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Success Story with Scott D. Clary
Lessons - The Hard Truth About Monetizing Data | Jager McConnell - Crunchbase CEO
00:14:55
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- [00:00]
A
In this Lessons episode, explore how a data driven company turned a free platform into a scalable subscription business under pressure. Discover how early monetization validated demand before product perfection. Understand why owning distribution became a critical growth advantage. And uncover how layered data systems and partnerships built a durable competitive moat. Let's talk about the strategies to actually build that model out. So day one, so you're like, okay, so we have access to all this data. People want access to this data. We're going to sell them a subscription to access this data. That makes sense. You're building, are you building a marketplace or do you have so much data already that you actually don't have to worry about the data side of it? You have to get. Because I know there's a whole bunch of components, right? Like as a user looking for data, I subscribe, there's a monthly recurring. But also I'm assuming at the beginning you probably didn't have every company properly filling all the information about them. So the data wasn't 100% complete. And I know like now it's probably advanced, it's probably some sort of black box machine learning AI algorithm that figures it all out. But that wasn't day one. So how did you first start building it out?
- [01:11]
B
Yeah, so it's a great question. So when we, when we first spun out the data was not that great. It was almost entirely user generated data which now today it's less than 10%. So we over time made a big shift but we didn't have time to fix the data. We only had about a year, year of Runway when we spun out. And, and so I had a year of Runway to change our business model. Change the team, go and build the software that, that I think people might buy, sell the software to show traction and raise a series B before we're out of money. So it was, it was a pretty stressful year that first year, you might imagine. And, and it was, it was hard because you know there was, there was only so much we could do with the skills that we had and the bandwidth that we had. So the first step was let's build the thing that just to see if anyone who has had this free tool would be willing to pay money for something else. So we built essentially a prospecting search tool. Basically lets you do very complex advanced searches of the data which didn't exist before as more of a lookup tool. I hear it before it was, I know a company, I'm going to look it up now it's, I have a certain type of company in mind which companies match that description and then if there's new companies that match that description, let me know. Like now there's monitoring. So it's give me a news alert, give me a funding alert, give me a new addition, new company that didn't match this criteria before, let me know immediately. And that's what we launched. Almost exactly a year after we spun out was Crunchbase Pro. Now we're charging 49 bucks a month and it was like, okay, well is this going to work? Because now we put it out there, I can announce it TechCrunch Disrupt and if no one bought it, we were out of business in like two months, like, like maximum. So luckily people did buy it and we were able to raise a series B from Mayfield shortly after.
- [03:04]
A
And okay, so as you're. So how did you get your first, say 50 customers on that? First hundred. First hundred customers. It was just through like you leverage media, I'm assuming because you had TechCrunch, you had TechCrunch disruption. So obviously you do have a little bit of reach there. But was there anything innovative, any marketing strategies, anything that you did that was a little bit different to actually acquire users?
- [03:24]
B
Well, this is, this is the sort of secret strength of Crunchbase is we already had 20 million people coming to our website, right? So they are already coming. All we really have to do is market to the people that are already coming to site and this will always be our strength. Again, I mentioned earlier 80 million people using Crunchbase, can we go and sell them something is so we don't have to. Our marketing budget relative to other companies our size is quite small because we are just trying to leverage our strength, which is people coming to site. And now it's like, well, who are the people we should sell to? Who shouldn't we sell to? Are we trying to sell them the big thing, the little thing, the medium sized thing, all that sort of funnel while trying to impact the user experience as little as possible so that the people that are getting value for free continue to get value for free. We don't want them to go away, we just want to with a rate of evolve into to a little bit further in their career or a little bit further in their prospecting. They pay us money.
- [04:22]
A
And then what?
- [04:23]
B
All we did was put up a toaster on our website saying, hey, check out crutchpace Pro and here's a video and showing you what it does. And again, by the time so we turned backstage at TechCrudch Disrupt, I'm about to go on stage to announce this new product, we had already sold licenses, but in the time that we turned it on, five minutes before I walk on stage, just because people were so eager to buy from us. So it was, it was rewarding because when I went on stage, I was already jubilant because at least someone had bought it and it wasn't my mom, you know.
- [04:55]
A
No. That's amazing. And, well, I mean, there's a lesson in that, in and of itself. I mean, if you like every company I believe should be a media company, like technically you leverage the 20 million people that were already coming to your site, you didn't have to, you didn't have to find a new audience to Target or a new, you know, a new user base at Target, which is very important. So I mean, that's, that is a lesson for startups. Obviously if they don't have 20 million people hitting your site every day, they gotta figure some way to monetize. But ultimately, if you become a media company, if you build masses, you can find a way to sell into that audience too, which is something that you, you, you did day one. But the other thing that you probably wanted to optimize is the data. So I'm curious, when you first launched that product, was the data valuable enough for people to pay for? Did you find out which data people would actually fork up some cash for and, and what was not acceptable?
- [05:41]
B
Yeah, it was a scary learning for me because when it's a lookup tool, you look up a company, if you've heard of it, the data is probably pretty good because it's probably a pretty well known company. But when you have a discovery tool, and now people are prospecting for companies just based on a set of criteria, it shows all of the bad data. So for instance, you could say, show me all the companies made before 1900. And it's like, okay. And then you see like we have companies from like negative 32 BC. It's like, what is that? I don't even know what a negative year is. And obviously it's not right. So we had a huge cleanup project where we just had to do all the stuff that we thought people might do to sort of figure out what data might be exposed as horrible. And for me, that flipped a switch on. We have to invest more on our data once we get funding to go and change how we get data. So it can't be user generated because you get squirrely things from people doing weird stuff like giving themselves a hundred billion dollar funding round. It's like, okay, we need to go and put some controls on this, which is now what we've done. So you asked a question earlier about Marketplaces. That was actually the next thing we did after Pro. Well, we re platformed the entire data set, or sorry, the entire website, the entire application. Because we had inherited this thing that was pretty terrible. So we had to rebuild the whole thing from scratch. Now that we have proven this prototype that worked and we were able to sell, the next thing we did after then was Marketplace, which allows us to go and integrate all sorts of data sources into what Crunchbase is. I can talk for hours about how we get our data and how data works, but the net net is we expanded the data from not just user data, but we also formed thousands of partnerships to go and get data in from governments, accelerators, VCs, data providers. All of that is flowing now into Crunchbase to make a unified profile.
- [07:39]
A
Yeah, I was going to say there's a couple of ways that we could take this because I wanted to have some great startup lessons, but then I'm trying to like bridge startup lessons plus the conversation about data because I saw one of your previous, I mean, like it all sort of combines. I mean you've built this incredible platform. We're talking about data I'm curious about and maybe I'll just let you speak about all these different topics. So like data security, what people feel comfortable aggregating, especially if they're not. If it's not user generated gdpr, Castle, all the different data compliance items that you have to be careful of and cognizant of. What else? Also the fact that you use all these different partners. So I would say let's talk about all the different data things that I'm sure you've dealt with. And then also all the different strategies you use to not just collect data, but you. I know you also use partners to build out the organization because you've used all these different. All these different. You have like, I don't even know if this is the case still, but at one point you didn't have your own QA team, you had a partner for qa. So not only do you have all these partners for data collection, you like you built a business with partners so that you don't have to deal with a lot of those internal costs. It's another interesting strategy. But first let's talk about data. Then we can go into sort of business growth strategy. So talk to your data. All things data.
- [08:52]
B
Sounds good. So let's start with just how we get data. So Today we still have a great million user plus community of people who just put in data into Crunchbase. Why? Because they want to be well represented on our platform. If your company is wrong on Crunchbase, investors are going to miss you, they're not going to pay attention to you. Job seekers are going to think that you're a dead in the water or you're not growing or not as big as they thought you'd be. All those things require you to update your Crunchbase profile. Because our brand matters in the ecosystem. Just like you keep your LinkedIn profile up to date, it doesn't matter which other profiles are out there about you. LinkedIn, you keep up to date because that's the one that matters for you as a person. Crunch piece is the parallel for a company profile. So that's one aspect. Then we've got, as I mentioned, about 4,000 partnerships with governments, accelerators, VCs all over the world who give us that data. Why? Because these companies, these governments, these VCs want to be well represented, our platform again, they want to look like tech hubs. They want to be, look, look like they're matter, that they matter and that are active. So they give us data directly. We have about 60 data providers that go and stream data into Crunchbase. That's massive amounts of data. Like you think about, like G2 crowd, like they've got all this data on products, those are tied to companies, so we're able to go and absorb that into Crunchbase. So you have sort of this one stop shop that has all these different data facets coming together and there's no way we as a company could go and get like, as our core competency to go and like generate all that data. There's entire companies that do that. Let's just absorb that data in a Crunchbase and they're again willing to do it for us because of our brand and they want to be well represented. Some, some of our partners you've never even heard of, like a lot of people haven't heard of Bombora. They give us intent data. That data flows in a Crunchbase, so you can merge it with other data sets. So that is another aspect of what we are. So no one in the world has ever combined all these data sets into one unified Prof. Before, and now you're able to do prospecting against all these different flavors of data all at the same time. And that's very, very powerful. So that's three. The fourth way is our machine learning, our AI systems. So that is a combination of crawling legal sources of data for us to go and get data from. And that's a sort of table stakes. But some of the secret sauce is we also generate a lot of our own data based on what we see from all these other data sets. So even from our own usage. Right. So if everyone's flowing to a company profile page to go and check it out, we're, that's probably an important page right now for whatever reason that helps drive our trend scores and our growth scores and our sort of recommendation engines. All these things are looking at which, which data has impacted funding rounds. Are there more news stories? Are people tweeting about this company a lot right now? All those things drive into does this company matter or not? And that helps figure out which companies we should prioritize. So that's the fourth way then. The fifth way is we have a team of about 20ish people who work for Crunchb and they manage a team of about 250 people overseas that go and do manual cleanup of data. Those automation, the AI systems flag things that I can't figure out, is this spam, is this bad, is this good? It kicks it over to the humans to go and add a human brain on top of it to go and clarify. So we spend like $20 million a year just making the data as good as it can possibly be and of course expand it all. That is a combination of those five things. What's beautiful about that is no competitor out there can do what we do. Like, I don't care who it is. There's no one who has all five of those things and can get themselves to a place where they can compete. A lot of people like, oh, I'll just crawl and I'll be crunch space. Yeah, good luck.
- [12:28]
A
So I asked like a, I did a horrible thing. I asked like a compounded question. So there was like 10 other things that I asked. But I don't want to let you go on because I actually want to just pause you here and just down on one thing you mentioned and then we can keep going. So the one thing that I realized is that you became, you became, you've mentioned this a few times, the source that people want to represent themselves on. Yeah. Now that's, that's incredible because if you even look at what you said, you, you, you get data from G2 and I don't know all the different sources you get data from, but G2 could even be considered a competitor, but technically not because they're feeding data into you. So how in the world did you become the person that everybody wants to be represented on because that, that is magic. However you manage to do that, that's incredible, that market position that you're in.
- [13:15]
B
And I think it really comes down to like G2. It's definitely a partner, not a competitor in our minds. As an example, you're going to go there.
- [13:23]
A
You know what I mean though? Because, like, they also represent companies, right?
- [13:26]
B
Totally. But you would Never go to G2 to like, figure out if they've got funding, you know, like, or if. Or if they. What their website traffic is. Like, you'd never, you would never think to go there. You say, oh, well, I'll go to a similar web or an Alexa for website traffic data. But no one had combined it all together into one place. And that based on our roots, that was very easy for us to do because when our. The use case for at the very beginning of Crunchbase was what the hell does this company do? I have no idea. I'm going to go look it up by Crunchbase. I'm going on a date with someone. They work@fiddlesticks.com like, what the hell is fiddlesticks.com to do? You Google it and Crunchbase comes up and then you go and look at it. That base level that what I like to call the master record of a company was already what Crunchbase was. We didn't have all the companies, but for the companies that we did have, we were the master record of companies. And then with that framing, then we can go and take all these different facets of data, like G2 products and plug it in. And G2 gets excited because we're going to give, we give it brand recognition as G2's data. Here it is. Click here if you want more data from G2 Crowd. So they see us as a lead source. Happy to do that because they're providing value to us.
- [14:36]
A
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