Operating Metrics For Marketplaces

this kind of goes back and helps reinforce the point about data mattering, you know, from the beginning so that way you can kind of learn and make informed decisions. And of course, with marketplaces, as you mentioned, there's kind of trade-offs to everything as well. So.

Yeah, I think I want to, I just want to, since you brought that up, that's another example of a metric I think that tells you where you're operating as a marketplace. So I just talked about like a marketing problem, right? Which is like, I'm going to grow the opposite side. What's the returns to growing the opposite side on this side? There's a complementary aspect of that, which is what I call inventory management. So another question you can ask yourself, it's really the same question as what I just described, but I'm gonna frame it now in terms of not so much bringing in new participants, but sort of retaining and making happy the existing participants. The way to think about that is if you're Netflix and you ask yourself, If Ramesh watches Juror Number 2, great movie, I just saw it a couple nights ago, you know, on streaming, does that mean that, you know, Dimitri can't watch Juror Number 2, right? So basically, does my watching a movie preclude Dimitri from watching that movie? Now, there was a time when it did because Netflix used to ship DVDs out. So if I had the DVD, he didn't have the DVD, right? So that kind of thing was part of the original environment of Netflix where there were inventory constraints. And you could ask the question, what does one person transacting with my platform do to another person who wants to transact with my platform? The math name for this is a shadow price. That's typically what we refer to it as. And really just sort of colloquially what we're saying is the tighter the inventory constraint on the opposite side is, the more likely it is that one person doing something is precluding someone else from doing something, right? And so that's another one of those metrics that you can look at that is telling you something about the health of inventory. So most platforms that are really scaled up are going to look at this regularly. Again, you could see it's a cross-market metric because you're really asking yourself, how does this behavior across the market of one individual influence another individual? It's kind of the level of competition induced by scarcity on the opposite side of the market. This temporally varies. It varies, you know, across space. So, you know, some cities may be more constrained than others for Uber, some times of day, are more constrained for Uber than others, that kind of thing. So it's not as if these are just like point in time, you know, fixed once kinds of metrics. But again, it's another version of a metric you can look at. It's kind of a complementary version of the thing I was saying earlier that tells you something about the cross-market health of your business. And in particular, are you really a market or not? So Netflix today is in a world in which Dimitri is completely uninfluenced by my viewing behavior, right? He and I can watch whatever we want. So Netflix is an example of a platform where they have infinite supply on the opposite side effectively. And it's really only thinking about how to optimize for, you know, the viewers. And, you know, I think what's interesting to think about is, well, what can you, what lessons can you take from a Netflix-like recommendation system for a 2-sided market? And this is the biggest one, which is that a 2-sided market needs to be like Netflix, but with— while respecting the role of constrained inventory. And that's where some of the data science, you know, challenges happen is in translating from vanilla recommendation systems out there into recommendation systems that are appropriate for an inventory-constrained environment.