Matt Kaufman, Head of Operations at Crunchbase, describes building a searchable business graph linking people, companies, products, and patents. Venture firms are hiring data scientists and launching analytics-first funds because structured public data lets investors find opportunities faster than traditional methods.
Chapters
So let me talk a little bit about the future of business intelligence, which is really what this is, right? It's all about finding information about other companies and investors and competitors and people and all this stuff. It's a graph, right? You know, it's all about these things being connected. Facebook, if you think of Facebook, it's a graph everybody knows, social graph, blah, blah, blah, but it's people, connected to people and to events in their lives. The events in their lives tend to be status messages. And when we started thinking about CrunchBase, what we said is, why can't we be the graph for business? Why can't we connect people and companies and products and patents and awards and programs like this and where people went to college and when— when they launched a new product or when they made an announcement or when they rebranded. Why isn't all that in a graph? Why can't I just go ask, give me all the companies that have rebranded in the mobile analytics space in the last 2 years and just pull all the events for brand changes, connect that to companies, connect that to companies tagged mobile analytics, look at the dates and get myself an answer? Like, why can't you do that? And you can't do it today. It's hard. But all this data is public. You know, if you go read a TechCrunch article, and I read a lot of them, every time there's an announcement now, it's like the currency of an announcement to get into TechCrunch is how much information are you willing to divulge. Are you going to say how many employees you have? You know, how many customers? How much money are you making? You know, when are you going to launch your next product? All that stuff, like it's all out there. It's amazing how much information is out there. Yet, if you wanna go find it, it's super hard. My favorite example is TechCrunch has these big awards. I work in the same office as the TechCrunch people. These Disrupt Awards or Battlefield Awards, whatever they call it. Try and go on the internet and find out who's won the Battlefield Awards for the last 5 years or however long it's going. There is no page for that. And TechCrunch is a big business. I mean, those conferences, those are huge businesses. There's no page. And the events team is there. Like, the team that's running the awards is sitting in the office. And I say, so why aren't there pages? And they just kind of look at me. They're like, if there was a place for us to go type it in, certainly we would type it in. But like, we have to plan the next conference. And, you know, we talked to venture firms too. And some of the venture firms come to us now and they say, will you just run our portfolio pages for us? It's too hard for us to keep track of what's happening. We can't track when companies rebrand or when they hire a new executive company or when they launch a product. We just can't do it. Like, if it was just out there and we could just point to you guys, that would be great. So, all this information is out there, but it's just really hard to like pull together. So, at the beginning of the year, and the reason why we've gone from 3 very part-time people to 17 now, and probably be somewhere in the 30s next year, is because we're building this graph. And it kind of looks like this, which is interesting because I pulled this off of a website. Which already map— already showed all the Crunchbase data in a graph. It's not just a cool graphic, it actually is Crunchbase data that somebody took the API and pulled together and did. But we're building a system that handles all of that and you can put in any of that information and ultimately then you can go query for it. So, that's what we're working on today. And so, what you end up with is this definitive business graph. People can do whatever they want with it. It kind of looks like this. It actually looks like a website that was built in post-2010 rather than something that was mid-2000s or earlier. It's all coming together. It's responsive. It does all kinds of fancy stuff. We're going to internationalize it because there is a huge demand right now to have one global database of startups and founders and investors. You talk to the large venture firms and what they'll tell you is, You know, we have offices in Bangalore and in Beijing and in Moscow and Hong Kong and Berlin or wherever else. We have the same essential— essentially the same investment thesis across all these places. Why don't we have a database that pulls all these companies together? We don't want to look in lots of places. Crunchbase, please go build the global database. So we're doing that. So, oh. Open data's impact on what's going on in investing. And it touches on GUSP and it touches on AngelList and all these people. So, hopefully this will answer those questions. There's a lot of people out there right now who are quantifying startups and quantifying the developers and quantifying the founders and quantifying the investors. And they're doing all kinds of stuff with all this open data or public data, whatever you want to call it. Just some examples. People who are integrating analytics into their investment thesis, Sequoia, Greylock, Kleiner, they're just some of the bigger ones and they've been very outspoken about the fact that they have data science teams. So you used to think about it like a data scientist is probably somebody sitting at Amazon trying to figure out where exactly to put the buy button on the page to get people to spend more money or if you just bought product X, what products should we recommend to you that you're most likely to buy after buying product X? Like, people thought of like, that's where the data scientists were. But, you know, these venture firms, and there's a lot of them, are hiring their own data scientists, and they're pouring through data, and they're going through all kinds of stuff about people's backgrounds and, you know, numbers about, you know, how many downloads web apps have and how much money individuals have raised before and where they went to school. And what they're doing is they're trying to find signals that would indicate whether a person or a team or an idea is gonna be successful or not. They're out there and they're working hard and they're spending a lot of resources on it. Not everybody, not all of the venture firms have a large enough fund to support a big data analytics team, so there's other companies which are coming out which build analytics which they sell to the investors, so Mattermark, Seedling, Dashboard, all of them are about scoring all the same stuff that the data science teams at these big firms are doing, but these people are doing it and what they're doing is they're creating a platform and then they're selling access to that platform. And then the other thing that's been really interesting that's happening is that new venture firms are starting based around analytics. So here's 2 examples. Founders Institute, I don't know how many of you have heard of it, They run all kinds of events for founders finding other founders and people, you know, pitch contests and all that stuff. They run thousands of these events all over the world. But in doing that, they've collected all this data on all these founders. So they're raising a fund right now and they're going to use a lot of that data that they've collected in addition to all their relationships that they've built and they're going to use that in order to in order to start a fund, and I think they're gonna announce their fund sometime this year. SignalFire, this is another interesting one. It's a bunch of extremely hardcore data scientists who are building a fund where the centerpiece of the fund is a data engine to help people make better investment decisions. So not only are you seeing venture firms starting to use data a lot more, and every venture firm, whether they're the really big ones or not, But you're seeing new, new investment vehicles being created around this data that's out there and that's open.
