Arjun Sethi of Tribe Capital on Data-Informed Investing
Hey, everybody. It's Eric torbert co-founder partner, Philip global, eight network driven venture firm, and this is metro stories a podcast covering topics. G tech business with world leading experts. Hey, everybody will consider episode interest worth. Here's a friend with very special guests are could issue Eric and thanks for having me. Are you are a thrill entrepreneur investor of founded messaging, awhile apps of partners of capo in your own firm. Tripod only talk a little bit about what you're building drive. What you set out to build in was the he's. If you think about, you know, a lot of people have asked he has an entrepreneur, why are you building a firm white deploying capital? And it goes back to what my founders ni- tribe of done for the past ten years. So we've built products from scratch in consumer in SAS invested in those categories. But when we did it it was at a time that I think it was fairly special. If you think about a post two thousand one you get into their up two thousand five is where companies were leveraging their data to make better decisions. So when one of the companies that people always remember is Zinger, obviously Facebook, which is they had these data science team and people that were assigned in parallel with product managers and engineers to make decisions and bespoke hypotheses around what was happening in their products. And in some cases, it's fairly behavior of behavioral. Oriented in some cases, it was paid acquisition customer acquisition, LTV, etc. And so in order to have done that you would build the right infrastructure. You would build the right set of teams you'd have the right set of software and infrastructure that maybe third party already he built internally, and then you would make ideally better decisions with that. And so we took a first principles approach to how would you do that in venture capital? And if you think about it what you're doing is you're delivering capital at the early stage where you have a more active role in having the companies being built. And so how do you build context while you could build context by having industry, knowledge or sector specificity as an individual or you can say, well, what does what are the all the common denominator denominators, you need in order to build a company, and how can you help companies step function? So what we did is that we felt we were the masters of product engineering and data science, and we would take the culmination of all. Of those three foundations and assess companies in that way, and we started that at our predecessor fund where a lot of credit goes to some of these frameworks that were built from my partner Jonathan at Facebook. And then he brought that when he came onto social capital where we had unlocked data for our company after we invested over time. We used our own softwares and tools to essentially ingest. The data store at continue to analyze it retrieve it as needed and get better and better at understanding our own companies and then providing that back to them. And then the next question you ask is will can you do that earlier and earlier in the life cycle of the company, and then can you do it earlier in earlier in the life cycle of when you meet them? And that's a century. What we set out to do. We started product ising learnings that we had on the data science side. And then we delivered it back to a company kind of we call the magic eight ball. It's something that's been continued to evolve over the last six years, but. We started it so long ago, and then we continue to use it across multiple companies multiple stages for better for worse. And then our frameworks get got better and better and better because the end number of companies that come onto our platform or they meet with us. We are able to derive better results for them and interpretations of how their companies performing. And so that really started out with Jonathan writing set of articles that were about growth accounting in a quantitative way to measure product market fit. And I think what you've seen a lot in the valley is everyone believes they have product market fit on the founder side, and everyone who's an investor qualitatively believes they know how to assess product market fit. And so what we wanted to do is take a first principles building a product from scratch approach to how do we deliver what it means to have product market fit? So the line we use when we meet companies are we are investing in one outcomes and in order to do that we take a quantitative based approach to product market fit. And we deliver that by our magic eight ball over and over again that helps you unlock the data that you have. So we can identify product market, and we can help you amplify. We're your one is back on. It's what it really means. Is that you have a monopolistic tendencies in certain sectors. And of one company is essentially a company that's category defining or it could be the market itself, and you're able to slowly and slowly in some ways improve the category, which are in because you can either take fragmented services and make into automated software or you have a network effect for the company that you have and you're able to go into chasing. Territories at high velocity anyone companies really to us was a term that stemmed from our days in social gaming, social gaming was one of the companies that we're fighting for it. And they we all believe could try to get to end of one outcomes by having a network effect or a conglomerate of customers in our in our products where we can move them from adjacent product to adjacent product, then workout didn't work out for thing. I didn't work out for us. But we've got far enough where we were one of companies. And so our goal was to help identify companies get to have one outcomes versus a one. Event company. Now does that mean, we don't invest in companies? No, it just means knowing where you are in the ecosystem knowing how to think about building your team's your Salesforce or product just having a guide map about a perform. So there are all there. So. So. Arcade versa. Yeah. I would actually say Uber in lift are now comes because there's just two of them in the United States. But if I was to take a global perspective than you could say there's lots of competitors all over the world and it's hard to compete outside your geography of one outcome company is slack one outcome company. Facebook. One outcome company for us companies like Carter where you see very clear signs of network effect. Very clear signs of Jason. Territories that you can go to and what I mean by very clear signs that network effect is that you can quantitatively measure that this company is eating everyone else in its way. So that's that's for us is special circumstances. When we feel like there's one company. Who tells the story and? I mean, there's so many narratives about slack. When we first invested in slack through our partner, Ted and Kaplan, he had known the team through a company called cozy that they were both on the board of together and obviously slack had gone through a pivot. They were previously a game company, and they had used some of these tools and communication paradigm to communicate with not just each other. But a way in which they thought would be the right way to build communication, and so the early companies that they used us on and they tested with one of them was coaching and the way in which Ted got bored updates was through slack. And he got information. So his context and the company was rising. So for him. It was really valuable. I think it's really important here is at that time, you know, a lot of investors look at companies, they think of it as tired or diverse too much money. They were a game company. Before they can't be an enterprise company. It's like it doesn't fit their mold of or at their biopsies of how companies should be built in a sector. And we took the bottoms up approach the volumes of approach was. Well, let's see how they perform. Let's see the demand signals that makes sense for this company and given that there was barely any revenue and engagement was there a couple of customers and the team had social capital really dug in deep and assess the data what's more important is that we continue to assess the data of the company across multiple stages of investments not during not just during the series. And so a lot of people say, hey, you can't really assess companies at the series. Well, if you think about it today at a series when someone's trying to raise between five and ten million dollars. They have raised some seed capital. Let's just say between five hundred three million if if you think about that wide range, and they probably have their product out at the at the minimum three months and up to fifteen to eighteen months, in some cases, where there are testing in iterating. Well, that's a plethora of data to look through to see how it's been performing. And it's always shades of gray. It's never perfect. There's no company where you look at their data the primary data, and I think this is the important part. This is not something that they provide to us in a deck. We're ingesting it. And then we are assessing and analyzing it, and then giving it back to them there. There are multiple ways in which you can kind of approach the market BBC top top-down midmarket small the medium consumer subscription. Even consumer enterprise B to B to beat ac- in some cases, when you think about energy. So there are multiple frameworks that you can use. And there are multiple ways in which you can essentially assess how is this company doing where it was before? Whereas today, and what will it take for them to scale from venture scale outcome. I think what happens is a lot of people just see a number and they get excited, and in some cases, they've already made the decision, and then they try to back it up with data versus the other way round. So our whole goal is to flip the coin. Instead when we meet entrepreneurs, we tell them don't pitch us. We'll pitch you give us access to your data. And we will run our analysis on you. We'll give you the magic eight ball back, and we will show what kind of value that we can. So we look more like data and analytic system, but with consultants on top of it. So kind of like the McKenzie way of understanding what it means to be in venture. About us worse. So you end of for they presume of Connie. As most I view in terms of. Will turn better. So a lot of this has also just secret sauce and some of this. We put out Gino Jonathan's published this around demand signals that we care about. But there's no right or wrong answer. And I think this is part of the key. Some people will say you need to have really great retention. Well, you can have really great retention, but you can have no net expansion of growth. That's not a company you wanna invest in. You can have high growth. No retention. That's not a company when invest in. So there's there's a lot of pieces that you care about it. I think it's more a lot of these frameworks exist on how to assess it, that's that's not a secret. It's just more about the interpretation of how do you get the data? So when you have to ingest it, and that's non trivial you have to have a framework to assess it, that's non trivial you have to be able to productized us and put this into a package of readable. That's non trivial, and then you've had to have done it. So many times thousands of times, which is what we've done, and that's also non-trivial. And so I could go into any company and say the types of things that we look out, but for any consumer, it's basically you're looking at all forms of customer engagement and some forms of that. Customer engagement is just the the intent in the way in which they came. So it could be anything like I think demand signals what you care about. And then you go to the next level, right? The next thing people will care about unit economics for some people. That matters a lot something doesn't. So it's more about how do you interpret the data? Once you have it. And the accuracy of it. We feel like we're very accurate because we have a ground truth perspective on how the company's been performing. Different views. It's essentially the same any company that builds software is measurable, and you just have to understand what are the demand signals that you care about the investment framework and philosophy to invest in that come in that company. You're just some people are okay with a slow growth. Six percent year over year. Some people are not this. Some people want fifty percent year over year. Some people are not okay with that. We generally on the venture side are looking at three to five year over year growth in something could be users could be revenue could be customer engagement, something that is helping propel the company forward in your in your digging into becoming more bespoke on what you care about. Let us us on the way you seeing that. Yeah. I'll take a step back and to talk about cars, we talk about slack. And then we talk about Facebook. And with really important again. This is just another indication of how traditional VC's have our mindsets. Are a company has raised a certain amount of capital. They didn't really hit the certain metrics when they saw it. And so they just assumed the company's tartans it's happened time and time again when we assessed slack. We were able to eventually assess what we believe is an outcome that there was a possibility to replace Email, and you could see multiple networks internally and externally, and I think this is the key thing that were interacting with the product with each other. So very similar to right. Like, I'm not within your organization, but I'm willing to talk to you, and I can create communication protocols to make that happen. So we saw that that's measurable that's uniquely identifiable in a quantitative way Facebook as well. Known for this. And our team has done this so many times that we were able to kind of recognize this. I wouldn't call this pattern matching pattern matching would be. I think this can happen because all these companies when you meet them during their series and B they'll say, I believe in work. I think I have this or they'll say it with confidence, but they can't measure, and so we always go in and say, okay. Well, what can we quantify around those types of statements? What can we quantify our selves? If we have a thesis and Facebook was really the first company outside of the social gaming companies around that same ecosystem where you are measuring network of growth in. Parts of the United States at a high school at college, you know, Japan versus Turkey different flows user account privacy control versus newsfeed all of these things have different frameworks around understanding growth. And if you really think about what growth means it just means product market fit in can you scale it? And so we did this. That's like as I mentioned when we met card. I we use these frameworks to understand. Hey, does this company have any semblance of network affect the company says they have network affect were hearing it and celery Why's that there's no effect, but we don't know for sure. So can we measure that? And so we did. And so we we saw a lot of early signs of connections between stakeholders stakeholders are employee's stakeholders are the company themselves in stakeholders are the investors that invest in the companies, and then we saw them multiple multiple interactions. It started getting stronger and stronger between those nodes again, that's measurable something that the company had not done initially. And so part of our goal was when we invest, let's help them align and reorient themselves to think this way similar to what we did at slack and similar to what the growth team and the data science team. It did our Facebook during the early days. So that's what we set out to do. So we did the series in two Carta, and then we did the series D. And then we basically lined ourselves with the company for as much as we can around orientation of what they can become on products that can be built on top of their network one of the products that, you know, obviously, people know about is the four nine eight and the cap table and really recently they went into investor. Services with funded ministration. But if you basically look at ten thousand companies in the platform, they're going to have a couple of hundred funds in the platform, the AM that comes from those funds. You basically see this system of record monster company that can be built, and they can go into as many Jason territories as they want because they're building a network that just continues to reinforce and strengthen and self similar to how you've seen other network affect companies. I don't think it's about missed opportunity. Angels is a great company to it has built an ecosystem around angels themselves companies hiring making sure that you can kind of propel them from one stage to the next, and I think what you've seen them do evolved from the early stage. Two parts of the mid stage by keeping Parada and value out services. So I think that they are completely different companies with different types of network effects. One is more prone to high frequency of transactions and the other one's more prone towards qualitative transactions. Are we most how mistakes his actions will have round are out of your or not realize rating? If you're a team that has raised a couple million dollars and all of your investors at the today's are saying it's time to go raise. I see some metrics. It's really great or you're a team that speaks very confidently about what you're building. Of course, you feel like you have you have this irrational passion to build something that you wanted to solve and your problem set with your solution set, you believe is starting to work you. So in some cases, you believe it yourself without any quantitative data. And then you use some surface level data in some cases to propel you forward and say, I think I'm ready for venture capital to scale five or ten x from here or one hundred dollars from here. I think part of the issue here is if you don't know quantitatively if your product is working or not that's one part. And then the second piece is how much capital should you really raise to get to the next milestone, should you really raise a series or should you raise half that amount to get to the next milestone. So a lot of what we try to do is just ground truth have a conversation. Just here is exactly where your company is. Here's how you've performed here's what it's going to take to get to the next scale, this may or may not work. And in some cases, these companies are not meant to have a tra- capital. They're meant to distribute capital back to themselves. They're meant to get alone. They're meant to be a small to medium business if you were us assess product market fit for local coffee shop, they might hit all the marks. They have retention of customers. People keep coming back, but they're not growing. They don't have any net expansion, but they are good enough. Or where they are this that company deserve venture capital. Maybe having unique value proposition in the way in which they think about growing, but in most cases, they won't they won't need venture capital. So I think a part of this is that we see so many companies all over the world, roughly, we'll do our assessment on about two hundred three hundred companies where we go really deep, and it's really great. Because this is the first time they have a view of how investors view them. This is the first time they get to see data science and product ministering in action to gauge in grade what they've done so far now. And it's the first time they might learn something new them never learned before about how they want to strategically move their company forward. So then you ask the question to the voters. Okay. Great now or an alignment about ground truth. Which is the hardest thing to do that is the hardest thing everyone tries to figure out now that you're in alignment with ground truth of how the company's been forming. Let's start a discussion on what it takes to go to the next stage. That's much easier. Way of building alignment with founders and investing through them, then believing in a story telling your other partners. I think they can do this, especially when you don't know the question of is it working? And that's the main problem. I think we've always seen with the industry, and the what we always wanted to try to solve this. How close can we get to quantitatively answering is it working in some cases? You can't. That's okay. Their companies were there won't be enough data to make a decision yet. And again, the data doesn't. Tell you to make decision. It's just a part of the equation. If you look at the three Dacians of any company product marketing team, there's very little data on the team. You can everyone basically has their quality to framers around. How to assess a team we look at product Centric metrics that we get from the software that they built and there's the market, and you kind of take all those three pieces and ask do I think this is venture scalable model. Are about different on approaches. They eight to mate. Wait. I think I would just echo. What I said before the approach is really very simple. If you're a engineering team product data science team at the company, what are the things that you do to try to understand what is working in your company, and what is not working? That's essentially what we do. We come in with our heroes. Six of how we viewed any company we look at customer engagement retention, whatever you want to define it as always different for each company. And we look at the primary data that the company is throwing off. Right. This is a treasure trove of information that matters retake that and then we basically build our own bottoms up view. And then we try to we present that back as if it's a dashboard for the company to see. And then we start the discussion on what makes sense what doesn't make sense for their company when we're building this bottoms up you you are learning about so much of the company. What's valuable? What's not? So that you can start asking the next question. What's the qualitative stuff that matters? Right. How did you do this? What happened to pricing? Why was there was this blip? Like, what was the way in which this affected these cohorts not to test them? But to ask what their plans are on their future roadmap. That's really important because if you're a product manager at a company, what do you do you look you look at past performance. You look at bespoke analysis that you're gonna do in the future. You look at the way in which you're going to test stuff, and you have your engine team in your data science team come up plans around what the future roadmap. Look like, we're almost no different. We're coming there to try to figure out how to align with a company as much as possible and gain the most context. When will venture digital venture. Venture. The rock is rates to do with lies having source companies Jews hiding Dylan's company retirees or. Vice? Yeah. The way the way we define stuff is. There is sourcing. There's evaluating there's a lining, and then there's managing places where we focused all of our attention. Almost ninety percent is on the ladder three so on evaluation, as I mentioned me just the primary data on a lining make sure that the way in which we think about helping the company step function is in alignment with the company, and they believe in the strategy, by the way, we won't partner. So we are fairly concentrated we are not fit for companies and managing the company toward successive where we continue to do more bespoke analysis as they get larger or if it's not working as well where we can unlock more data from the to help them. Make better decisions. We are not going to make the decisions our goal is to unlock the data. So that they can make the decisions, and it may be right or wrong. But if the wrong decision, at least, they'll know sooner rather than later, a lock the why are they in? Capable or will, you know? Yeah. In some cases, there are companies that are very good at this. And it's very rare. I think what you see is we have a holistic perspective on companies markets sectors. We see multiple companies the way in which they're performing. So we can continue to benchmark gauge and kind of show the value of what a company needs to spire towards in order to be best in their class. And it's it's actually pretty rewarding because if you set everything to ground level and truth around how you are performing across all of the appendages of your company, you tend to start making different decisions versus three or or I believe this. And it's not to say that you don't have a vision or northstar it's more about what can I get access to to make better decisions. And that's that's the whole point. The whole point is can we help accelerate a lot of these companies because they haven't built these teams out before you know, when you hire scientists, you you can't tell them do this. They have to have an understanding of your business to heuristic to kind of. Start digging into and the best companies in the world, like Google, Facebook, etc. They've been doing this for so long that they've mastered. Certain parts of what it means to have data scientists and engineers focus on this on this path product market fit. Whereas if you're a company of two people, if your company of ten people you've been focused on surviving and getting your product to a working state. And so our whole goal is to let us help you define that working state, and what it means to make that working state stronger and stronger overtime. I think some companies are capable of our whole goal is to teach them this over time. So they can do it themselves. But as we've seen with a lot of our companies, regardless of stage, there's always something new that they haven't done. We can continue to help them lock. It us. Because there's less vanished. You got Jane? Sourcing is an aspect of it. I think it's one part of the equation that matters for obviously venture capital. And we've always partnered with other firms we've always gotten inbound and strong referrals as well. So we're not opposed to using data science to source, but look at kind of the parameters of what you do a lot of the parameters of data sourcing data using data source is let me find publicly available data or either scraping using credit card. Pennells you're looking at crunch base pitchbook at different stages. You're looking at the white see list, and you're just going out to those companies. And you're hoping you might like the idea that you're taking a qualitative framework. Do I like this market? Do I like this team? So again across three verticals of product marketing team, the only you're using your your frameworks for what you think matters. And you might pass our whole goal is let's build a bottoms up view. Let's do the work on the company. Let's pitch to them on why we think they might be worthwhile. Well, regardless of where it comes from sourcing. It's not to say, we've got it. We don't use data science for sourcing. It's just not something. It's nothing that we focus on as one hundred percent. And let's make sure we not we're not going to miss the best companies because we had a bias. And that's that's our main goal, and that gives us the ability to invest in founders where someone might have been away tryst and she wants to start a B company where someone was a a karate teacher decided to start a vertically integrated SAS company someone had built consumer product before failed but decided to build an enterprise company, the three companies mentioning are all companies that are worth over half a billion and more. So I think the to understand, you know, how powerful this is that we get to reduce bias. We get to partner with anyone from anywhere in the world. And we can help them accelerate their business because we have a view on the way in which companies get built once you get too close enough demand signals for product market fit. So capitalism service at at social capital was essentially built on the frameworks of what we have. So we had different heuristic frameworks understanding product market fit procedure and companies and the goal was for one of our teams that social capital to find possibly outlier style companies outside of the traditional areas of venture capital, Silicon Valley, York, LA, etc. And what I'd say is that you could have a framework of using software to make investments or you can have a framework to think about using software and data to make better decisions. So they're usually two extremes. There are people in the industry in my opinion. That are on one side that say data doesn't matter. All I care about is like how I do the company it's been around for so long. I will call the tradit- traditional VC said that no matter what stage you're at that used the same framework. From Syria, see, Missouri's D, And I see that over and over again. And then there's the other side of the world. Which is I think what you saw Soche capital, which is like we can automate everything what we really kind of fit in the middle. Right. Like when you are building a company there are people. There are very Ables that are human. You have to work hard to help the company get from stage to stage you've been as VC that doesn't matter. And our whole goal is. Can we get as much context in the company using our data science? So that when we need to do the other aspects of company building where there to force multiplying the way in which we could have done it as a pass like one individual, right? We are our firm is set up like a company, I work on product, Ted works and operations Jonathan works on tech. So it's like, you know, yogurt CTO CPO, and we have data scientists engineers with team that are like fully focused on helping our companies as a partner. So we don't have Monday partner meetings. We never we almost never make decisions on only on a Monday. We have stand ups every. Day like a product team, and we're building products and we're building relationships with our companies. And so I think that's part of the equation of why we are focused in this way versus being on either extreme. Team marketing team. You. Team as maybe gone or earlier that day on that as early in their trash as well wizard walls, positive. You have for her binding. Yeah, we're all very different the firm. We have this perspective. Kevin our sweet spot is five or ten million dollar check series in B's. We do other rounds at other stages opportunistically. But again, it's the word opportunistic where we feel like we can help the company step function. And at the earliest age, I wanna call pre seed and seed different frameworks. Right. You have you have teams that are haven't never built anything before. Coming in fresh and saying they want to build this product for this market. Here's our solution. And it might be that whole team in napkin idea, then you have some that have a demo which is like this is what it's gonna look like. And then you have people that are coming out of companies that we all know. Well, the thing I want to build a company in X sector. Here's my background. I think I can do it. Give me give me capital. And so use different frameworks across all of that. Right. You either like the market and the team that's a framework you'd like parts of their product and the market you may not like the team. But you missed the deal. I think you've seen that from a lot of people. I mean, we tend to consider ourselves tribe like in that we want to treat all of our companies equal, no matter what the check sizes and in order to that we end up having to be more concentrated, but also more opportunistic with our time. And so when we do right small check, which we have we call it, our angel style checks is that a partner sponsors an area that they care about. So if I'm doing a deal I will act like an angel which is I'm going. To be accountable for this check in the movie accountable for my time to that company and make sure that they're actually integrated with all of our companies in portfolio, regardless of the check size that we written to the other portfolio. So someone has a twenty five K check that we've written to them. I'm treating them the same as a forty million dollar check that we Britain Marvis about Tostao eight worth more. Vase for this. Of attack Marquette, Joe Sanders. What space non brought are you processing you? Monks. You know, everyone says they like big markets. But we don't know what big markets are generally prescribe to Mark Andriessen this philosophy that, you know, software is eating the world. And then I would take that a step further and say Soffer has been proliferated in everything we do. And so if you just take that into how we live our lives how much time that we have throughout her Dane, what are we doing? Those chunks of time. Like, what are the products that take up that space? We generally kind of look at those markets, right? You'll you'll look at energy because you use energy you look at real estate because you live. Homer house. You look at transportation auto it look at all these pieces, and then you look at the full vertically integrated stack of what is in this industry, and what's either being deregulated or fragmented because of software. I can I can go on about every single one of these markets, but we're generalists by that fashion. We look at markets. That are interesting for us, regardless. If people think it smaller, not, and we don't actually care because we believed if we build a bottoms up view, we can have a better understanding of what the Tam could look like for a company and given that we're investing at the early stage. Tampa may not matter if you give it enough time to matter. Couple companies, but they be of NC Ray of his cover as what you saw in that on days unique. St. I UTA thinking on how hot car when it was review easy it yet. Yeah. So I mean first off thank you because you made the introduction. So I appreciate it. But you know, we met cover, and they had this thesis, which is important that most insurance companies today are built one product line at a time. So if you go back the advent ten years ago of the companies that are being built there have been renter's insurance auto insurance, homeowners life, etc. And they're all very specific to a product line and KARN who's the founder and Natalie who's one of the co founders in on the three of them together. The basically had come to us and said the way in which up insurance company of the future is going to work become big and massive is to do two things. One is to be an insurance company, actually. Similar to insurance companies of the Paso back to basics and being able to not turn down any customer for any reason so hot and do that. So it sounded crazy. And I just kept asking asking what this would look like in whether approach wasn't. So their whole approach was we want to be a broker we wanna be a Switzerland in the space, but we also want to have our own product lines. What does that allow you to do? Well, that allows you to not turn down a customer will hit great. Well, how do you actually do that from a product perspective? And so in most cases, people look oh cover is the mobile app. They're not just the mobile app. They are a choice on your point of sale system. When you do a driving school in a certain state. They are also your option there. The just have a multitude of ways in which they engage with the customer, which I think is the most unique part about them as they don't consider themselves in next-generation mobile app insurance company. They think of themselves the next generation insurance company, and then they have channels in the way in which they approach the customer and those check. Annals are products in themselves that kind of spire to the intent of customer. You may want to do just all through mobile. I made care about getting a hold of someone agent on the phone someone else only wants to buy insurance through their channel partners. Another person wants to consider a broker that they already working with which cover will also work with and they don't want to change their insurance companies. So they'll just use cover to represent them as the broker, and so if you look at that flexibility, but they can do they can end up working with anyone very similar to the way in which insurance companies work today like having that type of vision in the beginning was great clearly as venture capitalist. We didn't believe it right from the beginning. So our approach to kind of understanding what was working, and what wasn't for cover early on what's to understand their product market fit across all their channels, their first channel was mobile second channel shop affi-, and then the subsequent channels after that. And so then when you start thinking about their unique value proposition to the customer, how do I measure success? And then how do I measure? Market fit not just as a holistic company, but just each channel is product market fed. That's how we game conviction. Then we took all of that product. Is it gave it to them and said, here's how we think about what's working. What's not and how we would prioritize our time. Here's how you should think about your capital. The ended up being one of the most capital efficient companies in the space growing at such a rapid rate. They've you know, I would say in in many cases, there rivaling a lot of people that are raised hundreds of millions of dollars. But they're doing it at a pace, that's sustainable. They're doing it at a pace of what we believe is going to be the next, you know, insurance company that's going to last decades and be resilient. Us less. You think about? Digital verse you as a abuses capital tinier, others haven't really followed a hours in our said, you industry house is most of the hot wings renter involvement on of those religious offer finish physically of remerged as really is wounded Caesar about worlds of as receive injuring wars are sent. So I'll flip it back on you and ask. Well, if you've been doing something your whole life a certain way, and it's kind of worked for you. What's your motivation to change not a lot? If you've been doing product management the same way for a long time, your motivation to change is not a lot. So a lot of questions, you know, VC's ask why does Google do this? Why doesn't Uber? Do this. Why don't these other companies I want you're digging series? It's one of the one of the stupidest questions people ask because if you're used to doing certain. Way you usually don't adapter change of yahu didn't adopt or change Google golden adapted change to Facebook. We're just multiple stories like that. So it's the same thing in venture just because adventures been done a certain way for forty years doesn't mean it hasn't changed or incrementally changed it has some funds of gun larger they're deploying capital later stages. Some have become registered investment advisers somewhere using data for sourcing that wasn't the case before because before you had people on the phone calling outbound. So things have changed. I think people just don't care to admit that the periphery of what they do is changing. But their core investment decision. Making is still the same that is going to change. And I think what's wrong there is that you know, because you use excel. And you feel good about it doesn't mean that you can't use software scripts in tools to be able to make better decisions in augment you as a human. That's essentially where we come from. We're not saying that data takes over any of our decision making. It just helps us make better decisions. And it helps us make better decisions in the future. When we. We make mistakes. Now. Vangelis heats grasping. Yeah. There's a part of me that says, no. So we can continue to do what we do. Really? Well. And then there's a part of me that where I hope there are more people that are going to prescribe to the way in which you partner with entrepreneurs because I think it's really a big value. Add four founders of management teams at helps them more than it hurts anyone else. So I'm hoping that a lot of of what we do because we open source of the way in which we approached it gets proliferated further and further. So I would say ten years pretty longtime things can't change. And I'm sure people are going to try. But I think it's also hard. No, let's just say you were the person Jonathan my partner likes to say this lot. Let's say you were the person that came up with accounting frameworks one hundred years ago, you have the frameworks, but then it's the interpretation of this framework for your statement of balance sheet, or cash flow, etc. Everyone has the same level of information. When you invest in public companies, it's the interpretation on top of that what you. Believe is different. So you can find alpha. It's no different adventure in my opinion. And I actually think the reason why venture people use the word power law, or if you are doing a seed or series investment, they need to certain percentage ownership the reason they do that is because they know a certain percentage of their companies are going to fail. The reason the a certain percentage of their companies they're gonna fail is because of the antiquated frameworks we use to make decisions to our whole goal has been. Well, our frameworks are help us reduce our loss ratio for making which gives us the ability to have a better portfolio construction, which ends up being more concentrated versus like I need, you know, twenty five companies and one of them to return my fund. Well, oh, you only do that. Because you're frameworks are so antiquated. For for a second. I think he is at a rise in recent is somewhat of a all any seems is nine in close to like it is all theranos illegal legality in deserve. Environmental as we're like is. Fraud goes just rely money. Should resume late do Drancy. Well. Just be people closure win the Aqaba major doing it. Well, and it's her name's go haywire. What why you're how do is about you that? Everybody loves United Greer with that sorta. And what's? Sued will eliminate implode because they're dying of last long? Yeah. I, you know, if I if I go back to my career, and if I look at my competitive set as well that we're in the system. So let's take zinc. For example. I think you had a very talented team talented, founder of very talented approach to the market, but the way in which they hired culturally. I think it was more mercenary than anything else. It's a what happened is that you had a cultural implosion internally. A what matter what didn't and then more short term thinking? So and I think that's like a really quick way of of capturing what might have happened at Zingo, and there's lots of other things, but think at its core was that wrought started to proliferate within the organization now, I think you can have that in any organization, and depending on what the organization is doing how strong that platform is or what I call how resilient it is to rot is what makes it successful. And what does it make successful? Right. When when you're able to purge those things out of the system or inoculate. So I would. Say like your best ten percent of moving the company or your firm forward, you can generally survive. And I think you've seen this in the case of no one we sold our company will apps to next on when we went to Yabu from message me, you had pieces of this right were the in some cases, the platform was strong enough to be resilient to the Roth that existed, but at the same time you have so many smart people across all of these companies. And so the question is are being what is the north star or the atomic of unit unit of what they care about. How do you bring that together? And so at social cabinets his price on the smartest people ever worked with across any of the things that I built in. And you're putting them together to figure out how to facilitate what venture capital should look like what growth should look like what credits you look at a certain point and the public markets, and in some cases, I would say because so many smart people were in. The room we came up with so many different frameworks ideas of what could and could not happen that we ended up testing a lot of these theses of what was good MOS bad. I would say like the ultimate transition for our team moving into ventures that we believe we were very good at this stage of investing, and why we focused on it as an early stage mentoring like if you were to transplant our team, it's essentially the same team that was such a capital and credit to to be honest is the approach that he had taken when he was scaling Facebook, just the rigor and the types of personalities that you wanted in the room, the types of creative ideas around how you can deploy certain types of thinking into a new industry company capital. Was it? It's far beyond what other people were thinking. And it's part of why we all came together was that there was this vision of that we could think very differently in the way in which we partner with our our founders in the companies, and we did that. And so what I'd say like a. The success story out of social capital is the framework in the way in which we all think, and then how many other people now that have moved on from such capital to the next next choices in their life. Or the next journey is that we're still using those same frameworks, we're still working together on we're all still pretty closely tied together, including the people at social capital, including two moth have we already still work with today. And I think what you saw which was that. He wanted to start building more control positions. He wanted to start thinking about different stages as you saw with the advent of this back in the in the in the previous years that he's doing exactly what he wants. And that's really valuable and we're doing exactly what we want. And there are other former partners are doing exactly what they want. Is way too rare. California's in youth that I got my serve you sound with a view against a lot often. How could all of of firm? Send us as IRS. You know, why not take on? My see why not say on first round why the group on. If you look at the market today, there's two things that are happening. You have a proliferation of capital that's at the early stage. And then you have a proliferation of capital at the late stage. Now, why does that happen? We have a lot more liquidity in the system. We've had a bull run for a pretty long time. So how do you differentiate at the series seed precede seed stage while it's brand it's what you can do to have the company help propel it from the next stage the next stage. And so there's a lot of what I take qualitative pieces of company building the foundations that need to be built. That's what why c does. That's what you guys do village. That's what first round has done, and they all have a different approach, and what I'd say is in order for you to be successful in seed, my, you know, my strong opinion is that you need to have a larger value out of resources to help companies propel in a brand behind it to help them get to the next stage. No, hiring, etc. And then the next set of investors. And from where we come from. We know how to help companies amplify their product market fit post at stage. We know how to identify it. We can help them think through it. What's working what's not a really early stage? So we ended up building a lot of these relationships with wasiyu first-round like we've done many many times and help companies can guide and say, well, this is what it takes from us to raise a series. Do you have to have a million air are with us? Absolutely. Not do you have to have certain amount of retention metrics. Absolutely. Not. We basically are saying is that when we do our general overall check our health check when we give you a grading or a score on our magic eight ball. It gives you a perspective of how we think in. What would it take an investment from us? That's like a quantitative like product or a piece of paper. I'm delivering to you to let you know, what it takes, and what it would take for us to want to invest in YouTube, or like, how can we align? So the reason we chose series and B is that's the time where you have shades of gray. That's the time where. For data isn't everything where it's just a part of the equation in. We've been able to successfully find companies at the earliest stage using a quantitative metrics and finding companies really really early and providing this insight because when you provide us insight in our belief is that they're helps him step function faster. So that's why we did at the earliest age. Now does that mean we can't be helpful at later stages? No, we are helpful. But as I mentioned you've had a proliferation of capital at the late stage. And so it becomes more commodity oriented, right? Like, you're you if your company is working at the series and stage, you have a plethora of capital to choose from. And it becomes more transactional. Our whole goal is not to be transactional or Hoke goal is to be relationship driven alignment with the founders and make sure that we can stick with them as long as possible. Last retirement. Growth earth, or or some hanger. This. Our goal is to be the best at this. Does that mean we won't go outside the scope invest in later stage rounds? No, we've done that. It's I think it's more. Do we believe in or we have fit for the company where we can help them step function where we can handle FAI their product market fit that exists today. And if the answer is no, then we're we're not the right partners. And and I think what we've been able to show time and time again is that we're very good at actually still delivering that value to even people that we have not invested in the quantitatively tell him. Hey, we're not the right fit for you. We don't think it will work for us because this is the type of work that we do. Here's the time that we spend once invest, but this is a guidebook that we start with them. We don't think we can really help move the needle at all. And I think that's something that most investors don't do it because they think they can do anything. So if you. Bread or us a clear of earlier invasive law. You're oily is our first. Yeah, we have this thesis that everyone regresses TIMMY, it'd become mediocre at a certain point. And you have to figure out ways in which void that. And so a lot of to be honest. A lot of the pieces that I wrote were either frustrations that I saw at companies where I couldn't help an outcome or there were my own companies where I had unsuccessful attempts or at organizations where I was an executive all your who were I couldn't really affect change because the momentum of the ship is going too far whether we're just sinking and I couldn't fix it. And so a lot of it are around these pieces that are Britain is essentially a problems and trying to find solutions that can help those companies even while I was there. And in some cases, it's worked really well companies. Literally print them out. And it's on there. You know, when I when I come in at their offices on the wall and a second step by step guide. I think they've made it much better than I have. And then they can build frameworks off of it. And I would say that's more for team oriented stuff than it has been for the philosophical frameworks. But but what's really important here is this innovators? Dilemma thing really comes from a had a quantitative approach as I started thinking about what the quantitative approaches are how could you just learn more from what's happening and get to better decisions, and the more data that you have to be able to unpack hypothesis that you can ask get back answers in a much quicker format. My belief is that you will just generally make better decisions. And so a lot of these pieces are about like, how do you just get into that cycle to get to a place where you can make better decisions is not just a management team or a CEO, but even like your mid level folks that are running product engineering that aren't doing this in battling this on the day to day. What are they really what they're really fighting for is is a part of all these. Marks of the pieces that are. People. Resilient teams seems to review are crumble under under duress are. Yeah. There's a you know, they're in. I don't know. If you've read this book thinking fast and slow what it really comes down to some people are reactionary. I'm just need to fix this as soon as possible without thinking through it. And then some people have an appropriate response for this is it's a it's a it's a verbiage at the military uses a lot too and. I was and so one of the things that has always been like always kind of astounding for me is that when companies are building they kind of react to growth, right? Like, I don't prescribe to blitz gambling because it creates more mercenary style attitudes. And I actually think it creates more bias he's in the organization because you keep looking for more of the same versus the diversity of the and so they just keep reacting reacting reacting. So if I just slapped you across the face, you would immediately react to it. And that's not what you want at a company, you wanna have companies create responses, and so I've always been kind of puzzled by the way in which some companies are advised by their investors around you just need to hire this person from this organization because they grew this company from fifty to one hundred million about new what they do is they go after these resumes almost every single time. I've seen this happen. Is that the resumes? Don't add value to the company actually created more. Toxicity. And the companies that I've seen work, really. Well, is that they grow their ingrown talent. To create a ecosystem for them to succeed and inject the right people at the right stage, regardless of resume or not companies that I think I've seen do the successfully not perfect habit companies like Facebook, they're obviously there have been some social gaming companies that have done this in the past two was that worked really one of the ones that didn't. And you can kind of see the teams that worked really well are the ones that just generally had less churn. So it's not it's not a complicated thing to understand is that if your employees are generally happy with their momentum and success there generally have an understanding of where they're going, and they have a positive feedback loop transparent feedback loop that trend less, and so the people platform was more about like, how do you start thinking about investing in your old people similar to what the credo of Johnson and Johnson of the past? And don't forget that just because old companies that created this long time ago, it will companies are bad, which means that they had a thesis and some of it worked. And so what are the things that we can use today in the way in which he Abbas. On has grown out past companies like GM and Johnson Johnson grump for remember fifty hundred years, in some cases, if you go back far enough where our technology companies in some cases, they're not even more than five years old. And like you look at Microsoft's like what thirty five to forty years old. Now, see I don't really have a lot of data like this is the best way to build companies. So it's more about like what what are the the best things that you can take from each parts of these companies over the last ten years that you can use. Time is the or you choose it. I mean, we prescribe to a philosophy of knowledge accumulation and through knowledge accumulation you can make better decisions. Obviously, we're kind of see this reoccurring theme of decision making whether it's right or wrong is just the process of acquiring knowledge. And so it's time for us. It's more about how do you compound knowledge in in some sense. And, you know, over time, it's obviously evolved, and those kind of our first rations of thinking through it. But you know, like, in some cases life is very short so trying to figure out how to optimize for what you need to get. But in some cases, it's pretty long. So you kind of have to try to figure out the balance between the two of what you're focused on. And I think a company horizon units time, really matters, right? There are there are moments when you just need to be very taco get things done as quickly as possible. Make sure you have the best data available to make the best decision. But you also need to understand that it's going to take time to compound in. What does that look like? And so a lot of this was the framing the again goal of what it means to, you know, create a north star when it means to have an atomic unit for your company. How do you? Orient yourself. A lot of these things that we write about quantitatively or qualitatively are really focused on to be honest, creating the outcome. And so that's that's how I would think about units time is the subset of how to get there. Maitland. Their are star was his action about what was their star. He read a blog post from the thing they need to do the same thing. Right. If you look at any company, any company that has been successful hasn't been because if copied someone else's format they've they've done really well because they just do what they do better. They take other philosophies of had worked at other companies and figure out how that could be injected into their company for what they do rather than try to copy some other other frameworks, and it's kind of like the Roman philosophy right? Like, the Romans didn't have like this innate religion at the start. They add different religions to continue to conquer moorlands. So it's kind of similar here in that as a company, you have your value sets that you care about your principles that you don't want to change. But there are other tactics that you might want to change over time because you are a company as an entity it's like a malleable entity at the end of the day. And so you want to make that happen because you have different color. -tural sets as you scale different people that are coming on board different ways in which you think about building product. It's not just like one hierarchical way. And even the great companies like apple don't do it the same way across departments of product development, and has its own culture, but they have principles and guidelines that they follow. Attention being all on Assulin. You will you think on the honeys? Yet, you know, the beauty of having data and having it as a part of the equation, and recognizing it's not gonna be everything for you is a recognizing that it's not going to be everything for you at different stages of accompanying or different stages of anything that you do. There's only a certain amount of data that you can use to make decisions are basis talks about what is the least amount of data that I need to make decisions. That's essentially what you want across the board. What is the least amount of data that you need to have in order to make a good decision, which we don't think about it too differently. Right. So now, what people say what kind of data you gather on the team while the data that I have is with the built over the last two years, but to measure it, and let's give the team the benefit of the doubt to see. What what do they need to add one of the strengths and weaknesses of the team that we need to have to interpret the data in help them move forward. So there's no right or wrong answer to be clear. There are some cases where you have more data than companies more explicit can understand where they're going. You can make better. Forecasts the. The goal here in why we take this approach in wide. You guys have been asking about this for a while is that the the best data in the world is data that sits in the company in the best way to assess it is by understanding how to take a look at the the data that exists there and by continually doing it, you can build better and better. Here are six of each company. It's not about taking outside data in having a perspective because that's pretty commoditised, and is lagging indicators, it's more. If you're an early stage company at a certain life cycle once the data that matters. And so we have different frameworks for each stage. Of the I R the on Twitter tribe. Cap is for were then a or is? Thanks for having me. If you're an early stage entrepreneur, we'd love to hear you. Please hit us up village. Global dot BC slash at work catalyst.