E46: Vinny Pujji on Leveraging 3rd Order Analysis to Pick Winners for Left Lane Capital

0:02Welcome back to Turpentine VC, a podcast where we discuss the art and science of building successful venture firms, VC to VC. In today's episode, I sit down with Vinny Pooji, the managing partner of Left Lane Capital. Up ahead, we discuss Left Lane's unique positioning and how they can identify non-obvious companies to invest in. We cover their in-depth analysis process, as well as Left Lane's approach to fund construction and team building. Let's dive in. Vinny, welcome to the podcast. Thank you for being a part of it. Thanks for having me, man. I'm excited. So, Vinny, let's first dive into Left Lane.

0:37Talk about how left lane positions itself in the market. There's a lot of funds out there. You guys are doing something interesting. How did you think about where you wanted to play in the market and where is there opportunity? Are there other funds? Exactly. I say that half in jest, but half in a serious way. I think it's really odd and frankly, a bit backwards when you see funds, look at who's in the market and just think about how to pitch to LPs probably more than anything, and then how they can position to be different. And then last of all, what they're good at actually doing. we sort of started with stumbling into something which is the phenomenon of internet companies rather than enterprise companies and if we went back in time 30 35 years ago the tech investing industry was a real industry but it was investing in a huge variety of stuff and you saw a lot more of the semiconductor type of investors than the enterprise software investors and then 20 years ago, you started seeing more and more enterprise software investors.

1:48And 10, 15 years ago, it was hard to find anyone who wasn't just doubling and tripling down on enterprise software. And our group, our partnership was at Insight Partners. And they're some of the best in the business in enterprise software. And I had done a bunch of enterprise software deals, including some more private equity style deals. But we saw a new wave of companies popping up, just coincidentally, where they were oftentimes being built on this thing. And this was a pretty, pretty new thing 10 years ago. And at the same time, we saw even more traditional application software businesses being built in a different way, where it was a lot of what most people would call product led growth, but it was marketing and product fueled growth rather than boiler room enterprise software, top-down, whatever you want to call it.

2:38And that required a different type of thinking and a different type of investor. And I have a ton of respect for firms like Vista, but that Vista playbook of, hey, here's where we're going to cut, here's how we're going to scale sales. It was not as relevant to this type of company. And so not out of some genius or strategy decision, we stumbled into this and we started helping these companies. And after a few years of doing it while at Insight, those founders started coming back to us saying, hey, you know, nobody actually is running this type of analysis or making these recommendations. And that's when we sort of knew we had both product market fit, but also something that we deeply cared about.

3:19And I think it's very odd when people decide to start a firm when they don't have a moment like that. Say more about the type of analysis or type of recommendations that you were doing that's unique? Because don't other great, you know, the A16Cs, the IVPs, the Thrives, what are they not doing that you guys are doing? It's a great question. Listen, we don't have any crazy ego in this. We don't think that we are smarter and better and more capable than other firms. We do think that we've been specializing for about a decade in a certain type of company. And I think specialization, like everything in life, compounds.

3:57And so when you've been specializing for a decade, we did 20 % more correct, better, whatever analysis for every year for 10 years. And now we are sort of in a different league in the type of analysis we do. And I'll give you an example. I'll split it into first order, second order, and third order analysis. I think every firm with a pulse hopefully is doing first order analysis. That means looking at an income statement, taking what the company gives you and saying, hey, is this a good business? Is it healthy? Is it growing fast? Whatever your mandate might be. Now, second order analysis is what most people would call unit economic analysis.

4:34And hopefully, if you're doing that level of analysis, you're also doing something to verify that the data is correct. And when I say that, I mean actually collecting some, let's say a raw transaction file. And you're building from that raw transaction file into a unit economic analysis where you say, hey, how much are you spending to acquire a customer? At what point are you paying back or breaking even on that spend? And how much life after payback do you have? And that'll tell you, you know, sort of green light, red light, if you can keep pushing or if you sort of need to back off to maintain a healthy business.

5:14And I'd say that almost the entirety of the top quartile investors are doing that. Now, a lot of folks that are capital cowboys or they're running around doing SPVs or their family offices without a ton of specialization, they're not actually doing that analysis. they might be taking the company's LTV CAC analysis, but they're not doing that analysis from scratch. But I think people have learned how to do that. And, you know, maybe it's not best split into quartiles, but I know a lot of groups that do that type of work. Now, the third order analysis, this is where we either create data that others don't have, or we ask for data that others don't know how to use.

5:53And an example of that is we will look at usage data. And usage data might be 50 or 500 million rows of data. Let's say I'm a mobile app company. Every time my users have opened my email, opened the app, what did they click on? How long was the session, et cetera? And we will actually crunch and analyze that usage data internally, and then find patterns of some significance within that data. And it's not ever one size fits all. Trust me, we've tried to automate it. But there's a lot of nuance in that, Because for one app, it might be the time that I open the app at that becomes the most predictive factor of if I'm going to retain or not.

6:31For another app, it's just what I click on in my onboarding survey that's going to be the most important predictor of am I going to retain or not. And so it's different company to company, but we always find fascinating things. If you look at a company like Calm, it might be, hey, if people are using you for a sleep meditation, they're going to retain better than if they're using you for a morning meditation. And for a company like Truebill, it might be, hey, if users are opting in to more than three bank connections, then they're going to retain way higher than people who just do one bank connection.

6:59And then that can help inform the company's roadmap. But most importantly for our underwriting, it's actually helping us see around that curve. Like I could give you a bunch of data. You could do a bunch of analysis on it. But who knows if it's correct? Who knows if it's meaningful? We've done it enough times with a similar type of company that we know it's correct. And the other type of creating data is we'll actually run surveys, both third party surveys against potential customers and first party surveys against your customers, where we have the customer ID. And then we'll say, here's what this specific customer does.

7:32By the way, here's how often they open the app. Here's what they're using it for. And we're cutting this data in such interesting ways that we can actually help companies target the right customers and lean into the right types of growth. Rather than as you're growing faster and faster, what you usually do as a company is you just blindly broaden to wider and wider concentric circles of the market. And what do you know? The cost to acquire keeps going up. The retention keeps going down. And eventually you've acquired a bunch of customers at too high of a price and you get into a dangerous territory.

8:04So that's the goal of our analysis. And that's what we've gotten the confidence to do over the past decade. That's a good explanation. Give us another example of a company you identified earlier than other investors via your methods. Like you identified this company was really working and it wasn't obvious. Oh, gosh. Probably half of our investments would fall under that. And as far as identifying a company, there's two completely sets of what we do. One of them, what I was just describing is on the analysis of the company and making the right decision. The other side is how we find the company.

8:39So we speak with, I don't know, seven or eight thousand companies a year. And we have a very lean forward culture. And we try to get as close to 100 percent market coverage as we can. We spend millions of dollars on data and infrastructure to help automatically source these companies. But we are still a very human centric model. So first of all, we have to find the company before we get the opportunity to even analyze it. And we have a company, an investment that we just closed in India called Astro Talk. Astro Talk is an extremely unique business. They bootstrap their business to over 100 million in revenue, extremely profitable.

9:16And I love to see things like that because what they did is almost scoffed at by the typical tech coastal elite. This is a managed marketplace for astrologers. And a lot of people don't know this, but there's a huge percent of the global population that before they get on a plane, before they change jobs, before they enroll in school, before they break up with someone, before they date someone, before they marry someone, they consult an astrologer. And if you look at the actual content of what they're doing, they're really just sort of talking to someone. Right. And at the very base level, it's kind of like therapy is how I would put it.

9:56I think a lot of investors, first of all, overlooked the company. It was so big that people absolutely knew that the company existed. And at the same time, when we see investors just drive right back past something and say, hey, I'm interested in companies that will help me live to a thousand and help us all be robots, we usually put the car in park and say, well, hold on, we're still humans. And this is a really important thing for a lot of the world's population. Let's spend more time with it. And in that case, what we spent time is, is we looked through the chat logs. And of course, this is not me reading every single chat log, but this means that we took tons and tons of data to make sure, one, there was nothing salacious or nefarious or, you know, stuff like that and figure out the incident rate and how good the company was at policing that because that's the first thing we want to check on.

10:51But after that, we said, again, what makes good customers? How long of sessions? How many sessions? Where did you acquire that customer? And potentially even the content of that session, what makes for a good customer versus a bad customer? And I think what we saw in the data is that people have surprisingly recurring needs and they almost have a team of astrologers that they want to go to, not just an individual, which gives the platform some real defensibility where we actually surprisingly saw minimal leakage. And that's a super unique example that only was relevant for this company, but it gave us the confidence to say, OK, these are actually really stable annuity streams.

11:35This is clear behavior being formed. And since we closed that investment, it's continued to perform every single month, getting more and more customers and keeping a high retention rate. Yeah, that's a good example. Talk about what types of companies are in your sweet spot versus what types of companies you say are best for some other firm. Like we don't really focus on that here. Sure. I'll give you the boilerplate definition and then we can iterate from there. So Leftlane exists to invest in early growth companies and we have a global mandate. Now, if we zoom in and see what does that actually look like, it's usually series A and B companies.

12:11our checks are ranging anywhere from three, four million all the way up to 60, 70 million on the very high end. And we're investing in real categories of spend. So it's oftentimes companies that are taking, whether it's healthcare or education or financial services or insurance, something that's a very core, oftentimes multi-trillion dollar category, and they are driving digital adoption there. We're usually not investing in categories where digital adoption is 90 % and it's a completely B2B market and relatively penetrated. And this is like 20 % better than the next thing. Now, when we look at geographically where we invested, it's about 60 % US, 25, 30 % Europe, 10, 15 % rest of the world.

12:59Say more about education and healthcare because there's a lot of dead bodies in those spaces. So how do you think about where in education in healthcare you're excited to invest? So listen, whether it's education, healthcare, financial services, or really anything else, we are investing in a customer relationship. So our philosophy is simple. When we see something that is high trust, high spend, and habitual, that's where we get excited. I think where people have had very high loss rates in these categories is when one of those three things is not the case. If I paid 10 bucks for something and I used it once, that's not a left lane investment, right?

13:39This needs to be habit forming, extremely high trust, proven annuity streams to be a good left lane investment. And then we beat that up. And when I say beat that up, I mean, hey, if you lose your job, are you cutting this? One of our team's old investments at Insight was a company called The Farmer's Dog. The Farmer's Dog scared me personally. I didn't grow up with dogs. And we looked at this company where people were spending, give or take,$2 ,000 a year on their dog food. And I was like, well, hold on, guys. This is clearly just for really rich people. And so we ran our survey. We did our work.

14:13And we were shocked. I mean, if you look at the curve of just income in the US, this was barely offset from that curve. And then we got into the qualitative side. Basically, people said, hey, my dog's my kid. And even if I lose my job, I'm not going to screw with my kid's health or you know, their stomach and, and wrist. I'll eat McDonald's myself. But I'm going to feed my dog the same food, no chance am I messing with their food because something going on in my life. Now, that's the type of thing where you go, okay, that's pretty interesting. I thought that this might be a lower quality business, or I thought that it might be for a smaller audience.

14:50But what the survey data told me is, this is a really good annuity stream. And it is a rock solid retention curve. And that's proven to be the case at scale now. Hey, we'll continue our interview in a moment after a word from our sponsors. Today, I want to make a bit of a personal appeal to anyone working on a SaaS app or website. If you spend any time on the internet, you probably have interacted with chatbots in the bottom right corner of sites. Most are really annoying. AI is making them better. But still, I often just get really useless generic answers out of these and end up just wanting to talk to a real human.

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17:11What are examples of education or healthcare businesses that you've invested in or might invest in? One example is we have a company here in New York City called Talkiatry in the healthcare space. And Talkiatry aims to solve a very simple problem. We have, well, I think we have a few epidemics going on in the world in the United States, but one of them is a mental health epidemic. And the shame is there's a shortage of healthcare professionals to serve this problem. And so what happens, whether you're in Los Angeles, New York City, or anywhere in between, if you're a psychologist, the second you open your doors, good news for you, you're going to have a pretty full book of business in no time.

17:54But it is in what I, the reason why I say that is just to give an example of how this is a supply constrained market. And every market's different, but in this case, it is certainly supply constrained. And talkiatry said, hey, these folks, they love treating patients. They don't really like the business side of what they do, can we bring them onto our team, handle all the insurance side, basically the business building side of this, and have them instead be our own sort of in-network providers for people to give affordable, oftentimes in-network care to people for their mental health issues? And the answer was yes.

18:30And so now they have hundreds of psychologists and even therapists on staff. And that's a very high trust, very high retention relationship. And, you know, the business just raised another round of capital, but we backed them about, I don't know, three or so years ago. And that was a perfect left lane investment because we had a lot of littles to look at. We had, you know, sort of a managed marketplace dynamic and we had very clear annuity streams and that sort of held up at scale. And what's your what's an example of an education business that fits the criteria that you mentioned, whether or not it's in your portfolio, an example of an education business that fits that the three criteria you mentioned?

19:09Oh, I think there are a ton of businesses in the education world that fit our criteria. Now, I split education into typically two buckets. There's the L &D type education, right? So that's typically for adults to upskill themselves. And then there's things that fall under K through 12 or your college education. And we've invested in both. The first investment that our team broadly made in that world was a company called Udemy. And I think we learned a lot through that experience. And Udemy has both a B2C and a B2B business. So I think we've learned interesting pros and cons. The tough thing, because you referenced that it's tough to invest in ed tech, the tough thing about education is depending on what society you're in, people sort of have beliefs around education, like it should be free or provided by the state, or you don't need past a certain level.

20:04And I'll give you some examples. In India, it's typically been a great market for for-profit education because societal importance put on education, really high. Quality of public education varies based on where you are, but relatively lower. And that gap is what people are willing to spend. And so households are willing to spend a huge percent of their income on education. If you look at the US, still quite a good market, but that gap is a little bit smaller. And if you look at, depending on the European country, it might be a little bit smaller. And so we have companies in our portfolio, Actually, the first investment we made out of Fund One is a company called GoStudent.

20:43And with GoStudent, they said, you know what? We can build a really big business in Europe. We have no formidable competitors and we're going to go build. And they've now built a multi-hundred million dollar business just in Europe where they basically said, hey, we are going to take this marketplace model, this managed marketplace model. We're going to sell subscriptions on the demand side. And on the supply side, we're going to take people who maybe wouldn't have otherwise been able to tutor, and we're going to make it really convenient for them. And oh, by the way, on the demand side, we're going to make it that much cheaper, that much more convenient.

21:18And, you know, we always do these surveys. When we did our survey on GoStudent, we found that the vast majority of customers had never done for-profit tutoring before. But this was just cheap enough, convenient enough that they did it. When you see a marketplace business that is bringing people into the market that weren't previously in the market, that's where Uber comes into play. That's where Airbnb comes into play. This is something that through price and convenience disruption or accessibility disruption is actually increasing the size of the market. So that's one example of many in ed tech where we've gotten super excited because we see something that's just better.

21:56Most of what we see in ed tech is frankly not interesting because students have wildly high adoption and fast adoption rates of technology and they just churn through it. So we see a lot of interesting ed tech companies grow like this. And then just like that next new social media thing that you only log into for five minutes a day, it just drops off a cliff because summer, it freezes, everybody forgets about it, new school year, new product is out. And so there are a lot of things that fall under that bucket that have looked interesting. And don't get me wrong, we've missed a lot of things in that world, but that's not exactly where we feel comfortable.

22:36Yeah, that makes sense. Let's zoom back out to fund construction and how you think about fund construction at Left Lane. So you mentioned you get in at series A or B. Why there instead of C or D? Or how many companies do you have per fund at left lane? Talk more broadly about the fund portfolio construction. So we invest in about 15 companies a year, give or take. And so what the funnel looks like is speak with seven, 8 ,000 companies, do a deep dive on 300 companies, put down 17 term sheets, ultimately invest in and win 15 of those deals. That's basically what the funnel looks like. we think about it based on time rather than based on fun because our team's resources aren't really constrained by fun it's just based on like hey how many new investments are coming in and then over time how many positions are we exiting or are we stepping back from whatever it might be and ideally those sort of reach a point of harmony where they're roughly one-to-one and and if not we'll make sure that we're staffed accordingly so that, you know, none of us is on like 20 boards or something crazy like that.

23:49Now, what we think is something really interesting for our investors, which is an extremely high amount of diversity in the industries that we play in. So I think something we saw over the past few years is a steep correction in enterprise software markets, where the vast majority of enterprise software companies were suddenly hit with people cutting software budgets and pushing harder on price or slowing down on their growth and not needing the same amount of software. And I think it was fascinating for us to see because we didn't realize how sort of incestuous that industry was. So much of software is just sold to other software companies.

24:27And so when that little market takes a hit, it really takes a hit. Now, when we look at where we're investing, we're investing in everything from coffee companies to pet food companies across really all major buckets of spend. And so we feel that we are diversified across sectors. So that's the first thing that we very purposely make sure we are offering our investors. The second thing is that because we are early growth investors, we are still doing that growth underwriting that I was describing where we're getting in the weeds granular and opportunistically will position build in a lot of our portfolio companies.

25:03We basically want to go to the market and say, hey, we can offer you the best of both worlds. We can be your venture upside with your growth equity downside. And that's sort of how we were trained growing up at Insight Partners as well. And share more about team construction as you think about what is the right amount of partners or share more about how you think about, how do I architect a team to perform back the strategy? Yeah. Team I care tremendously about. I've always been and I will always be involved in our analyst recruiting. And we are unique in that we hire people junior and we have a promote from within culture.

25:42And we've I think as a result of that and the training and the care that we put into that team, we have had an incredibly high employee retention rate. And I hope that that continues to be the case for many years in the future. We have about a 40 person team. So it is definitely a lot bigger than our peer group. And we're split mostly across Brooklyn and London. Now, the goal of that team is coverage, right? So the majority of that team, 25 people or so, is on the investment team. And to a certain extent, we all have the same job, right? Go out there, hustle, find companies, evaluate companies, decide on investments, and win those deals.