neighborhoods is going to have a discrete boundary. That meant we needed to build a geospatial platform in addition to a social networking platform. We decided that every one of these neighborhoods is going to have a distinct name, and every one of these neighborhoods needs to have identity behind it. Because when you ask someone where they grew up, tell me again the city that you grew up. San Angelo.

San Antonio.

So he grew up in San Antonio, but if he met someone in San Antonio, he would say, this is the neighborhood I grew up in, whatever it was.

Well, in fact, I did. I sat with Josh earlier and we talked about how my wife grew up in Alamo Heights and which is part of San Antonio, how. Yeah, it's exactly right.

And so this is a very important part. In fact, the interesting sociological experiment we did is we said, when you meet someone for the first time, say, at a party, what are the things you talk about? Well, I go up to John and I say, hey, John, nice to meet you. Why are you here? He says, oh, well, this is Peter's party, and Peter's a friend of mine. And I say, oh, Peter's a friend of mine, too. That sort of Facebook. Then I notice that he's wearing a Stanford shirt. And I say, oh, you like Stanford? And he says, yeah, yeah, I went to Stanford. And I said, oh, I went to Stanford too. And that's a little bit of Facebook, a little bit of Twitter, right? Then the next thing, if you're in Silicon Valley, is you say, where do you work? What do you do? That's always a part of your identity. And he says, oh, I'm a venture capitalist. I say, oh, interesting. That's sort of LinkedIn. But almost every single time when you meet someone and think back to when you met people your freshman year, even when you meet people now, you say, where are you from? And the person says, oh, I'm from Texas. Where in Texas? This little city in West Texas, Odessa. Where in Odessa? And it just keeps tunneling all the way down until you typically hit the neighborhood. And that's a big part of knowing who someone is. So we felt that notion of identity was extremely important. It was the hardest decision we made for a couple of different reasons. One is, there is no objective encyclopedia of neighborhood boundaries. People argue about neighborhood boundaries all the time. So we needed to create a Wikipedia type system where we would have the community create a set of boundaries. That was hard. The second thing we said is, we're going to make the conversations private, unless you live in the neighborhood. So everyone who joins next door has to verify where they live. Very counterintuitive. People talk about reducing friction. We increase friction, right? And finally we said, there isn't even going to be a neighborhood unless 10 neighbors can come together in 21 days. Question. So how did you find these people who are so integrated into their community, like the 170 individuals across the country who were integrated? Well, we started in the Bay Area, and we started by asking all of our friends. It was basically like a game of telephone. We would ask all of our friends, do you know anyone who's really involved in the community? And they would say, well, yeah, I know these people and we talk to them. And if they were people, then we'd say, can you start at your community? If they weren't, we'd say, do you know someone? And it would just follow feather out that way at this point. And this is really one of the lessons, I think, around scaling all of those things that we did manually. We initially manually verified people's addresses. We would say, can you send me a picture of your driver's license? Right. Or can we get a homeowners association roster and go through there one by one and get people to be verified? We would go door to door to get people to join. There are all these things we did completely manually where we rolled up our sleeves. And it was very dirty work and it was never going to be scalable. And we knew it, but we were just looking for signal in the noise. And then systematically since then, we have made those unscalable things scalable with technology, and that's what has enabled that growth. Systematically, we've taken verification, made it automated, we've taken neighborhood boundaries. The whole thing's automated. Now. If you want to join Nextdoor, you come in, you put in your address, you're put in through an automated application that then dumps you into the pilot program, which is completely automated. All the reminders. In the early days, my co founder Sarah would call these neighborhoods that were getting started that only had five people, and she'd call up the first and say, come on, you can do it. You can do it. Just invite one more person. They might know another person. Right now we have all of those hooks built into the platform. And so we just looked for signal, we looked for fit, we looked for some fidelity and some notion that what we built was real. We didn't worry about how are we going to scale this. We had to worry about that next. And we've been worrying about it ever since. But initially we focused on quality. And as we think about the organization today, back then it was seven people. Now it's over 100. We try to do the same thing today. We actually separate the company. We have organizations like engineering, product design, etc. But we sit people, typically in project groups, where we have a designer, a product person, five or six engineers, an analyst, and we tell them, let's try to simulate what nextdoor was like in the early days. And it's okay if you do scalable things. To take an example, recently we launched a feature on nextdoor, which is finding a babysitter on demand. One of the things that you do in your neighborhood all the time is you ask for a babysitter. And so wouldn't it be cool if you could find a babysitter as easy as you can find a car on Uber?

You guys all have this problem all the time.

Well, you guys could be the supply side if you wanted, not the demand side. And when we piloted this, which we've been piloting in Palo Alto and a couple of other neighborhoods, we had the team members go and literally walk around Palo Alto to try to find babysitters to sign up for the service. Now, clearly, that's not the way we're going to do it long term, but we got supply to a point where we could test demand. Demand and supply were matched. And now we're looking at ways. How can we Actually prioritize this.

Yes. I'm struck by all the similarities. There's so many similarities between Nextdoor and LinkedIn and a lot of different points in the thing. Partly it's because by the end, you're gonna have this asset that looks like LinkedIn, which is very, very hard to say.

Well, let me show you some of the data, because I think the data is very interesting to look at. So this is where we are now, all 50 states. We've got Alaska and Hawaii in there. Go to the next slide, please. We've made it a goal to get highly penetrated in the major cities because as we think about building a competitive moat against any competitor, we want to own the most valuable cities in America. And these are some of them. And these are the percentages of neighborhoods in these cities. You'll also see something interesting, which is nextdoor is a true mass market phenomenon. It's not a Silicon Valley phenomenon. You're going to see cities all over the map here. Literally. You got Manhattan, Los Angeles, Houston, Washington, D.C. go to the next one. So now, to get a little bit more interesting, this is engagement. How frequently do people use the product? And the solid line is how frequently do our members. And the denominator is all registered members. So this is everyone who's ever signed up for Nextdoor. 41% is actually the jagged line. That's the percentage of our members who use the service every other day. And it's remarkably consistent. The two dips are Thanksgiving and Christmas. And what's interesting about it is the reason it's consistent is because while we've had to work to scale the number of neighborhoods, we have not had to work to scale the quality of the experience, because the quality of the experience was figured out in those early days. And so now we just need more neighborhoods using this thing.

Yeah, Alan said that, too. Alan Blue said, look, we're content to go slow until we figure out what made people really love it. And then you figure out ways to.

There's a time to actually step on the gas. And that time is when you're sure of where you're going. And you can be sure where you're going when your users tell you that they love the product. Go to the next.

Every other day usage is pretty good.

That's. I mean, look, the ultimate goal for a consumer Internet product is what Google calls the toothbrush test. We use our toothbrush once a day, hopefully some of us twice a day. Right. And so can you create a product that people are using every single day? That's the dream question. Oh, yeah. So I guess going back a little bit, you talked about how you piloted these 170 neighborhoods to see if there's any signal, but how did you know that these neighborhoods were representative of the rest of the year? Really, really good question. We worked hard to try to get a cross section of geographic diversity, socioeconomic diversity. We wanted rural and urban and suburban. We wanted senior folks and young folks. And what was pretty interesting is the use cases did have some variation from neighborhood to neighborhood. So in some neighborhoods, people were looking for babysitters in the marina In San Francisco, which is where many people go after they graduate from Stanford, no one's looking for a babysitter, but they do want to know what's going on on Friday night. So it's a different kind of conversation that you have with your neighbors. In senior citizen communities in Florida, there are neighbors that want to actually do bridge nights and solitaire nights and that sort of thing. Right. So the conversation differed. But the quality of engagement and the basic human need to connect with people around me, that was incredibly consistent. But it's a good question, because we did, because we were coming off of a failed startup, have a lot of skepticism about ourselves. So we did the first one. We said, well, this is just in Menlo Park. Anything would work in Menlo Park. So then we did another one, and we said, oh, well, that's just Portola Valley. Okay, now all we've got is a little coincidence. Menlo park and Portola Valley, right. So we said, let's force ourselves to go outside of California. So we went to Seattle, and then it worked in Seattle, and we said, well, maybe that's still just a tech kind of thing. And ultimately we made our way in that first 175 neighborhoods to Hamilton, New York, which is about as different a neighborhood as we've probably ever lived in, because we would see postings in that neighborhood of things like, I've lost my cow. My cow is wandering around the neighborhood. Can a neighbor please tell me if they've seen my cow? Right. And that's not what you see in either Menlo park or Portola Valley or any San Francisco neighborhood. But the conversation was still rich there, and it was still something that we felt had very strong signals. So we, again, systematically. Sometimes failure can be a very, very powerful motivational tool almost always, I think. And so we had this specter of, yeah, but is it really working? Is it really working? My wife asked me when we crossed 80,000 neighborhoods, which was just this week, she said, can you believe it? 80,000 neighborhoods. I remember when you told the company that first summer, if we get to 100 neighborhoods, we'll bring a dim sum cart into the company and give everyone dim sum and we'll call it the dim sum 100. And our engineers looked at me like I was crazy. We'll never get 100 neighborhoods in 90 days. That's crazy, right? Well, we got to 100. And then I remember telling them, if we get to 10,000, we're gonna do the Tuscany 10,000. We never went to Tuscany because we're scaling a lot, a lot more quickly now. But even when my wife said, we've run out of money, even though we've raised 200 million, we can't take all the employees to Tuscany, I did tell, I think we said we do have some goal about founders shaving their heads if we hit some extreme number of million, double dig millions users or something like that. But the idea was, and still is, we haven't made it. We're working hard every single day, and we're motivated by the fact that every single day we get some positive data points and we're just gonna keep going. And so there's this old quote. I'm not sure, it might be like a Sun Tzu quote, but the journey of a thousand miles begins with a single step or something. I'm not sure who. It's a train. Okay, so it's a Mao quote. Sorry, I was a little off. I don't quite know my super sad Asian historians, but that is very true for us. It's not true for all businesses, by the way. It's not true for all businesses, but for us, it's absolutely true. The only way for us to get there and get there for us is we want to be used by every neighbor in every neighborhood every day around the world.

The story you tell about, well, maybe this is just Palo Alto, or maybe it's just Portola Valley or whatever. It reminds me of my very, very favorite thing that anybody in Silicon Valley has ever said is Andy Grove saying, fight like you're right and listen like you're wr. And what he meant is that he wanted everybody to come at it with a strong product point of view about what's right. And he wanted them to be relentless about looking for data to figure out whether it was wrong or not.

Yeah. The interesting thing about data is your instinct and your intuition can be wrong. Data, if it's interpreted correctly, is very, very rarely wrong. And so what you see up here is what I commonly refer to as one of my favorite slides, what this shows here is a very systematic, consistent, predictable growth across neighborhoods, growth in size of members joining. And so what we've done here is we've cohorted the total number of neighborhoods we have, which is changing over time because we're adding more neighborhoods. We've cohorted them and we've said, okay, what percentage of the entire cohort corresponds to what size of members in a neighborhood? So you go back about two and a half years ago, Q1 of 2013, almost 60% of our neighborhoods had less than 100 neighbors using Nextdoor. Right. We were just getting started. It's literally like growing a tree. The first couple years you grow a tree, you don't see anything. But if you go to Muir woods and you see some of those incredible trees, those are trees that have been around for a long time. So what you see here with the green slowly but surely systematically growing is that all of our neighborhoods get larger over time. The denominator here, 2013, is 7,000. Over in 2015, it's 80,000. Right. So all these neighborhoods are getting bigger. Let's go to the next slide. I think.

Yeah. Dropbox had a feeling. Silicon Valley, love this idea because you're getting every cohort getting stronger over time. Dropbox had a chart like this, which is, every cohort is making more money than the month before.

Do you have increasing marginal utility?

That's right. You start stacking these things, and you get a very, very fast ramp.

You know, you have a network business. I mean, what's the definition of a network effect? Right. Every node that's added adds value to the entire network. Right. That's a little bit what you're seeing. I'll just show you this, and I'll take some questions. This is pretty interesting. This is looking at household penetration by neighborhood. And the neighborhoods that have launched on nextdoor are cohorted by their launch year date. So the green line here is all of our neighborhoods that were launched in 2012. So these are neighborhoods that are three years old, and they are now 30% penetrated. So 30% of the people in those neighborhoods, and it's the entire basket of neighborhoods is using nextdoor. What's interesting is if you look at the next year, 2013, which is the orange line, it's closely tracking. We're doing a little better, but it's very closely tracking 2012. Same for 2014, it's very closely tracking 2013, 2012. And then you look at 2015, it's about the same. So What I told John is if you see this kind of predictability and you can take a step back as a CEO and say, okay, as long as this continues, I know that Today we have 50% of neighborhoods in the country. I also know that at some point in time, that's years away, not many years away, all of those neighborhoods will have at least 30% penetration and more, actually, because it doesn't plateau, it keeps going. What that essentially says for me is, and the board, this is what VCs do. They saw this chart and they said, so are you telling me we could fire everyone in the company and at some point in the next three years, 50% of the neighborhoods in America would have 30% of their population on Nextdoor? That's not actually true. You couldn't fire everyone. You'd have to keep some of the engineers to keep the site up. But it's largely true, which is awesome. Not the firing part, but it's awesome from a predictability part. Because a lot of businesses that we see, or what I would refer to as treadmill businesses, every morning you wake up and you gotta go take a run on the treadmill. And those miles that you're accruing, that distance that you're traveling, you don't get any credit for it. Tomorrow, it's just one day you do everything you can, and then the next day you've got to earn the whole thing again. The really good networks, businesses that accrue value over time, it's not a treadmill business. Every single step you take is adding incremental value to the whole. And that is LinkedIn. That is the definitional quality of LinkedIn. And it's something that we hope is going to be true of nextdoor.

So let's see, questions for Luke.

How do you guys keep people on the platform once they make the connection here?

We should repeat the questions.

So sorry, how do we keep people on the platform once they're there? And then the second part, right, because.

There'S been a lot of cases where.

People go to platforms to make a connection. Yes. They bring it to another platform or text or something like that. So how do you guys manage that as an explorer, since you don't have.

To scale Facebook or.

We've been pretty lucky. When you have a platform that the average of all users is that 40% of those users are using the platform every other day. There's something that's so powerful in the core engagement of being able to tune in to what's going on in your neighborhood. And there really is no substitute. That's not actually a problem that we think about that much. We don't have a lot of churn. We don't have a lot of people who use the platform a lot and then go off and decay over time, which sometimes happens in gaming. You use the thing a lot, and then you're like, I'm sick of it. I'm done with farmville. I can't do it again. What we see on the other hand, is the opposite. People, they go in a little carefully, and then over time, as more neighbors join and as the information is richer and as their utility actually delivers more value, they use the product more. So I didn't show you a cohort where we take our neighborhoods and we say which neighborhoods have the highest engagement? And what you would see is the neighborhoods that are the largest have the highest engagement, which is also great because all the neighborhoods are getting larger. The one other thing I'd say is we're very lucky in that there isn't an obvious substitute. And John and I were talking about this. There's no Internet competitor, really, nor is there an offline competitor. And so it used to be, when I was at Stanford, I actually subscribed to the Chronicle as a student at Stanford.

A lot of people. Newspaper.

That is a newspaper. Dead trees, the whole thing. Right. And so I would get information about the local community. I'd read the Daily, I'd read the Chronicle, and that was it. I wouldn't go to CNN.com or whatever. I'd maybe watch the news, but that's where I would get the information. And today, I don't know anyone that reads a newspaper. Right. And so how do you tune into what's going on around you? We have to crowdsource that. You said you had 40% retention rate.

Now, do you remember how it was the first for the first neighborhood?

Incredibly consistent. And you can actually, if you go back one slide, you'll be able to see it, because one more slide. What's interesting here is this goes all the way back to June of 20 of 2014, and it's the same basic average. And so what that means is back then we had incredible retention, and today we do. Now, I always tell people two sides of the coin. The good news is 40% are using it every other day. The bad news is it's not 60%. But it turns out that when you slice the cohorts a little bit more finely, you find that the more established neighborhoods, which are older and larger, they do have increased engagement rates. So it does get better.

As a product thinker, you look at that chart is that it's nice that you have it because it provides you a base. Does it seem hard to increase it? As a product thinker, you say, well, maybe there's nothing we can do in the product.

Maybe this is natural. I would say, and the company would agree with me. Our product is very coarse. It's not a well refined product. And the reason for that is we're actually not a product company. We're a community company. And so the thing that we focused on and the thing that we've built and the thing that we obsess about all the time is community. And community is why we have 80,000 neighborhoods. But the product that services those communities, there's a lot of upside, a ton of upside. And all we have to do is look at the neighborhoods that have the most penetration to see rates that are much higher than 41%. So it's really about getting all neighborhoods to be like the best neighborhoods.

So what are your biggest growth bottlenecks and how did you figure out what they were?

We have a core growth bottleneck that is, it's sort of an interesting conceit because the bottleneck is also the reason for the service. So social networks typically grow through virality, and virality is I invite you to the service because I'm going to get something out of inviting you. Google is not a viral service. You tell people about Google because you just like it. It's word of mouth driven. But LinkedIn, you send a connection request to someone because you want to be connected to them. So we're the latter. Interestingly though, because Americans don't know their neighbors, they have no mechanisms to invite their neighbors. Now, the reason it's an interesting conceit is if they did know their neighbors, there would be no reason for nextdoor to exist. And so the reason that growth is so difficult for us is because of the value proposition that we're trying to create, which is people don't know their neighbors, so they can't easily invite them. If you think about Snapchat and Snapchat's growth, and we think about Instagram's growth as well. The social graph is something that Facebook doesn't have a monopoly on. All of us who have phones are carrying around our own social graph on our phone. It's not actually unique to Facebook. And so when a new service starts, if it's a service that relies on your friends, you can typically hit one button and bang, that whole thing is populated. There is no easy way for us to go neighborhood by neighborhood and populate the whole thing. We have to find one neighbor who knows two neighbors, and those two neighbors know two neighbors. And so we sort of systematically grow that way. We accelerated or heightened our growth problem by making a decision early on that the conversations would be private. So that means no SEO, no social sharing. So both the virality and the discoverability of Nextdoor, both of those things, are severely hampered, which is why, if he looked at this company before and we were just sort of whiteboarding it, he'd say, you've picked a very, very difficult execution path, because most of these things will grow either because they're intrinsically viral or because they're easily discoverable. And we've actually done the opposite in both cases. Now, how do we fight those things? We've done some pretty unique things. On the invitation side, we have many members. Our primary way of growing is neighbors invite their neighbors to the service. But if they don't know them, their neighbors, they don't know their email addresses, how do they do it? We pay for them to look at a map of their neighbors and click on the houses they want to invite, and then we will actually send a postcard on their behalf.

You'll still do that?

We will send this year many millions of dollars of postcards, I think on the order of 20 to 25,000 a day. Now, the nice thing is, every one of these postcards, one of our members has said, I want to invite that neighbor to the service. And so in the early days, you'd see all these tweets where someone would say, wow, this is really old school. And they'd be showing a picture of a postcard from next door. It's like, do you really use a postcard to get someone to join an online service? Right. Little counterintuitive.

And talk about nearby neighborhoods. That was like a. Yeah.

I mean, one of the things that you also want to look at is that virality. Like, is there a way to increase the viral vector that you could possibly have? Because if I say to you, I live in San Francisco, you live in Palo Alto, there's no reason for me to invite you to Nextdoor, because we're never going to interact. But maybe if we can connect Palo Alto to Menlo park in some way. Because there are some conversations that neighbors in Palo Alto and neighbors in Menlo park may want to have. Classifieds, for example, where you have an extended market. We came up with a feature called Nearby Neighborhoods, where today we not only connect you with your immediate neighbors. We allow you to also communicate with about the 10,000 closest households in other neighborhoods. And so those can be contiguous neighborhoods that are on your border, or they can be neighborhoods that are not exactly on your border, but very close to you. And that did two things. It created a better viral vector for growth. But the other thing it did is it increased the utility of the service. Because, for example, if you have a lost dog and you want to tell your neighbors you have a lost dog, your dog doesn't know that he's now leaving your neighborhood. And so no one else is going to be able to find him. Right, because he's going to the next neighborhood over. And so we had many people who said, look, the utility of the service will be better if I can communicate with a broader set of people. And there were other people who said, I live right on a boundary. I feel like I'm really part of both of these neighborhoods. And how can you proxy that? So it wasn't just a growth driver, it was a quality of experience driver. And I think old school Internet is the best. Growth driver is a great product. You hear a lot about growth hacking and that sort of thing. But ultimately, for a service like ours, every time we do something that really delights our members, we see a puff of growth.

It seems to me it also increased engagement a little bit. So it increased the density of people who are around you.

It got to the point where. So as an example, the number one use case on nextdoor is I'm looking for a service provider. So it could be a babysitter or a painter or a contractor, a doctor, dentist, et cetera. And that's 26% of our 11 or 12 million messages a day. And those typically have about 15 to 20 minutes before you get your first response from a neighbor. And over a 24 hour period, you typically will get a median of five and a half replies. So that's pretty incredible if you think about there's a platform out there where you can ask your neighbors for a service provider and within half an hour you'll get one answer and in the next 23 and a half hours you're going to get four more. That's pretty powerful. But we needed to increase the density of people that could respond to that query. And that's something nearby neighborhoods did.

I'm just going to put this thing on autoplay for the rest of the time. There's plenty of questions.

How did you think about revenue?

Good question.

How am I thinking about revenue?

How'd you solve the Problem.

I'm not sure if Reed has has copped to this, but in the early days when we were starting the company and I was leaning on Reid heavily for advice because he's built something like this or something that we aspire to be to follow in the footsteps of, he said, well, one way I think about it is you build user scale, you build usage scale, and then you build revenue scale. And it's this notion that when building a platform with indirect monetization, which is to say we will not charge our members directly, we need to monetize through ads or some services that we provide them or something like that. But the path that you do those things in, because each one of these problems, growth, engagement and monetization, each one of these problems are very difficult. The only way to solve them is to break them into sequential steps. So the first thing you do is you figure out a reason for people to simply join. Once you've figured that out, you can move on to a reason for people to stay on the service once they've joined and use it. Once you've figured that out, then you can move to monetization. And that's actually the path that Twitter and Facebook have followed. I think both of those companies were probably four to six years in before they started to truly monetize. And that's where we are today. And so 2016 is a really big year for us. I have an off site tomorrow morning where as a management team, we're going to talk about 2016 and how it's really going to be a great year for monetization for us because we feel like the platform from a user and usage standpoint is at scale. So now it's time to capture value. Yes.

So what product insights can you derive from the continued usage of Craigslist?

Given that it's. Yes, a great, great question. I think marketplaces are typically driven by liquidity over product experience. That's the number one.

The question was more or less, what can you figure out because Craigslist is.

So strong, or said a different way, why is Craigslist still around when 1,000 companies have tried to take it down? And from a superficial standpoint, there's no mobile app that's great for Craigslist. It's not intrinsically built for a mobile world. All these things that you see in great products, I think ultimately you go to buy things where the sellers are and you go to sell things where the buyers are. And Craigslist still has a lock in a couple of categories like real estate and Personals and others where it's still the best marketplace out there. Now we have a slightly different take on it, because Craigslist is a marketplace where you can go there anonymously and you can buy and sell anonymously. That's not the way Nextdoor works. Nextdoor, you have to verify your address. You have to put your real name in classifieds. For us, in Craigslist, that's not the direct competitor. We don't believe that there's a lot of business value for us there. We think they're doing a pretty good job, and we don't have a way of getting that kind of scale because of our model. But I think for other startups that are going after Craigslist, it's not about creating a prettier ui. It's about getting those audiences to shift. And that is very, very hard to do. Very hard.

Marketplaces are all about whether the transaction clears or not. If you put something up for sale, you want to make sure it sells. And nobody has liquidity like Craigslist. It's brutal to beat them.

Sure. Dial yourself back to 2012 at the.

End of 2012, and what are your.

Management objectives at 2012, 2030 and 2014.

As you've seen this?

Yeah, it's a great question. So I use this framework because it has been very helpful in the companies that I've been part of, which is, at any given time, you have sort of five objectives in a company. You have growth, you have engagement, you have monetization, you have infrastructure, and you have people. Okay, so those are five distinct things that you can be worrying about at any given time. And if you think about your total resources or your total focus as a pie chart of all of those things, you have to figure out what are the size of the slices at any given point in time. And sometimes that point in time is annual, sometimes it can be quarterly, Sometimes it's even briefer. If you have an outage, for example. I mean, interestingly, a lot of these services that get scale quickly, they go from spending no resources on infrastructure, and we did that to spending a lot of resources on infrastructure. So for us, if I go a little forward, 2014, towards the end of 2013, 2013 was all about growth for us. And we haven't put any percentage of the resources on monetization for a long time. Now we're about to get there. We've actually put surprisingly few resources on engagement, because in the first instantiation, 2011, we spent a lot of time, 176 neighborhoods, we were not focused on growth, we were focused on engagement. And so then the next year, 2012 was more about growth, 2013 was again about growth. And then 2014, we needed to actually invest in the service because it was coming down. We couldn't handle the number of concurrent messages that were being sent and that sort of thing. So again, as we move forward to 2016, I am thinking along with the management team about across these five things, what's going to get dialed up, what's going to get dialed down? The pie itself gets bigger because you raise more money, you hire more people, you have more resources, assuming that things are going well. But ultimately, those are the five knobs that I believe we can control. And as we look towards 2006, Tate, because my memory, I probably don't remember 2012 at this point, it's been overwritten. I have limited hard Drive space. 2016, certainly we're going to dial up monetization quite a bit. Growth for us in 2016 is about international expansion. So we're not necessarily dialing growth down, but we're directing it towards a different target. Whereas we've been domestic to date. And then I think that there should be. I mean, Interestingly, of the 50 or 60 engineers that we have, 30% at all times are dedicated to infrastructure, what we call core engineering. That's a lot of resources. That's a big slice of the pie that's on core engineering. And then people is something that. You guys talk about this in your class. I mean, as you start to scale the organization, you need to spend more of your resources thinking about how to take care of your people, how to create career paths for them, how to think about organizational structures that maximize the talent that you have in the organization. So we're dialing up organization and people. We're dialing up monetization. Right. We have more resources. So in some cases, even though I say we're dialing down growth, we still have the same number of resources towards growth. It's just as a percentage of the whole. It's gone down a little bit.

Can you talk about how the planning. So you talk about setting these priorities. You've got an off site. How has that changed as you've gotten bigger? So you're up over 100 people now, heading towards Dunbar's number.

I think what happens as you get larger is you have a clearer grasp on the near term, which gives you the freedom to spend a little bit more time planning the near and sort of the mid to long term, I'd say. So in the early Days of the company. We think about 2010, 2011. We were not doing annual planning. It just didn't make any sense. We were literally having standups every week thinking about what are we trying to accomplish this week. Right. So now we're at a point, I've just hired a great executive for HR to come in because again, we want to dial up our investment on people. And one of the things she told me was, okay, we're doing this 2016 planning, and that's all fine, but what's the bigger picture? Where are we at the end of 2017? Where are we at the end of 2018? And for so long I've thought, I can barely keep track of what's going on next quarter. Like, I can't think about next year. But then I started to realize the reason it's so important at our stage to think about 2017 and even beyond is we can't. If we don't set that big goal and then work backwards, we may not choose the right things to do in 2016. So what happens over time is you have more people involved. That's sort of obvious. We try to create real bottoms up planning of the real initiatives. And so again, as a company gets larger, you want to get as many people involved as possible, but it's hard to do. You have to develop processes to do that. So it's not just chaotic. And so we typically, as a management team, say in these five areas, here's an okr, an objective and a key result in each of these areas. But how? That's sort of the what. And maybe at a higher level, for me as CEO, I have to articulate why. Why is this important. So I start with why the team comes in and helps us understand what. But then the how is something that we want everyone in the company to participate in because they're the ones that are actually creating this value. When you're small, you're doing that all in one room in a very sort of haphazard, like, you don't want that overhead off sites and thinking about strategic planning. And, you know, this is sort of paralysis by analysis in the early days. But as you get a little further on, you need to dial that up a little bit.

Can you talk about one or two of the strategies or tactics you learned for Bill Campbell?

Yeah. So I was very lucky with opinions to have a guy named Bill Campbell on my board, who's my CEO coach, and he's probably the most incredible mentor, advisor, coach, management kind of expert in Silicon Valley. In fact, I used to joke, because when he was coaching me, he was also coaching Steve Jobs and Eric Schmidt at Google and Jeff Bezos. And he'd come visit me and I'd say, time for the scrub team. Right? Because you know, you've been with the real CEOs and now you gotta come with me. But he's like a business father to me. I would say to most people that most of the good things that I've been able to accomplish, I've learned things from him that have enabled those things and all the bad things that I've done, he gets none of the blame for any of those. But a couple of things. He ran into it for a long time. He was the CEO and I think he's still the chair. And they had a set of core values. And the first one was something along the lines of it's all about the people. And so the first and probably most important thing I learned from Bill is it is all about the people. These things that we're building, these companies, these products, these businesses, it all comes down to talented people. And so getting talented people in a room, making sure they're aligned, getting the team together, and then pointing at the mountain and then taking the mountain together, that's what he's exceptional at. And he's done it in his own companies. And he's helped many incredible companies do the same thing. He was a football coach for a long time, but he's the ultimate coach in general, and I mean that term in as glorious a way as you could mean it. He's the ultimate coach.

He doesn't get a lot of ink these days. He's a behind the scenes guy, but he's probably the best mentor, like one of the best mentors in the world. And I think that what he's really special about is that he can give you specific situational guidance. But he also recognizes that you're not the same guy as Eric, wasn't the same guy as Steve. And I think he coaches, he sees the genius of you, and he kind of puts his advice and hangs that around who you are.

Yeah, he's got, I would say, three incredible, incredible and unique skills. The first is he's just an incredible leader himself. Like an unbelievable leader himself. His instincts are incredible. And he's someone that people want to follow. He always used to tell me, your title doesn't make you a leader. Your people make you a leader. Being a leader is about being someone that people will follow. And he's someone people will follow. And so you want to soak up as much as you possibly can. That's the first thing. Second thing is the guy's actually done it. So he's not a professor who's never been in the field. He's not a management consultant who's helped with a few people, but has never had to make the decisions himself. I mean, this is a guy who's been in the boiler room and has achieved tremendous success doing it. And he knows and empathizes with everything that you have to do as a CEO or as a management team member. And then the third thing is, think about the companies that he's been around. Apple, Google, Amazon. I mean, what has he seen? He's literally seen the history of our industry. Right. I don't think there's anyone like him. No way. Yeah. So, taking a step back, what is the conversion rate of the postcards you.

Guys sent back to Growth?

Yeah, they won't let me divulge the numbers, but what I will say is it's not as high as we'd like it to be, but particularly in 2005, 15, we've been able to significantly increase the conversion rate, which then allows us to send out more postcards, because we're looking at a cost per acquisition, and we're sort of backing into that based on the conversion rate. And so we're very strategic about postcards. I'll give you two vectors upon which we're strategic. The first is we don't give every neighborhood the same number of postcards. If a neighborhood has 2,000 members, the neighborhood as a whole gets very few postcards because it doesn't need them. But if a neighborhood is trying to get to 10, we may give those early people who are starting the neighborhood 100 postcards. Right. So that's the first thing that's actually pretty interesting. In fact, moving into 2016, I think most of our postcards will be going to neighborhoods that have fewer than 50 members, because we know from all the data that the neighborhood's above 50. They're just going to grow on their own. The second vector that's interesting is we've now built a reward system where the number of postcards you get as an individual is driven by the number of acceptances from postcards that you've sent in the past. So if we've given you 10 postcards and you've sent them out and five of your neighbors have joined, you get more. If we've given you 10 postcards and you sent them out and none of your neighbors joined, you may not get any more. This is done on a monthly basis. And it's actually pretty interesting to look at the data because the first day of the month we have this giant spike in postcards sent because there are literally people, they want so badly for their next door neighborhoods to get penetrated that they're waiting until the clock strikes midnight on the first day of the month and then they're sending all their postcards out.

Can I ask a dumb question? Maybe. So how do you figure out what's a reasonable CPA for a pre monetization?

Yeah, you have to have some assumptions of ultimately how much you can monetize those people on the other end. Right. So let me just hypothetically say that these postcards, the CPA ended up being a dollar. So it's a dollar for us to use postcards to acquire members. Right. We should be able to generate a dollar per member in some reasonable number of time. And we've got to back out the churn members and we've got to back out any other things. Sort of, you know, you can do, you can write fiction in Excel, as they say. So you've got to be very diligent about it. I think for us it was a combination of thinking about value capture, but it was also a combination of thinking about value creation, which is what is it worth to us to have 80,000 neighborhoods that have launched and how much would we pay for that? So we look at it a number of different ways, but because as a management team, many of us have laid off people, we are exceptionally careful with our funds, exceptionally careful. We have to be.

This is a really difficult, just for the record, this is a really difficult calculus because you can fiction in Excel, right? You can convince yourself of almost anything. You can just justify almost any spend for the rationalization. Well, you know, I'll tell you sort.

Of in general, as a CEO, I'm okay with spot spending for experimentation and if it fails, no problem, because you don't have to do it again. The things that I'm very wary of and over hiring is one of these people one of these things. I'm very wary of spending money where I'm locked into spending over the long term without any terminal point. Right. So when you hire someone, you're giving that person the job and if things work out, you want that person to work with the company for as long as possible.

Right.

But if you decide to do a test where we give twice as many postcards to some group of people and we see what happens, we measure the conversion, we don't have to do that next month, right? So I'm a big fan of taking risks because you have to take risks to actually have successes. But I like to bound those. I like to be disciplined in boundaries.

Another way to say that things that increase your structural, things that increase your burn are dangerous.

Very dangerous.

Long term leases are terrible.

They're terrible. In fact, today the last three leases that I've signed have been subleases. They cost a little more, but they are not long term. And I don't know how to predict the size of the company and its square footage needs over a three year period. I mean, I shouldn't be able to because if things are going well, we should be growing a lot, right? And so I'm willing to pay more per square foot to not lock myself into a 12 year in San Francisco. Now the landlords are looking for a 12 year commitment, right? And they're getting it. They're getting it. And the math people are using is they're saying, well, there's such a huge demand out there for office space that even if I grow out of this space in three years, I'll find someone else to sublease it for me. Well, there are two problems. One is what if they contract and they don't need the space themselves? Right. And number two, if the whole market contracts, that demand's gonna shrink. It's smart on the landlord's part because they wanna lock in all the good stuff that's happening today. But it's very dangerous for startups. Very, very dangerous. Yes.

Two questions. First is the natural inclination of behavior methods would be between 25 and have you had any surprises and are you able to attract others? The second question is I appreciate the discipline of getting the members. Now, as you think about moving into a product phase or a revenue phase beyond advertising, can you give some overview of how you think about shared services or other?

Yeah. So on the 1st, I used to tease the team because they would come to me initially and they'd say, well Our member is 35 to 55, married, kids. And I'd say no, no, no, no, no, I don't want to create that kind of product that has that kind of narrow band. And I thought about it and I said, but it sort of is the data, so you can't dispute the data. Right. And ultimately what we realized is what was the age band of the first million users of Facebook? It was like 17 to 21. What's the age band today? Well, I know my 72 or 73 year old mom is on that thing Every single day. And so you pick an initial market and you overserve that market. And that for us was people who own their homes. And so you have to be a little older because you've generated some capital to do it. Who had children, they cared about safety, they cared about schools, those kinds of things that were living in suburban areas because that's where you can afford homes and send your kids to school. So that's really where we saw real penetration early on. Here we are today, 90% plus of the neighborhoods in the top 40 cities. There's no rhyme or reason. We have incredible penetration in Florida senior citizen communities and we have incredible penetration in the most urban areas, like Potrero Hill in San Francisco, where you have a much younger base. There's even some neighborhood at Stanford. I don't know exactly what's happening with that neighborhood. You should try to join it. I think it might be some professors or some folks who live on the Stanford campus. But the hope was always that we would pick a group initially and then widen the aperture, either through product features or just because we understood the needs of the users. What it turned out happened for us is our core value proposition, which is to speak with your neighbors or communicate and connect with your neighbors in a trusted way. That's not an age driven value proposition. It started as it's more important for a certain set of people, but it turns out that it's marginally important to everyone who lives in a neighborhood. So now the ambition, it knows no bounds. We believe, and we said this at a board meeting a couple of months ago, 100% of the neighborhoods in the country should be using nextdoor at some point in the future. It shouldn't be just the neighborhoods that have married people. Now the second question, how do we think about modernization? I think there's interesting learnings here, particularly for consumer Internet companies that have indirect models where you're not going to ask your members to pay. Uber and Amazon, they ask you to pay, right? It's a direct transaction. You know what you're getting into. Google and Facebook, they're free services and they're monetizing through you. So let's talk about those two as a way of illustrating the way we think about it. For Google, the ads in many cases are a part of the product. If you do a query on some commercial thing, you may think of the ads as content. And I think they've even done all kinds of testing and analysis that shows that when they remove the ads on certain queries, trust goes down. Doesn't go up because they're useful. Okay, now let's think about Facebook, which, by the way, is a juggernaut. They're doing incredibly well. And I tremendous respect in every way for what they're doing. However, I have never clicked on an ad on Facebook and I've never thought to myself, I'm going to Facebook and I hope I see an ad that I like. Right? And so they have said we have such incredible scale and they do a billion concurrent users in a single day, that we can just put a couple of ads in there and we can drive what they refer to as demand generation. Whereas Google has demand fulfillment. When you go to Google and you type in digital camera, you want to buy a digital camera and they're going to help you fulfill. When you go to Facebook and they show you a picture of the newest camera and 100 of your friends like it, you may actually say, cool, I want to go buy this camera. But that's demand generation versus demand fulfillment. That's the way we're thinking about nextdoor as well. So I'll give you a couple of examples. I mentioned that 26% of our use cases are around finding a service provider that's demand fulfillment. Neighbors, does anyone know of a great contractor? Well, we should be able to, in a very straightforward way, monetize that. And we plan to. Now, on the other hand, real estate agents are clamoring to get into next door because they either want to tell you how much your home is worth so you can sell it, or to tell you that there's another home around you that's bigger and nicer that you may want to buy. But they want to catch people who aren't necessarily thinking about buying or selling their homes. In that case, it might be demand generation for us. So we're thinking about both of those. But I think the important thing is over half of the conversations that go on on nextdoor are what we would call transactional. There aren't status updates and photo sharing. Like, it's not like you come back from Hawaii and you say, hey, neighbors, look at these killer waves that I just surfed on, right? It's much more. You go to your neighbors and you say, hey, I'm thinking about where to kids send my kids to school. Do you guys have any feedback? If it's a private school, that's a very large, high economic value decision. And so the good news for us is there are conversations about cleaning up graffiti and about getting together to have a barbecue that aren't easily monetizable. But in Google's case, only 30% of the queries or where they generate capital. And we might think of Nextdoor the same way that 50%, that's transactional. We want to drive both demand fulfillment, which is very straightforward, but we also want to think critically about demand generation.

One more question, and then we should wrap up. Who.

Okay, this one right there. Do you police your neighborhood from, like, their name is there, but they may not really care about their individuals. There's been a lot of discussion recently about how do we make these conversations as civil as possible, because we do require verification. We also screen out all sex offenders because they're required to register where they live. So you cannot join next door if you're a sex offender. And because of this core intrinsic thing, which is if you're mean to your neighbors, you may see them in the real world the next day. If you're mean to someone on a message board on the Internet, and that happens all the time. Message boards are basically message boards, and comments tend to be cesspools of meanness in many cases. Right. But it happens much less on nextdoor because you have to see these people. If you raised your hand and you said something really inappropriate, mean, you come back to class a week from now and all these people see you. That's a different kind of regulation. That being said, whether it's education around the right way to report criminal activity or whether it's the neighbors talking about some political issue where there's a disagreement, we have to remember that civility and constructive dialogue is the way these neighborhoods get better. And so that's actually, as we think about 2016, going to be one of our big focuses, because before we had these massively penetrated neighborhoods where there were thousands of neighbors communicating, it was mostly all utility. There's no bad actors. When someone says, hey, neighbors, do you know of a great dog walker? That's not a good opportunity to be mean. Right. But in San Francisco now, if someone posts, hey, here's the ballot for the upcoming election on November 3rd, and here's who I think we should vote for, there's a very spirited conversation that goes on after that, and people disagree, and that's okay. That's good, because we want that conversation to happen, but we want it to happen in a constructive way, and that's something we're focused on. I think every large platform, Facebook went through this a little bit where it was used as a platform for bullying, and sometimes it still can be stalking, that sort of thing. It's any large platform that gains scale, and Facebook is at the very top of the list. Has a responsibility towards making sure the conversations and interactions are as safe and civil as possible, and we take that seriously.

All right. I think we'll end up. Thank you very much, Nirav.

Thank you, guys.