The below is a full (unedited) transcript of a Youtube session / podcasting episode I recorded with Leo Polovets, founding parter at Susa Ventures in Q2 2020. You can view the video/listen to the podcast on Youtube, Apple Podcast, Stitcher or wherever you get your podcasts.
Erasmus Elsner 0:07
What’s up everybody? Welcome to another episode of Sand Hill Road, the show where I talk to successful startup founders and investors about the companies that they built an invest in. And the goal, like always, is to give you a sense of what it’s like to be in their shoes, to understand how their businesses take, learn from the many successes and mistakes. And today, I have the honor to announce my very special guest, Leo Polovets from Susa Ventures. Before starting out, Susa Leo gained more than 10 years of experience as a software engineer, which is why his personal blog is also called the “coding VC”. And his experience ranges from really pre-seed small startups to scale ups to really big tech. Believe it or not, he started out his career as a second engineer at LinkedIn. Working on most of the website features released between 2003 and 2005. In 2005, Leo decides that he wants to get some flavor of big tech. So he joins Google just a year after that IPO. And he worked there for four years working on the fraud detection infrastructure. In 2009, he’s seen enough of big tech, and decides he wants to join a smaller startup. So he joins Factual a location startup before they had even raised their seed. At Factual he was Hadoop-ifying the data processing pipeline. So fast forward in 2012. Leo’s friend Eva Ho, asks him whether he wants to join her and two friends in starting a new venture firm as their technical partner and Leo jumps. They managed to raise a small $25 million maiden seed fund from which they make 41 investments. Of these 41 investments, there are four breakout companies including in Lendup, Flexport and Robinhood. And so it comes as no surprise that when they raised their second fund four years later, they have doubled the LP commitmentsto $50 million. And then most recently, last year, they managed to raise two new funds, a third generation of their flagship Fund, which came in at $90 million. In addition, they raised another $50 million for the first Opportunity Fund. The fund’s thesis, which Leo will unpack a little bit for us in this session, is around so-called “compounding moats”, such as proprietary data, economies of scale, and the good old network effects. But I would say let’s hear it from Leo himself. And let’s jump right in.
All right, welcome to another session, and I’m super excited to announce my guest today, Leo pullets, who is a co founder and general partner at Sousa ventures, one of my absolutely favorite seed funds in Silicon Valley, having invested in the likes of and Bella, land up Robin Hood and flex port Leo, super excited to have you with me today. Are you ready to take it from the top?
Leo Polovets 3:32
Yeah, I’m excited to be here. Thanks for asking us.
Erasmus Elsner 3:34
So you’ve been crushing it on VC Twitter. But before I want to dive into your life as a Twitter icon, VC, Twitter, I can and as a VC, I want to take a step back and learn a little bit more about where you came from. So let’s start with your first job at LinkedIn where you joined us their second engineer after completing a Bachelors of Science and computer science from no less than Caltech. So tell me, how was it in these early days at LinkedIn with Reed Hoffman must have been quite the experience out of college.
Leo Polovets 4:04
Yeah, it was, it was definitely a really special experience. And I feel like I got really lucky I joined the company when it was just over a dozen people. And it was because I had known one of the co founders during an internship in college and he invited me to join and you know, to be honest, I didn’t really have a good sense of like, where LinkedIn might go. I think social networking was really new. At the time, I didn’t really have a specific like thesis on how that might evolve. I just wanted to work with this friend that was a really good engineer that I had met previously. And then the company ended up being really successful. But the team was really small when I was there, you know, most of most of the time, it was like three, four or five engineers for the first couple of years. And when I joined the product was really early. So you know basically had like profiles, invitations and I think like a way to upload your address book and that was about it. And then over time, you know, we added messaging and you know the job board and LinkedIn groups and payments and ads and all of that stuff. And all of that basically came in the first few years. And I think like, they got really lucky because most companies struggle to just get like a single revenue stream that works. And they had three or four, that worked pretty well. And so it’s just like a really cool experience to watch that company grow in the very early days from, you know, sort of 10s of 1000s of users to maybe a little millions when I left. And I would say, Reed was definitely like a visionary too. So when I first met him, I asked him, like, what his what his vision was for the company, I remember him saying, you know, something like, maybe three 400 million white collar workers could be on the platform someday. And this is back in like 2000 to 2003. Or I think, I don’t even know if Yahoo had two or 300 million users. So it’s like such an audacious prediction. And I think now LinkedIn is maybe like two or 3x set. But like, read really nailed the vision. And I think he had a lot of, you know, a lot of thoughts on like, where the product would go, how people would use it. And a lot of those ended up coming true over the next 1015 years.
Erasmus Elsner 5:55
Then in 2005, you decide you want to a flavor of big tech, and you decide to join Google a year after they had IPO. And you worked on their payment fraud infrastructure for four years there. Talk to us a little bit about how that was and how this was different from maybe the environment at LinkedIn.
Leo Polovets 6:15
Yeah. So you know, to be honest, I was pretty happy at LinkedIn. But I was, I was like a hardcore math and algorithms guy in college in high school and did like programming competitions, really enjoyed things like that. And a lot of my friends that I had made, you know, that were like, from some of those programming competitions, most of them actually ended up going to Google. And they were kind of reaching out and saying, like, I should apply, I’d really like it there. And I was, I was pretty happy at LinkedIn. But I kind of figured, well, I’ll apply, you know, if I don’t get in, I’ll just stay at LinkedIn. And I’m happy here. And if I if I do get it, I’ll think about it. And so after going through the interview process, Google gave me an offer. And they invited me to join the payment fraud team, which is, you know, they were basically launching a pupil competitor. And they wanted somebody to help them look at data and like, try to figure out, you know, which credit card transactions might be fraudulent real time, and it seemed like a really interesting problem. And I also figured it would be like interesting to get an experience of working at a big company, because I think back then Google is probably, you know, I think probably the highest regarded tech company by engineers. Like they just launched Gmail, they just launched Google Maps, which are really groundbreaking at the time, they had recruited a bunch of like, kind of the foremost experts on a bunch of engineering topics. So it seemed like a really cool place to work. And so, you know, I thought about it for a while and decided, you know, it’s been a couple years at LinkedIn, and I wanted to try working in a big company. And so I ended up spending a little over three years at Google, I work mostly work in the payment fraud project.
Erasmus Elsner 7:35
Yeah, Google was a big challenge for every engineer to crack the coding interview. And it was really an engineer’s first company. And then in 2009, you decided you needed an early stage startup environment again. And so you meet Jill Elbaz, who has previously founded plaid semantics, which was later acquired by Google considered to be one of the most important early acquisitions of Google, really forming the backbone of what is now AdSense. And you decide to join factual as an early team member. And I know you’re not a venture capitalist by that point in time. But being an early employee in a in a startup, before it does raise a seed round is a little bit like an undiversified investment in a sense. So when you consider this option, what were your thoughts on the business model and the future of factual,
Leo Polovets 8:24
I think what really attracted me to factual was the people and the mission, the products evolved a bit over time, but initially, the founder basically wanted to build something like Wikipedia for structured data. So Wikipedia people, you know, upload essays, they can collaborate, they can like link to other essays. The idea was to do that, for datasets, you know, seek upload some data, you could, you know, use factual tools to like clean it up or join it with other datasets that would be sort of this, like, you know, huge global data platform. So, you know, seeing both like a cool mission and a really interesting technical challenge. So something I was excited to work on. But I think the team was like, what really what was really special for me. So as you mentioned, Gil had this amazing experience of building, essentially the precursor to AdSense, which was, you know, almost half of Google’s revenue. And then he he rang Google Santa Monica office for a few years on the engineering side. And the company was still pretty small, I think was about 15 people. So I got a chance to work with him pretty closely and learn from him. My boss was also like my direct Boss, I was just kind to him. He’s like one of the smartest people I’ve ever met. He was a he was like a world math Olympiad, you know, silver medalist or something in high school. So, like the caliber of people is just really top notch. And I would say just, you know, looking back a lot of the opportunities I’ve ended up taking or not taking, when I when I end up going all in on something, it tends to be where I’m really excited with the mission or the people where, you know, even if financially something ends up not working out. I still feel like I had a really good experience. I learned a lot like I you know, I kind of grew as a person. And then also, I look a lot of the opportunity Costs where, you know, I think, for example, like coming from Google, I could probably have gotten a job at Facebook, or maybe a couple years later Twitter. But I think there’s always companies like that around where, you know, at any given point, like if if I had wanted to apply to a big company, you know, if I applied to a couple of them, I’m pretty sure I could have gotten into at least one. And so I feel like those opportunities are always there in the background as a backup, but you know, something like factual, where I get to work, you know, is like one of, you know, 1015 people with this guy that, you know, previously built like, half of Google’s revenue stream, and another startup, like, that seemed like a really unique opportunity, that would be really hard to find again. So I really jumped on that.
Erasmus Elsner 10:37
Yeah, it makes a lot of sense. And so in 2012, your friends asked you to become the technical partner in a new venture firm that they were starting. And before I want to talk more about Sousa, I want to talk a little bit about the name. The name is a reference to a family of mountain gorillas. And I think all of the partners have visited this family of mountain gorillas, your colleague, Chad Byers said that Sousa is really a family and a support network. And I found this angel list reference about you as an investor, which said, Leo is willing to jump into code review API documentation, and always be be thoughtful and give very technical advice. So it was really formed around this gorilla family support network. I know there’s this picture of you with this gorilla. I’m intrigued.
Leo Polovets 11:22
Yeah, well, I mean, so to be quite honest, I think when we there were four partners initially. And when we first got together, we’re, you know, most important thing for any company is like, instead of doing real work, you start thinking about what’s your name be like, what’s your website be? So we were thinking about, you know, what are good names for VC fund. And I think we kind of went through a list of all the all the names that are pretty common, like, you know, names like mountain ranges, and, you know, geographic like entities and things like that. And, and a lot of them were taken, I think were also just personally weren’t, like, weren’t really feeling inspired by them. And then as we were talking about other other ideas for names will realize is like all of us had seen this group of gorillas in Rwanda called the Susa family. And Susa is basically the name of like the oldest, you know, kind of patriarch in that group. And we thought that was really cool coincidence, because they, the government, or wannabes, who gives like 10 individual permits a day to see these gorillas, so it’s like, 3000 people a year. And so the fact that, you know, several of us had seen them independently felt like a pretty neat coincidence. And we do it also really like that these girls have, like, really tight family groups, like, you know, they grow up together for like, decades, you know, they help each other support each other. And we thought, we thought that was a good, like a good way to build a venture fund as well, where it’s less of a, you know, like an investment portfolio or set up like one on one financial transactions. And a little bit more like a community or a family where everyone tries to help each other everyone tries to, like, you know, advance everyone else. Everyone else’s, like ambitions in the family and help them out when they’re, when they’re struggling.
Erasmus Elsner 12:52
I really liked the name. And and so your original plan was really to, to join the group for maybe six months or a year, and then later, start your own startup, the experience as a VC you mentioned was something that was really humbling for you. And you had this analogy to the NBA, that when you play with your friends in your hood, you feel like like you’re on top, and you’re really crushing it. And then you spend a day playing in the NBA. It’s a really humbling experience. Talk to us a little bit about this.
Leo Polovets 13:19
Yeah. So like you said, I originally thought I’d maybe do venture capital for a year, I actually had never thought about joining it. You know, it was an opportunity that came up because one of my friends was starting the fund. And like you said, they wanted a technical partner on the team. And my goal was actually, you know, I’d been at LinkedIn and factual at roughly the 15 to 50% stage of both companies. And as my ideas for businesses, I wanted to start, but I felt like I didn’t really know anything about, you know, what does it take to build a company when it’s, you know, two people or five people. And so I wanted to learn more about that. And so when my friend Eva invited me to know, try out joining Susa, or it was, you know, the angel group that was going to become Susa, are really excited about that, because I figured, hey, I could spend a year on this, you know, I could meet a bunch of investors and build a network there, I could build meet a lot of founders that are, you know, at that two or five person stage and learn about, you know, what are their challenges, like, what does it take to grow a company from that stage to the stage I was more familiar with, is that was the initial goal, I thought, you know, I thought I’d maybe do this for about a year. And then I’d go back and then even start my own company. And I would say, in that first year, year and a half, I met some just like, really amazing founders. You know, there’s people like, there’s Jeremy Johnson and, and Bella, for example. And that guy’s basically like a walking TED Talk, where you listen to him for like, 1015 minutes, and it’s just so inspiring. And you’re like, I want to drop everything and go work for him and like, help him build his company. Or, you know, maybe like Brian Peterson or flexport, which, you know, he’s just like, he has so much ambition and vision where you talk to him and you’re like that, you know, flexport is going to be $100 billion company and like, I want to be a part of that. And so when I met those people, I was like, you know, they’re really good at this. I think it’d be okay, but I think I wouldn’t be at that level. And so it really gave me you know, made me pause in terms of Whether I wanted to be a founder, and I think around that time was also feeling like, Susa is actually a little bit like a startup where, you know, obviously, it’s a fun, it’s a very different kind of business. But we’re still doing a lot of company building like things where we’re recruiting, we’re trying to think about, like, what’s our mission? Like? What’s our place in the market? How do we differentiate? Like, what kind of products do we have, you know, for founders. And so that was, like, pretty fun to think about that stuff, and a lot of fun to meet with, like, Great founders and work with them as they build their companies. And so, you know, I think after a year, year and a half, I realized, like, actually didn’t want to start a company anymore. I just wanted to work on Susa for a long time. Yeah, that’s about seven years now.
Erasmus Elsner 15:38
So I used to work for an institutional LPs. So I want to talk a little bit about fundraising. So you managed to raise a first micro fund a 25 million micro fund, out of which we made 41 investments, and of these 41 and investments, you had four breakout companies and della flexport, Robinhood, lend up. And so one dynamic that you often see is these companies that manage to raise much larger rounds, you can mark up the deals really quickly. And so you get a pretty good TVPI, although the unrealized portion is still pretty high. So talk to us a little bit how you think about these dynamics, you know, let’s say flexport had delivered really good metrics, but didn’t raise such large rounds. how this would have fed into your fundraising process for the follow on funds.
Leo Polovets 16:28
And venture capital is definitely a very interesting industry. Because essentially, you’re, you’re sort of being graded on what you did, you know, five or seven or 10 years ago. And I think in a lot of other places, it’s it’s sort of a crazy thing to think about, you know, to think about careers that way, right? Which is like, Hey, Erasmus. Like you were a great, you know, software engineering intern seven years ago, do you want to be my director of engineering, right? Like, people don’t really think about things like that, it’s more of a progression. And here, it’s there’s less progression, there’s just like this, like 10 year feedback cycle. And in overtime, people are looking for proxies like, which companies embrace fall on funding or how far along they are a lot of your success or failure in fundraising ends up being, you know, how good the early companies you invested in seem. And we got pretty lucky because we we did invest in like flexport, and Robin Hood, basically in the first like, 1215 months of Susa, and to your point, they raised a lot of money pretty quickly. And so I think that that made our fund look pretty good on paper, I think even if they hadn’t raised, you know, people still look at other other proxies for success. So like, it could be number of employees, right, where, you know, if you raise $2 million, and then even if you haven’t raised more, where your company is now, like 200 people, presumably, you’re doing something, right, because like, and maybe even better than if you had had to raise to get to 200 people, cuz you don’t get to that kind of scale, once your business is really working. But you know, people looked a lot like who were the follow on investors, who do we co invest with, you know, kind of how hot some of those companies are just in terms of like, kind of the buzz in Silicon Valley. And that that really helped us raise our next fund. So I think we’ve been we feel very fortunate about that.
Erasmus Elsner 18:03
Yeah, for sure. And so let’s talk a little bit about the Sousa thesis, which is around compounding modes. And I want to unpack this a little bit and really go back to the, to the basics, what are modes and why are they important,
Leo Polovets 18:16
fundamentally, a mode is a sustainable competitive advantage. And those competitive advantages are usually things that either let you have lower costs than your competitors, or they let you create more value than your competitors. And then the sustainable part of that sustainable competitive advantage means it’s like hard to copy some of the really common ones, you know, brand can be a moat, right, like because, you know, if you have a really good brand like apple, you could maybe charge a lot more for the exact same device, then, you know, an Android phone or Samsung, you have data network effects. So somebody like Google has a lot of data on search queries and search results. And when people click on, and so that lets them create a much better product than somebody that maybe has a good search algorithm, but like no data to really train it with. There’s things like network effects. So that’s often for like LinkedIn or Facebook, like, the bigger the network gets, the more valuable it is to each user. And so even if somebody has a better product, like it’s hard for them to get started and compete against you. So there are a lot of these examples. And I would say like in the early days of startups, none of this matters too much. Because you’re just looking for product market fit, you know, often your company’s small and maybe even like your business opportunities, you know, not even recognized by everyone, like you see up and nobody else does. And so like, nobody’s really trying to copy you. But then as you get bigger, that changes, right? So, you know, maybe someday, you know, it’s like you raise $100 million, and you have a lot of revenue. And now suddenly, there’s a lot of startups being like, Hey, I think I could do this better than you because I have some other insight, or maybe some big companies thinking like, you know, this is close to our product lines, like why don’t we add an adjacent product. And so I think that’s where moats become really important. Because you want to make sure that you know when people look at your business and think like I want a copy of that, you want it to be so hard to copy that they give up or like you know, ideally they don’t even try in the first place
Erasmus Elsner 19:58
and then aspect of the business. pounding part, we know that people are really bad at estimating compounding interest. And the same I think applies very much to two compounding modes. When we talk a little bit about this compounding aspects, you mentioned the network effects and the data modes as well,
Leo Polovets 20:15
I think one way to try to quantify the value of a moat is to think about, what would it cost for somebody to try to, like, try to overcome it, right. And so there’s some modes, like, let’s say, IP, where I think the value doesn’t change a lot as your company grows, like, you have some patents, and maybe, you know, maybe it takes $5 million dollars for somebody to come up with a different way of doing the same thing. Like, it’s gonna be $5 million, whether you’re a million dollar company, or a billion dollar company. And so that’s, that’s a little bit tricky, because when you are a billion dollar company, maybe somebody’s like, hey, it would be worth $5 million to try to compete with you. But then there’s other things like let’s say, you know, Google’s data set, right? When they’re small, and maybe they’ve had only like, a million users, every user search engine, it doesn’t take a lot for somebody to try to get that kind of user base, right? Like maybe, maybe Microsoft puts up a search engine, and they get that kind of traffic almost for free. And so like that data sets, not that hard to copy, but you know, as Google doubles, and doubles, and doubles again, and maybe now they have like, you know, years of data from 100 million people or a billion people. Now, when you think about, you know, what would it take for Microsoft or a startup to get, you know, billions or trillions of queries worth of historical data? That’s like an astounding cost. I would say you could think about network effects the same way, right? with, you know, like a Facebook’s on one campus, like, what does it take for somebody else to copy that? I know, you can probably give like 1000 students like 50 bucks each. And like, now you have, you know, the same sort of like network and another campus. But when Facebook has, you know, a billion people on the platform, like, how do you get a billion people to switch over to your platform, like, that’s gonna be astronomical. Alright. So I think these kinds of modes like data, network effects are really valuable. Because generally, the bigger the companies get, the more costly it is for somebody else to try to do the same thing.
Erasmus Elsner 22:04
I want to dig a little bit deeper into data modes, where you’ve written a lot about it on your coding VC blog. And I want to push you a little bit here, Martine casado, from a 16 set has written this, the empty promise of data modes. And when you wrote your, your articles in 2015, I think it was, you were quite optimistic about data modes. And I think the argument that Martin casado is making is that there’s sort of a threshold utility for some data modes, let’s say credit scoring, for example, if you have some credit data, and you pre train a model, you sort of get to a point where additional data is not creating as much defensibility maybe talk a little bit about these these different aspects. Sure.
Leo Polovets 22:44
Yeah, it’s been a while since I read that article, but I remember being pretty, pretty interesting. And, you know, like, provided a lot of things to think about. I mean, maybe stepping back, I would say, I think modes only matter if you have some, like a business and a product worth defending. Right? So if you think about like moats, and like, literal castle sense of like building a moat, like you can put a moat around a trash pile. And like, you know, no one can steal your trash, but like nobody really wanted to. So it’s not, it’s not really valuable. And so I’d say like, on the topic of data moats, I think one area people get stuck sometimes as they pursue the data set, versus trying to figure out like, how to create more value and build something great. And I think the better approach is to work on building something really valuable to customers love, and then looking for opportunities to build like data moats, and other kinds of moats around that. And to Martin’s point at Andreessen there’s definitely a lot of nuance to data moats, right. So some of them asymptotes, like you said, maybe for credit scores, you know, maybe if I have like five years of your credit data, it’s not that much, you know, more useful than four years. And so, you know, even though like a company with five years of data has more data, maybe it doesn’t really help them do credit underwriting. But there’s a lot of there are a lot of problems where, for example, you have, you know, a lot of different use cases, or like, there’s a lot of nuance, and so, like search queries, or like that, right, where, you know, I forget the stat, but it was something like a few percent, or maybe even like 10, or 20%, of every of all queries on Google are brand new and never been seen before. And so that’s the kind of thing we’re like, the more data you have, like, the more queries you’ve seen, the more you have a good sense of what’s going on. And that’s the kind of thing where, you know, having five times more data actually probably does make your first query a lot better. Because you have results, great results, maybe for like 98% of search queries instead of 92%. And for user, that ends up being a big difference. So I think there are a lot of these questions about does the value of the data asymptote, you know, how big is the data set, right? Because maybe if it’s small, like let’s say, you have some proprietary piece of data in every country, but maybe somebody can just like get that data by, you know, doing like, $1,000 of research in every country. So that’s like, that’s not that hard to copy. But sometimes it is, that’s huge. And so it takes a lot of work to copy. So you’re looking at like, How hard is it to copy? How valuable is it like can you do interesting things with the data? Is the data fresh, or does it need constant refreshing like the more The data needs to stay fresh, the more valuable it is, you know, because if you’re looking at things that are like maybe, you know, you can be a year or two stale, that’s easier to copy that if you really need to be like up to the minute accurate, for example. So there’s a lot of nuance here, for sure. Yeah, for sure.
Erasmus Elsner 25:14
So let’s segue from this to discuss some of your investments at Susa ventures. And I want to kick this off with Robin Hood, which has been in the news over and over again, where you invested in their 3 million seed round. And this was notably before the infamous waiting list. So it was pre waiting list. And pre product, I put out a medium post recently, where I looked into how the back end of Robin Hood relies on sending orders to these high frequency traders like Citadel and Virtru. If I were asked What the Why now question around Robin Hood would have been that that we’ve seen this market structure move to the ecn and high frequency trading firms. Take us back to this point when you were pitched on on Robin Hood.
Leo Polovets 25:56
Yeah, I definitely feel like we’ve been you know, we were very fortunate to meet Vlad and baijiu because we’re on summer of 2013. And it was definitely very early. It was before you know, it was before the the waitlist, I would say like some of the things we found really compelling about them is like they’re really sharp. I think one of them actually worked in like Terence Taos lab in UCLA who’s like a Fields Medal mathematician like just like really, really smart guys, both of them, they had, you know, what people often call founder market fit, which is they had some experience in this space before. So they hadn’t built a brokerage before. But they had built infrastructure for high frequency trading firms previously. So they really understood like, here’s how trade execution works. Here’s how to make it fast and cheap. And so I think on the technical side, and sort of like understanding the components of the the back end of the business, they were really knowledgeable. And I think what really convinced some opportunity is, you know, I think first it did feel like the world is shifting to mobile more and more. This is 2013. So I think that, you know, in some ways largely shifted from five years ago, but there’s still a lot more to go, like Uber I think was just starting to take off. And they’re they’re starting to be more and more of these kind of like mobile first apps that were really interesting. And it didn’t feel like brokerages like traditional brokerages hadn’t provided like a good UX on mobile. And I think the other thing that was really interesting is when you look at like the the financial filings of like ETrade and Schwab and all of those companies, they you know, back six, seven years ago, they charged high commissions, like I think Schwab was charging 20 or $30 for each trade each way. And, and I think as a consumer, it’s easy to think like, oh, like these are high fees, you know, the cost of trades are probably pretty low, this must be how they make the revenue. But if you look at their income statements, that was often like 20 30% of the revenue, and a lot of the other revenue is based on assets under management. So you know, maybe things like margin interest, right? Like if you’re borrowing a margin, and you’re paying 5% interest on, you know, a lot of your balance that ends up actually dwarfing like the Commission’s most of the time. And so we saw that in like the Robin Hood founders pointed out that there’s real opportunity here where instead of making you know, the same type of revenue profile as the traditional brokerages, you could essentially give up the Commission’s piece and still make 70 or 80 cents on the dollar. But now you have like a really awesome customer acquisition channel. Because you have a mobile app, it’s free, you can trade for free, whereas like everything else costs 10 or $20 of trade. And that’s like, you know, free is so much better than than $20. And so I think that was the secret to like their their early success and their continued success, which is, you know, these companies like e trade will pay hundreds of dollars for new user, because it takes a lot of marketing to convince somebody like, Hey, you should pay me $10 you know, per per trade instead of paying somebody else, Paul dollars a trade. But when you’re when your offers free, and the UX is really good, and I think like people really like the brand, the customer acquisition is essentially the cost less. And so that’s that’s been like the key to their growth. And so they managed to accumulate, I think over like 10 million accounts now over seven years. And that’s actually more than E trade at this point, which is pretty exciting.
Erasmus Elsner 28:56
Yeah, it’s a super impressive story. And and let’s move on to to another investment of yours, scalar. And I remember you put out this this post on the coding VC that they were originally hired for doing technical due diligence at Sousa. And in this in this blog post, you said that basically, there’s no point of doing technical due diligence. And so scalar is a unified observability and log management platform, which sounds super technical. And I want to push you whether whether or not your technical background played a major role in making this investment and being on the board of this of this company.
Leo Polovets 29:35
Yeah, so presumably, I’ll tackle the technical due diligence piece first, I would say, this is an interesting and surprising lesson for me when I started because there aren’t a lot of software engineers in VC. Like there’s some but not that many. And so I partners and I really believe that, you know, me being on the team would be useful for you know, us being able to really look at the tech side of companies more and really like evaluate them on their technical merits and within a few months, I think We sort of figured out that that was a broken thesis, essentially, you know, first, I think seed rounds move really quickly these days. So there’s actually, there’s often not an opportunity to, you know, meet with the founders, and then also meet with, like their engineering team for a few hours, because things are moving fast. And also, you know, if other firms are not asking for that level of like engagement, and they’ll write a check after a meeting or two, it’s hard to say like, well write a check after a meeting or two plus also taking a few hours of your engineering teams time. So that was, that was one aspect, I think the other aspect of tech due diligence was also like, in the early days, for seed stage companies, the code is often not designed to be like the best code, it’s more like what’s the fastest thing you could build just to get a product to market. And so because of that, I think it’s, it’s sort of unfair to judge like the merits of the code, because of that, right? It’s sort of like if somebody gives you a rough draft, just to see if you like the plot, you don’t want to like, you know, really evaluate on like grammar and spelling you really looking more at the plot. And so I think, I think we realize is like the tech side for most businesses was, you know, sort of secondary to whether like, does this feel like the right idea, the right team, the right approach. And I’d even add that in retrospect, over six, seven years, like very few other companies I’ve worked with have struggled to, to build out the technical side, and like build the product. And where they really struggled is like sales or, you know, finding the right product to build or recruiting or things like that. So netscaler specifically, this is one of the few companies right, I do think my tech background did help. So what they do is they do observability, and especially log management. And so what happens is, you know, when an engineer writes code, and it’s up in the cloud, and it’s sitting on a bunch of servers, and it gets run, when, let’s say, like, you visit a website, and it hits some servers, and like the server’s do something on the back end, those servers end up basically saving some log messages about what happened, you know, they’ll be like, oh, like Erasmus. logged in, it was, you know, 12:15pm, you click here, this happened, we like read this in the database. And that’s really useful for, you know, eventually, like, let’s say you have a problem and like the website crashes for you, the engineers figure out what happened. And so they look at these log messages, maybe they look at some metrics about the servers to see if like they were under load or something special happened. There’s tools for that, like Sumo logic and Splunk. And I think data dog just went public that’s in that space that’s doing really well. And what’s interesting is these tools are generally siloed. So maybe you have like metrics in one place, you have the server logs, another place, you have other types of tools in different areas, and like none of them are really connected. And this is something I’d seen at Google, where there are a bunch of when I worked at Google, there were a bunch of great developer tools, we have to check like, you know, five or six different systems really figure out like what’s going on with my server? Like, why is Erasmus having a problem on the checkout page, that kind of thing. And so I saw that these tools really siloed. And then there were these, these tools coming out that were pretty good, but they’re definitely on the slow side. And I think they just like didn’t scale super well, for a world that was moving into like AWS in the cloud. A lot of these, I think were actually like on prem installations where like, you buy the servers, you install the tool, like you buy a license. So when I met the founder of scalar, I thought his approach is really interesting. He actually come out of Google, he had seen the same tools. He was like a world class engineer, he had built this program, called rightly, with a few co founders that eventually Google acquired and turn into Google Docs. So it essentially built like, you know, the world’s most successful like collaborative editor. And then he was a Google, he’s working a lot on the infrastructure. He’s like a really great algorithms engineer. And so he seemed like the right person to build a really good log management platform, which is essentially a platform that stores logs, and lets you search them really quickly. And then because this was built in the area, in the era of post AWS, instead of pre the search ended up being like 10 to 100 times faster than existing tools. And that was the thing that like really sealed the deal for us. Because as an engineer, you know, if like, if I’m trying to debug something, I do a search query where I’m like, Okay, what happened on this server for this user, and it takes like three minutes to get a result, that’s a really slow process. And maybe I find out like, oh, the search query is a little off. Like, let me try it again. And it’s just like, it’s really slow. I tend to like hate the tools, I don’t use them that much. But with scalar, when it’s, you know, 100 times faster, and it takes a second instead of three minutes. That’s just like such a game changer for engineers. And so that was that was the product we invested behind about, I think six years ago, I worked with the founder, Steve for a while he he found a CEO, with more like a business and sales background to take over the business side about a year ago. She’s been really awesome. And the company has just been like growing really well for about, you know, for the last five, six years. And they have a bunch of huge customers. And I think their approach is like really interesting and really technical. And because of the tech team and how the technology has shifted to the cloud. It was like the right time for this, this company to get started.
Erasmus Elsner 34:35
Yeah, super interesting. And the company hasn’t raised that much money given given the traction. I think they raised I think 26 million. They had a CSA, but relatively capital efficient. So let’s move on to my absolutely favorite part of this session, which is diving into some of your previous tweets. I’m a big follower of yours for for many years now. I’ve learned so much about not just startups and venture I meant tech but also about life in general. And so I want to start with with a more general tweet of yours, which I absolutely loved. And it’s about reputation. You tweeted there, and I want to read it out, I’m still in the early stages of building a reputation. But here’s an algorithm that I think is working. First of all, meet lots of people. Secondly, be helpful to as many as possible. Third, don’t screw anyone over fourth, play the long game, and don’t be transactional. And fifth, repeat 124 forever. So you have the loop there. And I like this engineering, mixed with with, with life advice. And then related to that, you talked about external validation on Harris stabbings, 20, minute VC, you mentioned there that a lot of people in the valley over index on on warm intros, and then you’re one of these fewer investors who will respond to cold emails and who are open to that kind of deal flow. And I think it’s, it’s related to this building a reputation of being open, talk to us a little bit about this refreshing and unorthodox social protocol that you’re following.
Leo Polovets 36:01
So I think venture investing is really interesting, because in traditional investing, maybe you make 100 investments, and, you know, on average, 50 go up and 50 go down. But if you’re good, maybe like 55 go up, and you know, 45 go down, and you’re an investor, with venture, like, you get all of your returns from one or two investments. So you might make 100 investments, and there’s like, two that are, you know, 80% of your returns. And I found that, you know, kind of working with people and trying to help people is the same where there’s a lot of value, almost like serendipity. And just like the law of numbers, where are the law of large numbers where, you know, maybe 50 people asked you for advice or a favor or something to help with and you help them and maybe like, 40 of them you never talked to again, and you know, five or six, maybe they ask you another question, maybe the like, do a small favor for you in a year. But there will be like one or two or three where you know, almost feels life changing or like, oh, the senator, being a founder I worked with for many years, or, you know, or this person like really helped me through, like, think through some challenge at work. And so I think there is a lot of value to just interacting with a lot of people and being, you know, being positive or like, you don’t really expect anything in return from any person. But sort of like, the more seeds you plant, like, the more good things will happen to you over time. And so I really believe in that, I think a lot of, you know, whatever success I’ve had, has come through that to a large extent. And then in terms of warm intros, I think, for me, this is just sort of like a first principles thought, which is, you know, with warm intro is you’re basically trying to, like, you’re only talking to people that have an in or like have have established themselves, but a lot of people that are really successful, like, at some point, they started out from like, from scratch, right? And so, you know, maybe like the CEO of like Netflix or Spotify or or, you know, or Apple or something, you know, today they can get like ormond train anybody, but maybe like, just before they went to like Spotify, or Netflix or Apple, like maybe they weren’t that well known. And it was starting to be a shame of like, you know, Steve Jobs emailed you and you’re like, hey, I need a cold intro. Like, I don’t know, if you’re, like really that special. And so I think there’s a lot of value to just like, looking at people more on their merits, or their potential, or, you know, like, Are their ideas. And, you know, a lot of times like, those people go nowhere, but a lot of times, they go somewhere, or they go really far. And I think it’s a lot more, it’s a lot more rewarding to like, help somebody with potential, you know, get to the next level. And then in the future, like, you know, maybe you can’t get an intro to them, because like, I couldn’t get an intro to like Scott cook today or something, because he’s really busy. But if I met him, you know, 20 years ago, and, you know, or maybe, maybe not him, but maybe somebody that’s like a little bit more my age, like helped him out when you know, when we were 25. Like, that’s a relationship that is really hard to build, you know, when we’re 40. And, you know, the other person’s a lot more successful. So I really, like they do just like meeting people earlier, trying to help them out. And then you know, just seeing what happens. And in the worst case, like, it feels good to help people. So
Erasmus Elsner 38:42
yeah, absolutely love that. And I found this YouTube clip of yours back from your days at factual when you were at a at a conference and they’re in the interview, you say, this is the first conference you have ever attended. And that was, I think, in 2010, or so. So you were not always a big networker. And then moving on to a more product, focused tweet of yours that I really loved is where you tweet my experience. So far, most companies that try to build platforms end up evolving into tools for their early user base. Some companies that try to build tools for a specific user base, eventually evolved into platforms. And to build a platform, start with a tool for a set of users and then generalize. And this reminded me really, Chris Dixon, come for the tools stay for the network host. Talk to us a little bit about this idea of coming for the tools and staying for the network.
Leo Polovets 39:53
Yeah, I mean, I would say a lot of it comes down to like, it’s really hard to to self to people when they don’t realize they need them. And so a lot of times, like platforms are a very abstract concept, right? where, you know, for example, maybe you’re recording this podcast, you have specific problems, like how do I record stuff? How do I get transcripts? And, and so if I, if I came to you and said, Hey, I have like a really great transcription tool, or like, you know, a podcast hosting tool be like, Oh, that’s great. Like, I’ve been looking for that. I think if I come to you and say, like, Hey, I have a, you know, an audio platform, you’re like, Okay, like, What is that, like, I’m not looking for an audio platform, I’m looking for, you know, a hosting tool. And so I think what I’ve seen is like these companies that started as platforms, they have a big vision, they go pitch it to, like, 50 companies, or 100 companies. And most of the companies are like, well, like, I don’t really know about, you know, the platform, but like, Can you help me do this? Like, can you help me, you know, transcribe my podcast. And so what happens is that company starts at a platform, and then they talk to 100 customers, and they’re like, well, there’s a lot of pull for, like, you know, transcriptions, like maybe we’ll just do podcast transcription. So they end up starting more general, and then quickly, like moving more into a tool. And the flip side, I think a lot of times when you do end up on a tool, like let’s say, you know, transcriptions over time, if you’re really successful, you can start building adjacent things, does anybody have papers, we do transcriptions. And then maybe afterwards, like, well, like, people want to search the transcripts. And now we have, like, you know, searching built in, and then maybe next, it’s like, Hey, now that you, you know, we see like, you can search transcripts and people, we see what people are searching for what they click on, now, we give you like a recommendation engine. And then pretty soon you’re like, Okay, now we have like, a really comprehensive podcast or platform with all these services. And because you started in like a few concrete areas, you get, you get a lot of adoption, and then it’s like, it really takes off and like it’s hard to, you know, for others to copy you. But it’s really hard to start with that, like platform general view off the bat. And that’s kind of what that tweet was about to tie it. You know, I think it’s a really good observation about Chris Dixon’s post, which is that a lot of times like people, you know, for all of these social networks like Pinterest, when you first join, when it’s really early days during a lot of users there. And so you can’t really hook people with like, Hey, you should join to be part of a network because like, there’s no value in the network. And so we’re trying to do is you give them something concrete, like, let’s say, a tool to say like to pin all of the images that they’re interested in, and to categorize them. And so that’s very much like a single player mode, where even if there’s no one on the platform, it’s useful to a bunch of people. And so you get people in on this like, very specific tool. But then once they’re in, you’re starting to build this network around them, which is, you know, maybe a little bit analogous to building a platform around a tool, or like that usefulness just expands over time.
Erasmus Elsner 42:32
So the last thing I want to talk about is related to pricing, and how pricing tells a story about your product, and you say pricing tells a story, low prices, the product isn’t that valuable, high prices, this is a premium product freemium, you need time to see value, pricing by number of seats, every user gets value pricing by team, the value is for the team, not the users pricing by the transaction, you get value from every transaction. So what does the price say about you talk to us a little bit about about this tweet, and give us some personal flavor on how this has played out in some of your portfolio companies.
Leo Polovets 43:08
I think pricing is really interesting. First of all, because it’s really high leverage, like you can, you essentially can, you know, not change your product, not change your team, not change your sales strategy, but just come up with better pricing, and maybe like your revenue goes up 20% or 40%, you know, overnight. So I think it’s a really interesting area to like, think about and research and learn about as a founder, and as an investor, the way companies price things really reflects on how customers perceive them. Right? Because a lot of times, like whatever the pricing mechanism is, the customer is thinking like, Okay, do I get value out of that, you know, kind of proportional the price, right? And so, if someone says like, hey, it’s, you know, let’s say like anchor the podcasting platform, if they say it’s, you know, $1,000 per podcast, maybe you’re like, you’re thinking like, Okay, do I get $1,000 of value per podcast, right? And you know, you’re doing the math and maybe doing maybe you don’t, but maybe different ways, like, Oh, it’s, you know, a minute for like, $1 per minute of audio, or maybe it’s like 50 bucks a month, even if you do like 50 podcasts or something, right? And so all of these things are framed in very different ways. where, you know, for example, if they charge like, $1 per minute, you’re gonna be thinking like, Okay, do I get additional value for every minute because like, if I don’t, I don’t really want to pay that. Or if the, you know, if they charge you like, per user, maybe if you’re like a heavy podcaster it’s really worth it. Because, you know, if you’re doing like 10 podcasts a month and paying 100 bucks, it makes sense that if you’re doing one a month that maybe it doesn’t, you know, so I think customers always like thinking about it, maybe implicitly, maybe explicitly of whether this pricing aligns with like how they think about the value of the product. And, and in that vein, like when the, when a company says, like, Hey, we priced by the seat, they’re basically saying, like, you’re going to get value by the seat. Like it’s per user. It’s not per transaction, it’s not per month or length of time or something else. And so as As the company as the product maker, like you really want to make sure that aligns, right. So if your values by the seat like don’t charge per transaction, or if it’s like by transaction, you know, don’t don’t charge by like team or something, you just want to make sure it aligns. Because otherwise, you know, customers end up having friction, right? Because they don’t think about your product the way you want them to. And like maybe like a really dumb analogy is, you know, Uber prices like per mile. And there’s some surge pricing, but like, basically a prices per mile. If they said, like, Hey, we’re gonna price by like the number of gallons of gas the driver uses, like, nobody really knows how to think about that, right? They’re like, I don’t think about whether you know, this trip is half a gallon or a gallon, I just know, it’s like, it’s six miles, I have other alternatives that I know, like, for six miles cost this much. How do you compare for that. So you just want to make sure that your story that you tell with your prices really aligns with what the customer wants.
Erasmus Elsner 45:48
So we’ve had a lot of investors and builders in the open core vertical on this show. And I think in the open core, or in the open source, commercial open source segment, there’s so much room for for maneuver in terms of pricing that there, it’s super interesting to think about, you know, how do you price it such that the value is really derived for the enterprise only, and basically fee for for the developer ecosystem, that your tweet really resonated with me in that respect?
Leo Polovets 46:18
Yeah, it’s actually so open core is interesting. Because if you you know, so it’s like, basically products that have like an open source core that people can use for free, right? Then you can think about the pricing there sort of says, like, here’s how you’re pitching your product, which is, you know, let’s say everything is free, but you charge for like services and support. I think the messaging there is like, Hey, this is hard to use, you’re going to need some support, right? Or maybe like, if you charge for hosting, I might be like, hey, this works great, but like hosting, it’s a pain in the butt. So like, you know, you’re gonna want to pay us for that. But the user is sort of looking at that. And like, they’re sort of thing like, Okay, this will be hard to use, or it’ll be hard to host or, like, you know, the basic features are free, but have to pay for advanced ones. So maybe like, the basic features are like not going to be as useful as I hope. And so so whatever, however you set those prices, and like what you’re charging for that ends up, you know, really communicating something the user implicitly Yeah, absolutely.
Erasmus Elsner 47:06
So I want to wrap this session up. So where else can people find out more about you?
Leo Polovets 47:13
I would say Twitter is the best place I’d probably spend way too much time there. So I’m I’ll pull events on Twitter, it’s LP o l o v ETS. I’m also email as well. I’m Leo at Susa ventures calm. Sue says SEO se, but yeah, I’m pretty accessible online. So you know, always excited to chat with people working interesting things. I had a blog where, you know, when I started my venture career, I had a lot of free time. So I was doing like a post every week and then became every like, week or two and then every two or three and I think about two years ago, it got down to more like every couple of months. And then I got so you know, I had so much work that piled out that I really fell off the wagon. I have a few drafts. I’ve been working on my goals to like get back to blogging this year. And you know, at least do like like maybe a post a quarter or something like that.
Erasmus Elsner 48:00
We’re really happy to have you on the VC Twitter as active as you are. So thank you so much, Leo for taking the time.
Leo Polovets 48:06
Yeah, it was great to chat. I’m really really happy you invited me.