How I Invest with David Weisburd
00:10:16 · David Weisburd, Jerry Ye
[00:10:16] S0: What exactly are you looking for when it comes to revenue? [00:10:19] S1: Might be helpful to take a step back in terms of what I'm talking about for, say, like, card panel data. Right? So there are data providers out there that basically act as, like, the interconnect between your banking account and your brokerage. And they, as a side business, resell this, and a lot of hedge funds buy it. Right? Sometimes this stuff is actually real time, and hedge funds will pay $7.08 figures a year for this. Venture on the other end, because the time horizon is ten years, the ROI is not is not the same. Be happy with, like, a delayed panel. Right? But you're literally talking about three to 5% sample of all US credit card and debit card spend. Right? And with that, not only are you able to figure out, you know, how the corner Starbucks is doing, like, who's coming back, how... What the retention rates are. You're also able to figure out what, you know, OpenAI is looking like in terms of revenue on the consumer side. These are generally consumer type card panels, but there are some that kind of focuses on business transactions as well. And for the consumer side, what you can do is try to identify the companies based on the credit card descriptors, which is similar to what you see in your credit card bill at the end of the month. And for these panels, they generally match the stuff with companies with stock tickers or late stage venture companies. [00:11:49] S0: So hedge funds are using this to figure out earnings data before Yeah. They're announced by the companies.
00:11:49 · David Weisburd, Jerry Ye
[00:11:49] S0: So hedge funds are using this to figure out earnings data before Yeah. They're announced by the companies. [00:11:54] S1: Yeah. So interestingly enough, I remember going to a meeting here in New York that this is almost like a decade ago, and it was it was like a dinner with a bunch of hedge funds, and they basically concluded there was no more alpha from credit card data. That's just like how far advanced they were. Right? Whereas still on the venture side, just because a lot of stuff wasn't tagged, right, because it's only tagged for the long tail, I would say the the head revenue, the long tail was not tagged. So there's actually a lot that goes into it that, you know, you can do any resolution to figure out does this square is this square square cafe? Or is it like square? Or is like... Is there actually like a submerchant under there? And it's still largely untapped. You can't feed this into your LLM. Like, you blow up your context window immediately. Right? And... [00:12:45] S0: And that's because there's so much... Just just so so much data. [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.
00:12:49 · 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.