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Lessons - The Hard Truth About Monetizing Data | Jager McConnell - Crunchbase CEO · Success Story with Scott Clary

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  In this lessons episode, explore how a data-driven company turned a free platform into a scalable
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  subscription business under pressure, discover how early monetization validated demand before
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  product perfection, understand why owning distribution became a critical growth advantage,
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  and uncover how layered data systems and partnerships built a durable, competitive mode.
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  Let's talk about the strategy used to actually build that model out. So
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  day one, so you're like, okay, so we have access to all this data. People want access to
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  this data. We're going to sell them a subscription to access this data. That makes sense.
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  Are you building a marketplace or do you have so much data already that you actually don't
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  have to worry about the data side of it? You have to get, because I know there's a whole bunch
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  components, right? As a user looking for data, I subscribe. There's a monthly recurring. But also,
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  I'm assuming at the beginning, you probably didn't have every company properly filling all the
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  information about them, so the data wasn't 100% complete. And I know like now it's probably
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  advanced and it's probably some sort of black box machine learning AI algorithm that figures it
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  all out. But that wasn't day one. So how did you first start building it out? Yeah, so it's a
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  great question. So when we first spun out, the data was not that great. It was almost entirely
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  user-generated data, which now today it's less than 10%. So we over time made a big shift,
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  but we didn't have time to fix the data. We only had about a year of runway when we spun out.
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  And so a year of runway to change our business model, change the team, go and build the software
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  that I think people might buy, sell the software to show traction, and raise a series B before
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  rav money. So it was a pretty stressful year. And it was it was hard because there was
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  there's only so much we could do with the skills that we had and the bandwidth that we had. So
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  the first step was let's build the thing that just to see if anyone who has had this free tool
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  would be willing to pay money for something else. So we built essentially a prospecting search tool.
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  Basically, let's you do it very complex, advanced searches of the data, which didn't exist before,
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  as more of a lookup tool. I hear it before us. I know a company I'm going to look it up. Now it's
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  I have a certain type of company in mind, which companies match that description. And then
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  if there's new companies that match that description, let me know. Like now there's monitoring.
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  So it's it's give me a news alert, give me a funding alert, give me a new addition, new company
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  it didn't match this criteria before. Let me know immediately. And that's what we launched
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  almost exactly a year after we spun out was country's pro. Now we're then we're charging
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  for an bucks a month. And it was like, okay, well, is this going to work? Because now we put it out
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  there. Again, now it's a crisis erupt. And if no one bought it, we're out of business. And like
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  two months, like like maximum. So likely people did buy it and we were able to raise a series B
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  from Mayfield shortly after. And okay. So as you're so how did you get your first say 50
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  customers on that first 100 first 100 customers? It was just through like you leverage media. I'm
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  assuming because you had tech crunch, tech crunch disrupt. So obviously you do have a little bit of
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  reach there. But was there anything innovative, any marketing strategies, anything that you did
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  that was a little bit different to actually acquire users? Well, this is this is the sort of secret
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  strength of crunch basis. We already had 20 million people coming to our website, right? So
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  they are already coming. Oh, we really have to do is market to the people that are already
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  coming to site. And this will always be our strength. Again, I mentioned earlier 80 million
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  people using crunch space. Can we go and sell them something? Is is is so we don't have to
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  say our marketing budget relative other companies are sizes quite small because we're just trying
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  to leverage our strength, which is people coming to site. And now it's like well, who are the
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  people we should sell to? Who shouldn't we sell to? Are we trying to sell them the big thing,
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  the little thing, the media size thing, all that sort of funnel while trying to impact the user
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  experience as little as possible so that the people that are getting value for free continue to get
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  value for free. We don't want them to go away. We just want to with a rate of evolve into a little
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  bit further in their career or a little bit further in in their prospecting, they pay us money.
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  And then what we always do is put up a toaster on our website saying, hey, check out crunch space
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  program. Here's a video showing you what it does. And again, with by the time we so we turned
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  the back stage at TechCrunch to strap down about to go on stage to announce this new product.
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  We are already sold licenses. But in the time that we turn it on five minutes before I walk on
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  stage, just because people were so eager to buy it from us. So it was it was rewarding is when I
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  went on stage, I was already duplicated because at least someone had bought it and it wasn't my mom,
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  you know, no, that's amazing. And well, I mean, there's a lesson in that ended up itself. I mean,
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  if you like every company, I believe, should be a media company. Like technically, you leverage
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  to 20 million people that were already coming to your site. You didn't have to you didn't have to
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  find a new audience to target or a new, you know, a new user-based target, which is very important.
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  So I mean, that's that is a lesson for startups. Obviously, they don't have 20 million people
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  hitting a site every day that got to figure some way to monetize. But ultimately, if you become
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  a media company, if you build masses, you can find a way to sell into that audience too, which
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  is something that you you did day one. But the other thing that you probably wanted to optimize
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  is the data. So I'm curious when you first launched that product, was the data valuable enough
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  for people to pay for it? Did you find out which data people would actually fork up some cash for
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  and what was not acceptable? Yeah, it was it was a scary learning for me because when it's a
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  lookup tool, you look up a company. If you've heard of it, the data is probably pretty good
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  because it's probably a pretty well-known company. But when you have a discovery tool and now people
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  are prospecting for companies just based on a set of criteria, it shows all of the bad data.
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  So for instance, you could say, show me all the companies made before 1900. And it's like, okay,
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  and then you see like we have companies from like negative 32 BC. So what is that? I don't even know
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  what a negative nut year is. And obviously, it's not right. So we had a huge cleanup project where
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  you just had to do all of the stuff that we thought people might do to sort of figure out what data
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  might be exposed as horrible. And that and for me, that flipped a switch on, we have to invest more
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  on our data once we get funding to go and change how we get data. So can't be user-generated because
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  you get squirrely things from people doing weird stuff, like giving themselves a hundred billion
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  dollar funding round. It's like, okay, we need to go and put some some some controls on this,
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  which is now what we've done. So you asked a question earlier about marketplaces. That was actually
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  the next thing we did after pro. Well, we we re-platformed the entire data set and the
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  outside the entire website, the entire application because we had inherited this thing that was
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  pretty terrible. So we had to rebuild the whole thing from scratch, now that we have proven this
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  prototype that worked and we were able to sell. And next thing we did after that then was market
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  place, which allows us to go and integrate all sorts of data sources into what crunch base is.
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  So I can talk for hours about how we get our data and how data works. But the net net is we
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  expanded the data from not just user data, but we also formed thousands of partnerships to go and
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  get data and from governments, et cetera, as VCs, data providers, all that is flowing now in a
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  crunch base to to make a unified profile. Okay, yeah, I was going to say there's a couple of ways
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  that we could take this because I wanted to have some great startup lessons, but then I'm trying
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  to like bridge startup lessons plus the conversation about data because I saw one of your previous
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  so that mean like it all sort of combines. I mean, you've built this incredible platform,
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  we're talking about data. I'm curious about and maybe I'll just let you speak about all these
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  different topics. So like data security, what people feel comfortable aggregating, especially if
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  you're not if it's not user generated, GDPR, Castle, all the different data compliance items that
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  you have to be careful of and cognizant of what else. Also the fact that you use all these
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  different partners. So I would say let's talk about all the different data things that I'm sure
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  you've dealt with. And then also all the different strategies you use to not just collect data, but
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  I know you also use partners to build out the organization because you've used all these different,
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  all these different, you have like, I don't even know if this is a case still, but at one point,
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  you didn't have your own Q18. You had a partner for QA. So not only do you have all these partners
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  for data collection, you like, you built a business with partners so that you don't have to deal
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  with a lot of those internal classes. Another interesting strategy. But first, let's talk about data
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  that we can go into like sort of business growth strategy. So talking about data, all things data.
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  That sounds good. So let's let's start with just how we get data. So today, we still have a great
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  million user plus community of people who just put in data in a crunch space. Why? Because they
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  want to be well represented on a platform. If your company is wrong on crunch space, investors are
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  going to miss you. They're not going to pay attention. Job seekers are going to think that you're dead
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  in the water or you're not growing or not, because they thought you'd be all those things require
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  you to update your crunch space profile because our brand matters in the ecosystem. Just like you
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  keep your LinkedIn profile up to date, it doesn't matter which other profiles are out there about you.
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  LinkedIn, you keep up to date because that's the one that matters for you as a person. Crunch
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  space is the parallel for a company profile. So that's one aspect. Then we've got, as I mentioned,
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  about 4,000 partnerships with governments, accelerators, VCs all over the world who give us that data
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  why? Because these companies, these governments, these VCs want to be well represented on a platform
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  again. They want to look like tech hubs. They want to be look like that matter that they matter
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  and that are active. So they give us data directly. We have about 60 data providers that go and
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  stream data into crunch space. That's massive amounts of data. You think about G2 crowd. They've
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  got all those data on products. Those are tied to company. So we're able to go and absorb that
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  into crunch space. So you have this one stop shop that has all these different data facets coming
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  together. There's no way we as a company could go and get as our core competency to go and generate
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  all that data. There's entire companies that do that. Let's just absorb that data into crunch
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  space. Again, we're going to do it for us because of our brand and they want to be well represented.
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  Some of our partners you've never even heard of. Like a lot of people haven't heard of
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  Bambora. They give us intent data. That data comes in the crunch space so you can merge it with
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  other data sets. So that is another aspect of what we are. So no one in the world has ever
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  combined all these data sets into one unified profile before. And now you're able to do
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  processing against all these different flavors of data all at the same time. And that's very,
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  very powerful. So that's three. The fourth way is our machine learning or AI systems. So that
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  is a combination of crawling legal sources of data for us to go and get data from.
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  But and that's a sort of table stakes. But some of the secret sauce is we also generate a lot of
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  our own data based on what we see from all these other data sets. So even from our own usage,
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  right? So if everyone's flowing to a company profile page to go and check it out,
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  that's probably an important page right now for whatever reason. That helps drive our trend scores
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  and our growth scores and our sort of recommendation engines. All these things are looking at
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  which which data has impacted funding rounds. Are there more news stories? Are there
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  people tweeting about this company a lot right now? All those things drive into does this company
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  matter or not? And that helps figure out which companies we should prioritize. So that's the
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  fourth way. Then the fifth way is we have a team of about 20-ish people who work for crunch
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  base and they manage a team of about 250 people overseas that go and do manual cleanup of data.
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  Those automation, the AI systems flag things that I can't figure out. Is this spam? Is this bad?
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  Is this good? It kicks it over to the humans to go and add a human brain on top of it to go
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  and clarify. So we spent like 20 million dollars a year just making the data as good as it
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  can possibly be and of course expand it. All that as a combination those five things. What's
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  beautiful about that is no competitor out there can do what we do. I don't care who it is.
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  There's no one who has all five of those things and can get themselves to a place where they can
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  compete. A lot of people are like, oh, I'll just crawl and I'll be crunch base. Yeah, good luck.
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  I asked like a horrible thing. I asked like a compounded question. So there was like 10
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  of the things that I asked but I don't want to let you go on because I actually want to just
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  pause you here and just down on one thing you mentioned and then we can keep going.
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  So the one thing that I realized is that you became you became you've mentioned this a few times
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  the source that people want to represent themselves on. Now that's that's incredible because if
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  you even look at what you said you you you get data from G2 and I don't know all the different
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  sources you get data from but G2 could even be considered a competitor but technically not
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  because they're feeding data into you. So how in the world did you become the person that
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  everybody wants to be represented on because that that is magic. Whoever you manage to do that
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  that's incredible that market position that you're in. I think it really comes down to like G2
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  it's definitely a partner or not a competitor in our minds as an as an example. You're going to
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  go there you know what I mean though because like they also represent companies right. Totally but
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  you would never go to G2 to like figure out if they've got funding you know like or if they
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  what their website traffic is like you never you would never think to go there you say oh well
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  I'll go to a similar web or an Alexa for website traffic data but no one had combined it all
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  together into one place and that was based on our roots that was very easy for us to do because
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  when our the use case for at the very beginning of country was what the hell does this company do.
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  I have no idea I'm gonna go look at that by crunch base. I I'm going on a date with someone they
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  work at fiddle sticks dot com like what the hell is fiddle six dot com to do you google it
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  and crunch base comes up and then you go and look at it that base level that what I like to call
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  the master record of a company was already what crunch base was we didn't have all the companies
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  but for the companies that we did have we were the master record of companies and then with that
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  framing then we can go and take all these different facets of data like G2 products and plug it in
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  and G2 gets excited because we we're gonna give we give it brand recognition is G2's data here it
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  is click here if you want more data from G2 cross so they see us as a lead source happy to do that
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  because they're providing value to us thanks for tuning in if you found this valuable don't forget
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  to hit that subscribe button so you never miss an episode and if you want to dive deeper into this
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  conversation check out the links in the description to watch the full episode see you in the next one