How I Invest with David Weisburd
00:12:49 · Jerry Ye, David Weisburd
[00:12:49] S1: Billions or trillions of data data points. Right? And so there's a little bit of work there. But if you do the the grant work there, you can identify, you know, like, up and coming companies, like, what is inflecting? What what has high retention? Right? And a lot of times, you could figure out these companies before it becomes like a cultural phenomenon or before the media picks up on it or other VCs pick up on it. [00:13:14] S0: And the majority of venture firms, the large firms are using this data? [00:13:18] S1: I think a handful are. Right? Especially the larger platforms. The crossover funds are all definitely doing it. Right? They had 8 figure data budgets with 20, 30 people engineering teams. A lot of the other ones, even on the venture side, large platforms may not be doing it. And all the smaller ones, like, it's it's a dataset that's actually pretty expensive. So they might work with a third, like, a a partner on this where, for example, there was second measure before, and they tag a lot of companies. Most of their clients were venture backed were venture funds, but most of their revenue was actually from the hedge fund side. Right? So they ended up being acquired and kinda deprioritized the long tail tagging. So it's still something that a lot of firms would have to do on their own.
00:13:18 · Jerry Ye, David Weisburd
[00:13:18] S1: I think a handful are. Right? Especially the larger platforms. The crossover funds are all definitely doing it. Right? They had 8 figure data budgets with 20, 30 people engineering teams. A lot of the other ones, even on the venture side, large platforms may not be doing it. And all the smaller ones, like, it's it's a dataset that's actually pretty expensive. So they might work with a third, like, a a partner on this where, for example, there was second measure before, and they tag a lot of companies. Most of their clients were venture backed were venture funds, but most of their revenue was actually from the hedge fund side. Right? So they ended up being acquired and kinda deprioritized the long tail tagging. So it's still something that a lot of firms would have to do on their own. [00:14:10] S0: I love the disciplinary nature of the show because I I get to talk to public investors, private investors, and sometimes these things are so obvious to public investors. You said with hedge fund managers, it's so obvious that there's no alpha there. There's no more juice to squeeze in the public markets. Most venture capitals haven't even heard of this.
00:14:10 · David Weisburd, Jerry Ye
[00:14:10] S0: I love the disciplinary nature of the show because I I get to talk to public investors, private investors, and sometimes these things are so obvious to public investors. You said with hedge fund managers, it's so obvious that there's no alpha there. There's no more juice to squeeze in the public markets. Most venture capitals haven't even heard of this. [00:14:28] S1: When I first went to my first alternative data conference in New York, and I looked around, I was literally the only one representing a venture fund there. Right? And you saw everyone else on the hedge fund PE side. And it it is it is fascinating, but a lot of it is also in terms of what the profile of the teams look like. Right? If you look at venture, most people can, you know, handle looking at, you know, their data rooms in Excel, but being able to to figure out signal from a dataset with billions of data points is actually difficult. Right? [00:15:05] S0: Perhaps it's obvious, but these venture capital platforms, the large platforms, and the crossover investors, they're getting this data because it's essentially ground truth. Because if you know what the consumer and the enterprise is spending on on their credit cards, you know exactly what the next top company is.
00:15:05 · David Weisburd, Jerry Ye
[00:15:05] S0: Perhaps it's obvious, but these venture capital platforms, the large platforms, and the crossover investors, they're getting this data because it's essentially ground truth. Because if you know what the consumer and the enterprise is spending on on their credit cards, you know exactly what the next top company is. [00:15:22] S1: So it really depends on the type of company, but if it is a consumer facing company, let's say, like, an online DTC subscription company, you should have really good visibility into it. And actually, similar to polling what's going on right now, right, there's only a percentage of the population you actually need to poll, and we're talking about a three to 5% sample of US credit card, debit card spend. Right? So depending on the size of the company, actually have a really good idea of some companies once they hit a certain, you know, like, run rate or a certain stage. [00:15:59] S0: And who's selling the status? Are these debt... Data brokers buying from Visa and Mastercard? [00:16:04] S1: So these are generally interconnects between, like, your bank and your, like, brokerage. If you ever sign on and it says, like, connect your other account for, like, external transfers, etcetera. Plaid is definitely not. [00:16:16] S0: Shout out shout out to Plaid, non sponsored.
00:16:16 · David Weisburd, Jerry Ye
[00:16:16] S0: Shout out shout out to Plaid, non sponsored. [00:16:19] S1: Yeah. It's actually not Plaid. Okay. But there's... It it can't be Visa or Mastercard because their agreements are actually with the merchants. Right? And the merchants definitely do not want, you know, them selling the Who is that? There are panels like Yodlee or Consumer Edge. This is all, you know, public information that... [00:16:38] S0: And where do they get their data? [00:16:39] S1: Yeah. So they they form the interconnects for a lot of these companies. Right? Some of them actually buy smaller banks, smaller card issuers, etcetera. [00:16:47] S0: So using this card data, SignalFire invested in Grammarly. Tell me about that.
00:16:47 · David Weisburd, Jerry Ye
[00:16:47] S0: So using this card data, SignalFire invested in Grammarly. Tell me about that. [00:16:52] S1: So as part of the the panel, right, just keep in mind that you can figure out what retention rates look like as well. But we saw a company that was inflecting, and not only was inflecting, you saw really high retention rates, which were similar to what you would see in a SaaS company. And that led to investments there. But what was interesting there was actually, and this kind of ties into what I'm working on now too, is before, from the outside in, that led to the investment in the company early on based on cohort performance. And now, Grammarly actually, a couple years ago ended up receiving a billion dollar user acquisition financing facility from another firm, and they're essentially leveraging those same cohorts, but for user acquisition, that's non dilutive. Right? So it's not an equity investment. And for them, it's actually a short term problem, and this is a short term solution for it because the revenue comes back in twelve, eighteen months. Right? And they don't have to sell a chunk of their company for it. [00:18:02] S0: This touches on one of the most underrated and least talked about forms of funding for startups, user acquisition financing. Tell me about that. What is user acquisition funds?