Power Laws, Venture Math, and Changing Your Mind with Abe Othman

Speaker A: Welcome to Investing in Startups. I'm Joe Maker. Our guest this week is Abe Offman, researcher at Angellist. Abe is one of the leading researchers in the venture and startup space, publishing super insightful research on everything from VC portfolio construction to valuation data and returns. We had a really fun, geeky conversation today about check sizes, contrarian thinking and what Abe has changed his mind about over the last few years. I'm a longtime reader of his research, so I really enjoyed this one. I thought we covered a lot of really interesting ground and I think you'll have fun listening as well. Please enjoy. I've been reading your stuff for years, so it's great to uh, finally talk shop with the man himself.

Speaker B: Thank you for having me, Joe. It's great to be on, I thought

Speaker A: a good place to start given and especially with like seed valuations have been warming up a lot lately. Interesting place to start would be to talk about valuation and how much do you think valuation matters if you're investing at seed?

Speaker B: Yeah, great question. So I think the short answer is not much, provided that I do think there may be uh, you see some kind of absurd frankly seed rounds now where people are raising hundreds of millions or billion dollar valuation and calling it a seed round. I am not sure that those extremely expensive rounds will have the same characteristics as sort of the rest of seed. But if you're talking about maybe like sub $100 million valuations and you want an assessment of like, you know, someone's doing a Pre seed at 5 versus someone's doing a seed at 75, there's not much difference in those opportunities. Now what we think is happening right, seed is actually relatively pretty efficient. The company raising at 75 is probably about 15 times better than the company raising at 5. It's one of the challenges I think the asset class is like. And so on a forward looking investment basis, neither of them to one word, first order, neither of those is necessarily better than the other opportunity. It's one of the challenges I think especially thinking about a signals driven approach to uh, startup investing is that people have come to me and they're like, I've cracked the puzzle about how to do seed investing and it's to only invest in companies that have repeat founders who've had a successful exit. And you're like cool, yeah. And they're like what does the data say on that? And you're like yeah, data says that is in fact a positive signal. Yeah, I solved it. And it's like, well you kind of solved it because that's the company that's raising at 75 or 100 pre, not the company that's raising at 10. So like you're right that having a repeat founder with a successful exit is a positive sign for the valuation of a company on a future basis. But like you are paying for that

Speaker A: and it's not exactly a hidden signal.

Speaker B: Uh, correct. Yeah. By signal I would say, you know, my interpretation of signal is like anything that's in a deck is a signal. So it's you know, traction, founder, bio, team, whatever. But I do think uh, the sort of, on a deeper level, I think my kind of world model is that every positive signal is in fact a positive signal. But uh, founders take 90% of the boon of those signals into price. And so if you kind of work that out like on a kind of like iterative thought level, it does suggest that the most expensive seed deals should actually be the highest performing because they're essentially aggregating a bunch of little alpha edges from all the positive signals that make it have a high price. Essentially like they're very high priced because of the positive signals, but the signals are not fully priced in. And you run the analysis with Angelus data, uh, you kind of get that result. The kind of, the hit rate of like you know, 10x MOIC seed deals like, you know, you can kind of see an up into the right slope as relative valuations increase. It is certainly not strong enough for someone to be like, I'm only doing top decile consensus seed deals, bro. That's, that's how you get return. Like it's. No, it's not, it's not that good. Um, but it is there enough that I think it does reinforce the kind of overall view that like, yeah, I mean so like someone going to MIT or GSB or having a successful startup or having a great team or having a bunch of traction or whatever, these are all positive things for an investment, but they're mostly priced in. And so you know, there's not, there's not like, combined with the uh, inherent randomness of the seed stage investing, like, like asset class, like there's not an obvious clear arbitrage that's just lying there to, to take advantage of by, by any kind of anything that would appear in a deck.

Speaker A: I think that folks who maybe don't look at pitch decks all day might find it hard to believe that there could be a 13x gap between a uh, 65 pre versus a 5 pre valuation startup. You know, you look at it and you're like, well how Big of a difference can there be? But when you're qualitatively looking at it or quantitatively and you're looking at different signals just on founder quality, pedigree, traction, market competition, you know, growth, like all these different variables that would, would show up, usually companies that are raising at ballpark 5 million. There are very good reasons why it's priced around there and vice versa, you know, for the know, top decile startups that are raising. So I thought that research was really interesting. I also find it fascinating because there are so many GPs like VCs who are just dogmatic about, as you kind of alluded to, like people who, hey, we do, we invest in the best founders, period. We invest in repeat founders only. And then you have ones who are like, we only do deals at 10 posts or smaller, you know, and that's dogmatically about it. And what's interesting is like actually you could kind of pick any of these boxes and so long as you're investing well in any of them, like you could seem to do well. But the, the level of conviction that people have about how their, their way of doing it is the superior way when the data, you know, that you put out kind of flies in the face of that is, is interesting.

Speaker B: I mean, yes and no, right? Because one of the things that's become really clear, I mean it's, it feels so dumb to say this because it's like, uh, you know, you get kind of that the, the, the dumb guy, the average guy, the smart guy meme, right? Where I like to think of myself as a smart guy, but right. It's like adverse selection really matters in venture, right? So you have the dumb guy being like, well, is it the founder talk to you first and then the person in the middle is like, oh. But like it's actually a complex set of factors that go into making a great seed investment. The smart guy's like, yeah, it's adverse selection. So like it's really, it actually in some sense is a universe equilibrium. Sort of makes sense that everyone would be like that. You'd have a bunch of gps that are convinced that their own weird idiosyncratic area is the right thing to do. Because like, you know, you really at seed, given the volume of companies and stuff, you really can't be someone's, you know, top three person they email about their new venture for every single startup. And so I think you actually have this like weird matching equilibrium where everyone is like, oh, I'm the person you talk to if you're raising it sub $10 million or I'm the person you talk to if you're starting a company in Austin. I'm the person you talk to if one of your founders is Canadian. Like I'm the person you talk to if you're doing you know, small molecule biotech in this exact way. Like you get this and like, and that's the way to do it and like that you actually get this. Like it actually makes sense from a universe perspective that you would have because adverse selection is so prominent. It actually does not make sense for someone to be like galaxy brained. Like oh actually you know, it doesn't really matter what we invest in. So we'll invest in anything. And uh, we're open. If you just send us an email we'd love to evaluate it because like then you're always someone's like 50th email. And so the only emails you ever get are from companies that people who are the actual sort of domain experts have passed on and, and you end up building a terrible portfolio. So I actually think there's a uh, it, it's funny because there's like you are completely correct on a local level. There's absolutely no reason like I'm going to invest in only companies that are, you know, the, the person who only invests in the most expensive prestige opportunities and the person who only invests in like companies they view as undervalued or whatever. Like they're pro, like ex ante, you know, they're probably both going to have great portfolios. Right. And but the person who's like oh actually like I don't even have a niche, you know, because like everything's priced in so I'm going to take whatever opportunity comes to me. Like that's the portfolio you don't want which is, I don't know, it's crazy to think about that as like there actually is a, an extreme amount of logic for being irrational in the way that GPS are.

Speaker A: What sustainable edges do you think exist among gps kind of with that worldview?

Speaker B: It depends on what you define as sustainable because I think sustainability in this weird asset class that we're in is probably more on the order of like two or three years in terms of anything sum because I think sustainability is probably driven by network effects more than anything who you know, really matters. But uh, there's a lot of turnover in these jobs. And you know, I think about for instance, you know, my own personal seed investor. I'm not doing any more seed investing but like I was like pretty Good at it like eight to 10 years ago. And I like, I, if you gave me a seed fund now, I don't think I do a pretty good job with it. Like and then you see also as well like kind of a progressive like folks that do a lot of seed investing and are like kind of the pinnacle of seed investing and then it kind of like they burn out for whatever reason. Right. You saw with um, I mean way back in the day, like way back being like 15 years ago maybe there was Harrison Metal and Google Ventures and they stopped doing that more recently. Founders Fund was like uh, we had them pegged as one of the very best, most frequent awesome seed investors and I guess they stopped doing seed investing. I also kind of wonder on an asset class level if there is something that's just inherently burnout prone in doing seed investing because you have such a huge gap between like when you actually wrote the check versus when you see sort of the benefits of writing that check. And I do think like, you know, what you sort of perceive. Just speaking to my own personal like seed investing opportunities, like I've spent a lot of time in my life with companies that like didn't go anywhere that I thought really highly of, that I worked hard, that I like really gave it, you know, didn't really, you know, and, and I do want like, whereas like the companies that like kind of seemed indistinguishable from the other ones, they've done really well. Like I actually haven't gotten the chance to spend a ton of time with them probably because they're crushing it so hard that they got to meet other better people really fast. And so it's like, I don't know, I think that that dynamic does lead to burnout. You know, I think when we talk about sustainability from seed investing perspective, I think it's a pretty short lifespan. I don't know, maybe that's a different perspective than you sort of wanted from that question. But it is a very good question and it's something I, you know, I think about and I grapple with quite a bit actually in terms of thinking about what, what sort of seed looks like as an asset class.

Speaker A: I listened to a talk that you gave recently and one of the things you mentioned to go back to kind of the valuation decile piece, but also maybe just adverse selection about being contrarian in startups and how one element of it that's fundamentally different than a lot of other markets is the need for follow on funding. And you made a really interesting point around how while being Non consensus and commonly discussed being non consensus and right is the biggest payoff in investing across all spheres. But what's different with startups is if you're investing in something extremely non consensus, most likely in 18ish months, they're going to need to go back and get additional funding. And if it's so non consensus yet hasn't shifted into consensus by that point, it's probably not going to get funded. And that is a really interesting wrinkle to startup investing. And uh, I'm obviously leading with some of the points you've already made, but I'd love to get you expanded and rolling on that because I thought it was a really interesting point.

Speaker B: I think it's one of the most interesting dynamics about seed as an asset class is like, yeah, in general, virtually every startup you invest in will need to raise more money. And the easiest way to raise more money is like, is to be a popular company that has an easy time raising. Like that company is going to have the, just will tend to be the, you know, two or three years from now will tend to be the easiest company to raise money in the future. Whereas the company that had struggling to raise money now will probably struggle to raise again in two or three years. And so yeah, I think, you know, I said this a little bit facetiously or like I've given talks where I've said this feature, but it's because there is a tie and it defends some people, right? Because you know, ultimately these are financial securities, these are real assets. Like they do tie. Eventually, you know, hopefully the company gets, does exit or does get acquired or does, you know, IPO or something. There is a tie to the actual real economy. But it's, you know, kind of all the way back telescope, all the way back to seed. Seed does look a lot more like, it does look a lot more like the, the market for vintage Rolexes or cool Air Force One shoes than it does for municipal bonds. And that's because it's a popular consensus kind of perspective on value as opposed to some objective technical perspective on value. And I think what that means, few ask for that. But one is in a nutshell, that's why being contrarian at seed has very little value. If you can't support that company for the amount of time it takes to become a popular idea, which could be quite a bit of time and quite a bit of money, like, it's just, it's not worth doing it because if you go and invest in a bunch of unpopular ideas you think are cool what you have in three years is a portfolio that's going to be staring down a lot of go to zero write downs. And only, you know, there are only very, very rare cases where you see companies that like startup companies sort of figure it out or have enough revenue coming in the door that they like, oh, raising again becomes an option. And then yeah, those are great stories and those are in fact really huge gainers. But I don't think um, that's sort of not the way I think to handle the asset class. So it is like yeah, I think that's such an interesting perspective. It's like you have to go finding the companies that other people think are popular is a really good way to do it. And I think it's one of the things that sort of coming at this asset class from the perspective of a startup founder, um, I was always super irritated by meeting VCs and having them just be like, well it was so cagey. Either at the sort of they would ask at the start of the meeting or they'd ask the end of the meeting. They'd be like, well, who else is investing? I actually came to prefer when VCs would ask it at the start because at least it felt much more transparent. Whereas you would spend 45 minutes going through your plans and your go to market market and your progress so far and how that pilot's going and how close are you to the contract and can this tech really scale? And then at the very end who else is investing? Clearly that was the thing they were thinking about. They weren't paying any attention, they didn't care about your company. Who else? That was the thing I came to ask. I would love to have data that would suggest that that's an awful lazy way of doing venture capital. And in fact the data points that that is actually like trying to ferret out a common signal by understanding who else thinks this is a good idea. In fact a really fantastic way to do seed stage investing. And that uh, the VC who looks like a lazy frat bro is actually a really like that is a correct way to handle venture investing which um, yeah, it's been kind of sad frankly getting that result from the data. But it has in kind of my seven years at AngelList, I think my perspective has really shifted from one in which I thought VCs were really dumb and bad at their jobs and, and that you know, just need some, the appropriate amount of data to like prove how bad VCs are at their jobs to one where I actually like grudgingly have gained a tremendous amount of respect for VCs, specifically seed stage VCs, for doing the really, really challenging job that they do.

Speaker A: Actually, on behalf of all seed stage VCs, we'll take that, thank you. I'd love to talk about an awesome paper that you wrote on check sizing. We were talking about it before the show. There were multiple really interesting insights coming out of it. Maybe start with the headline one, which was that small checks, relatively small checks from VCs outperform other checks they write. And maybe we could start there, you could speak to why that's the case.

Speaker B: Yeah, so I think this is one of the things that has sort of reinforces my, again, little like vintage Rolex perspective of what seed stage investing is, which is that like in a normal asset class, in a normal kind of financial market, you have this idea where you essentially scale check sizing to quality of opportunity. So, you know, if you have a really, really good opportunity, you'll sort of, you know, have some other constraints. You'll come in at size. If your opportunity, you perceive it as being a little bit less good, you'll, you'll write a smaller check. This goes back to like the start of quantitative finance. You know, I mean, that's, that's really like the Markovitz portfolios are really about how you scale check sizes given risk and reward the calorie criterion, which I love, you know, and a lot of people who do this stuff, love is around scaling checks. So you put less money behind worse opportunities and more money behind better opportunities. And like, in some sense that's sort of what I expected to find when we were looking at the AngelList data. So one of the cool things about Angel List is that we can do this research. I'm like, okay, let's take a look at every GP who did at least five seed investments in a given year and try to understand what a big check size would be for them as opposed to like using anecdotes. We can do hundreds and hundreds of GP year examples as our input data for this, which is like essentially a large enough slice of the universe that we think that there's not really another conclusion that you can draw. And so the question is, you'd expect naively, or if, uh, seed investing was a normal asset class, you'd expect small checks to do the worst. Because I think pretty highly of our gps. I think they're pretty good at their jobs and I would assume that they'd be able to assess quality decently. And so if you assume small Checks, worse opportunities, those should be the worst performing. And in fact what we found is that those are in fact the best performing checks. And the reason small checks are the best performing is because they're in some sense actually a very high conviction signal. So what we mean by small checks in this context is that it's uh, less than half of a GP's typical seed check that they'd write in that year. So again, a normal, you know, I write 250k checks. This is a company I'm only writing 100k check to. The reason why a, uh, GPU would write a 100k check on that company is actually you. Like, one reason, the naive reason would be, well, they think it's an okay, but not great opportunity. It's worse than their tip opportunity. We'll write a small check. The actual reason they're running 100k check is they asked the founder for 250k allocation and they got crammed down to 100k check. And actually like, they feel strongly enough by this company that they're like, okay, I'm willing to take the 100k check, even though I really want to be writing 250k checks. And so actually it's like the actions of other people are causing them to write a, uh, smaller check and that those smaller checks, because they carry this sort of consensus signal for being a hot deal, they're popular. Again, going back to the idea of, yeah, the company that you'd expect to have an easy time raising money in three years is the company that having an easy time raising right now. There's no better indicator that a company's having an easy time raising now than they actually have to turn down money from people who are like, who want to invest. And so, yeah, I think the small check thing is really, is very, very counterintuitive in the sense of like, it does not align with a typical outcome for a, uh, typical financial asset, but is definitely in the data and is the. And it's also in some sense like if you think, you know, I tend to think about the universe as pretty efficient. And so like, you should always be skeptical if you're like, this is a source of alpha. Because in general sources of alpha tend to be exploited. And this is one, this is a source of alpha that can exist, right? Because it's like the things that you should be putting more money into are the things that you cannot put more money into. Like, that's, that's fine. Like, that's, uh, a, that is a. I've not broken the universe and created M. And we're not like suggesting there's some like magic money pump here because so in some sense the outperformance from small checks is like allowed to exist in, in a, in a universe with, with no arbitrage conditions. So yeah, I think, I think it's a, it's an interesting result for sure.

Speaker A: I think that leads to a natural segue into the large check piece and the takeaways that you had from, from that side of the research as well. Would love to, to hear about performance of large checks and how that shook out relative to your expectations.

Speaker B: I think that's actually maybe even a more interesting side is, is large checks because you know, uh, again, small checks can be a little bit complicated, right? Because there's a lot of reasons why someone might write a small check, right? Maybe they do actually not feel as good about the company or whatever. But there's only one reason someone write a large check and it's that they have a bunch of conviction. So again like we're. Large check here means more than twice as much as a typical seed check you write in a year. So you typically write 200k checks. You're writing a 500k check. To this startup, I think the GPS we look at are pretty good. I would trust them that they like when they think something's a good investment. I would be like, oh, it's probably a good investment. What we found was that large checks were pretty much identical performing to typical size checks. And the conclusion from that is a couple. It suggests that any sort of idiosyncratic signal that a GP gets about a company that makes them want to write a big check is like countered by the fact that that capacity was there for them to take in the first place, that a better investor didn't take that capacity. And so it opens up the opportunity for a gp. Like I think that to me is like a really fascinating result because it suggests that like here, here between the small checks and large check results, what we haven't. This shapes the universe, right? It suggests that idiosyncratic signal. I want to write a big check in this company because this is like I know this area really well and this company is the company that's going to win. It matters. Zero and common signal, which is like who else is investing in this deal, bro? Is the thing that really matters for future returns. And so that's really this paper on something that seems kind of innocuous, right? Check sizing is actually I think quite significant in terms of what it reveals for the asset class and really is why I think it's much closer to vintage Rolexes than it is to a normal financial, uh, asset. So it is surprising. But there's some implications from that in terms of thinking about, okay, if idiosyncratic signals don't matter. I think the kind of broader project of a quant disruption to startup investing will never happen or won't happen from the same way that systematic investing has disrupted traditional financial assets. And it's because the idea of, like, getting your team of quants to, like, figure out these cool signals based on proprietary data and then like, investing idiosyncratically to like, find the undervalued opportunities is like, not. That's not the way seed investing works. You know, there is data that would be really valuable to help seed investing, but that data is like, who are the companies that are meeting a lot of VCs right now and getting a lot of term sheets and, like, try to invest in those companies? Like, that's the data that would be useful. Not, you know, oh, we have like satellite data that's looking at parking lots. Like, that's not what matters at seed.

Speaker A: Is it possible that the lack of edge or alpha or outperformance on the large check could be some kind of middle ground between. So the positive, you would think if there's outsized conviction or expertise, you would think intuitively that should show up in better performance on that check. But the signal or the, the implication from small checks performing so well as a result, most likely of rounds being very competitive in the signal with that, like, is it possible those things kind of net out as far as their straight adverse selection on the, the capacity for awards check? But on the other hand, the netting out piece is like, well, maybe there is a lot of conviction here and, and there's a positive to that and it just lands at where a typical one does.

Speaker B: Yeah, I think that's what's happening. I agree. Like, the idiosyncratic thing is not a purely negative because it's not like large checks were worse, but they're not better. Um, and so I do think there is a netting out. Like, you have the, the, the two factors. You know, one's positive, one's negative, you know, whatever they are more or less canceling each other out. I think that is what's happening. But yeah, if you had to pick one, would you rather do a seed stage investment that you really believe in or a seed stage investment that everyone really believes in? It's better to go for the One everyone believes in. Which is like, yeah, I mean, that's interesting, right? Like, that's certainly like, yeah, that's an unusual finding for an asset class.

Speaker A: You kind of alluded to a couple times your opinions change on different ideas, perspectives over time. And you mentioned know with the small check piece when you publish that, like, I actually don't know that I love the conclusion of this, but I love that you put it out anyway and you're, you're running with that and put it out in the domain and helping investors and founders be better informed with it. What are those internal or monologues? Like when you do a deep piece of work, the result is like, oh, bummer. But there's a great insight here. But I guess this isn't what I was hoping for. What does that look like?

Speaker B: Yeah, it's a, that's a good question. I feel like, you know, so I did my PhD at Carnegie Mellon in Pittsburgh. Like I would, I want the results, I would love for the results to be like, oh, Pittsburgh has all these exciting startup opportunities. You know, we need to look beyond the Bay Area. There's so many undervalued companies. You know, it's not, it shouldn't just be a cabal of Stanford frat bros that are like controlling this asset class or whatever. Like, I'd love for the results to be pushing in that direction and they're just not. I do have a PhD. I feel like I have an obligation to kind of report the truth as we can best find it. Um, but on a personal level, it has been kind of a little bit disturbing to see so many of the, what I perceived as the negative things about the asset class actually come out as being totally rational in the data. I've had some of these things where we were looking at, uh, illiquidity in the asset class or something and I got this result. I still remember this because it's such a bad feeling from it. I got this result that, oh, according to this data, good seed investors are sitting on a highly appreciated portfolio that's not really growing in value and just praying for exits. And then I thought for a second I was like, oh, that's my portfolio. Oh, good. Um, um. I don't know. I guess to be most charitable, it's a testament to the quality of the data set that I have the privilege of working with that I get results that depress me. It is tough. Like I sort of wish. Yeah, I mean, I wish the world were a certain way. It doesn't appear to be from our Data and, but I do think we have an obligation to sort of report on that. I do think like I kind of wish that we had more, you know, contrarian results some, some of the time because I feel like a lot of the results I found from the data actually do align pretty well with like conventional venture wisdom. And so it's like, you know, it's, it's not really a net positive to the universe for like what we've done because it's, it's like people are like, oh, like it's hard to get headlines about the research because it's like oh yeah, everyone knows that though. And you're like, well yeah, but I like, you know, empirically validated it based on this enormous data set. And everyone's like yeah, but like that dude said that that one time. So you know, that's, it's true. So I think that is like a little bit of a challenge when we, when we think about uh, data driven stuff is that. I would love to.

Speaker A: Yeah, I feel like I kind of took us down a little bit of a dark path with that question to flip around. Is there an insight result from your research that came out that you were like, love it. This makes me so happy. I look forward to sharing this and this is great.

Speaker B: Yeah, I think it goes back to my, my, my first kind of big result from startup growth and venture returns. The white paper we wrote back in the end of 2019 about suggesting that seed, like I think that early stage venture is actually three asset classes, seed, series A and B and kind of like B and beyond and those asset classes correspond. In this paper we suggest that those asset classes correspond to breakpoints of the alpha parameter of the power law of returns from investments. And essentially like seed has an alpha less than due power law with these really, really wild outcomes. Series A and B ish is kind of like intermediate alpha parameters between two and three undefined variants defined mean. And then later stage investing is you know, depending on, kind of like it looks sort of like maybe a slightly more wild public markets, um, actually of those three assets. And like what's fascinating, super interesting about this asset class is that like if you're, if you're, a good seed investor, your investment actually goes through four different asset classes. Right. It goes from seed to series A to like late stage to public like you get to go on this crazy journey with different attributes and it's like yeah, that's, you don't just get to buy a municipal bond. But yeah, I think that's the most interesting Result. And the implication of that is like, really, like, people hate the, like, I love it because that's the one super contrarian thing. People hate the result. Uh, or at least find the result to be irritating in a way that I love pressing on, which is that, um, you know, like, it's almost like a trick question, right? Uh, would you rather have a portfolio of 10 companies with larger checks or 100 companies with smaller checks? And like, you know, people are like, well, actually, you know, they should be around the same expectation, but maybe there's a question about variance. And you're like, nope. Like, the implication of an alpha less than 2 power law is that the sample mean increases in nature. So it is actually, we believe, like the implication of this is all is that you should actually get a higher sample expectation from the hundred investment portfolio than 10. And people are like, that's not possible. In general, that's true because of linearity of expectations. But The Alpha less than 2 power law has this magical property where it does not have a defined expectation and therefore it is not subject to the linearity of expectations. And, and so you get this crazy result where you make more investments. You should get higher average returns, which is like, what that means is that is absolutely unequivocal. Bigger portfolio is better at seed. Like, I think that that to me is like the real kind of controversial finding because people like concentrated portfolios.

Speaker A: I normally end the show by asking, what's a conventional viewing venture that you think is BS? But I feel we've covered 10 of them today, so I don't know that you need to throw another on, but this was great. I enjoyed talking to you so much about this stuff. And yeah, thanks for coming on. Thanks for all the research you put out and do for the ecosystem.

Speaker B: Yeah, I feel so privileged to get to sit on this giant data set of these outcomes. It's a really cool thing I get to work with. And um, yeah, I sort of view the research as a way of sharing some of that boon with the larger community because I think there are some cool lessons that we can learn from the data. And I love finding them and I love sharing them and to you or to any of the readers or listeners of the podcast, like, if you want to shoot me an email, you have a question you think we answered in our data? Uh, shoot me an email. Uh, I love when people have, uh, ideas for stuff that maybe our data set can kind of uniquely answer.

Speaker A: Thanks for listening to the show. If you're enjoying it so far, please tell a friend or give the show a five star rating. It helps. One more thing, investing in startups does not have sponsors, but I want to give a shout out to one of our portfolio companies, Packsmith. Packsmith is the all in one e commerce platform built for brands with unparalleled transparency in your fulfillment operations, unique packaging customization options, and up to 80% faster delivery at rates your 3 PL could never match. Pacsmith is a logistics solution built for the future of ecommerce. If you're a growing ecommerce brand on Shopify looking to optimize your brand's distribution and sales for scale, head to Packsmith IO to learn more. Thanks again for listening. Joe Mega is the founder and Managing Partner of Seaplane Ventures. The content here is for informational purposes only and should not be construed as investment, legal or tax advice. The opinions expressed by guests are, uh, their own and do not reflect the views of Seaplane Ventures. Our host guests and colleagues clients may hold investments discussed in this podcast. Please invest responsibly.