Nick: Before we jump into the # NSF, you know, I often hear people talk about how they invest in market places or education or drones or healthcare or IoT or SaaS or machine learning, etc. But they mention these things all in the same breath, you know, some classify them as sectors, while others talk about horizontal themes. Clearly something like SaaS is more of a business model than it is a sector. At # CB Insights, how do you think about these categories and also structure the data, so that you’re not mixing apples and oranges?
Anand: Yeah. It’s a really hard problem. So industry classification and taxonomy is , has probably taken a few years off my life. We, you know, we started, so when we started day one, it was sort of SIC codes. Amazing if we were building a database for agriculture and just miserable for anything high growth. Kind of quickly abandoned that. You know, went to something that was again too high level, sort of internet mobile software. And then we went to something much more granular. So now you can go into, you know, internet software services, payments, which is good. And then the challenge is kind of what you addressed, which is there’s certain things that are more schematic, right, IoT, FinTech, Big Data, Digital Health, right. And so how do you deal with those? You know, you don’t want to introduce a new filter in the taxonomy every six months because of the flavor of the month
Nick: Right
Anand: because then, you know, in two years Nick, you’d call us as a customer and say hey Anand like what the heck is location based services, right. Like remember when that was hot. So we don’t introduce, the taxonomy is actually fairly, you know, set in stone. But what we’ve added are what we cal lists. And those are essentially tags, right. And so then what you can have is, and you let us do kind of a one to many classifications, so you could have a company that is a IoT company as well as a FinTech company, right. And so those things let us organize companies in a bit more of a topical kind of thematic way. And I’d say like a lot of the research that we put out tends to leverage those lists that we create. And it’s also become I think one of the things that customers like the most about # CBI is this kind of, the fact that we have these things that, you know. An internet of things list is available on # CB Insights, right. I think that’s, otherwise you’re building it yourself using keywords. And that, you know, there’s a lot of data janitor work that customers do that I think we , you know, we get them out of, right. A lot of our users are analysts and we actually get them doing analysis versus just excel jokeying and
Nick: Yeah
Anand: and, you know, trolling around on the web looking for data points to drop into a spreadsheet.
Nick: Yeah. I mean I’ve used the platform and the tagging approach is so much better than the restrictive filter.
Anand: Yeah
Nick: But anyway, I want to move to this # NSF piece. So last year you received $1.15 million from the # National Science Foundation for the launch of Mosaic. Can you tell us what Mosaic is and how you obtained the # NSF funding?
Anand: Sure. So, you can think of Mosaic as sort of, sort of modern FICO score for private companies, right. And so, the private companies, they’re not compelled to provide financials the way a public company is. And so, how do you get a sense for which companies are doing well and which ones aren’t. And the way we’ve, our approach to that is that there’s a lot of data exhaust now on the web that we can leverage to do that. So if you’re a tech company, things like your customer and partner signings, your press, the sentiment of that, are people talking about you on social media, are they talking about you at all, and if they are talking about you is that positive or negative, web traffic, mobile app download data, hiring statistics. So looking at all these disparate pieces of information to try to get a sense for sort of the momentum of the company
Nick: Yeah
Anand: is what Mosaic is. And then it’s, Mosaic kind of has 3 M’s we call them. So there’s Momentum, which is sort of a lot of those measure that I mentioned. Then there’s Market, right, so what industry are you in and how healthy is that industry. And the reason that’s important is that no matter how good your sort of momentum looks, if you are in an industry that is out of favor, it is incredibly hard to swim upstream, right. So if you’re in flash sales right now, godspeed, right. It’s going to be, that’s like a tough place to be, right. You could be executing really well, people might love it. But you know, if you need another round of funding, or , you know, exit multiples have been crushed there, the market score is really depressed. And the final thing we look at is Money. And money is, we model burn rate, we model or we look at the quality of the investors. So we have kind of a Mosaic score also for the investor side of things. And so if you’ve raised money from # Sequoia Capital, that holds a lot more weight than if you’ve raised it from # Anand Ventures. And so those things kind of, so it’s money , market, momentum collectively make up this Mosaic score. The idea for the #NSF was, kinda came to us accidentally. Somebody knew of the program and heard what we were doing and said hey, you know, the # NSF would probably be in to this, this idea , you know, I had seen the problem when I was at # American Express evaluating private small businesses was incredibly hard. We would make a lot of money for a few years, the recession would hit, it would sort of effectively kind of decimate what we’d earned over the last fee years. And so we thought, you know, hey this is an interesting problem. The # NSF liked it because if we can help assess private companies at a firm level, then people would take risks, kind of understanding the company is better, you know. Then what happens today is the economy turns and people say nope we’re not lending to small businesses anymore. And so like that just lumps this very heterogeneous group of companies together
Nick: Yeah
Anand: and so they thought can we give them , or can we give sort of the market, you know, more firmer graphic or firm specific information that would help people make better decisions on financing of companies, or financing. And it’s not just financing, I guess it opens up lots of opportunities, right. So if I am trying to get somebody as a customer, you can look at the Mosaic score and say okay you know this company looks solid, right. So from a, an opportunity perspective, it’s financings, it’s customers, it’s partnerships, it’s M&A, I think it opens up a lot of doors. And so the # NSF really liked that idea. They gave us some money, over a few grants, to try to, you know, we had to prove ourselves that we actually could, you know, get this somewhere. And so then, you know, yeah, over several grants we ended up getting. We were fortunate to get a little over a million dollars from them.
Nick: It’s hard to predict all the applications, but I could imagine that this Mosaic score, you know, depending on how it plays out, it could be useful to a variety of different customers. So that’s in different sorts of ways.
Anand: Yeah, definitely. I mean, I think of it as a, we’re still relatively young company . I think we were at 70 people on Monday. It’s always a challenge of figuring out which opportunity to go after. And so, yeah, I think we’ve seen a bunch of potential opportunities and then we’re sort of I think narrowing it to the ones that we believe are the closest in terms of approachability, so
Nick: Yeah. Did I see that you guys closed a Series A last quarter, is that right?
Anand: We did, yeah. I think we announced that in November. So yeah we closed it, 10 million dollar Series A was our first round of capital. We’ve been, kind of revenue funded, as we like to call it for you know otherwise since we started.
Nick: Awesome, congratulations on that.
Anand: Yeah, thank you.
Nick: Last thing on Mosaic, I was reading your newsletter, which I’m a huge fan of, I read it all the time, it’s really well done
Anand: Thank you
Nick: I was reading it probably yesterday or the day before, and I noticed you picked up on this data points and you pulled it out of text somewhere, but it was on # DraftKings sub-leasing their space and how that was kind of an indicator, right?
Anand: Yeah
Nick: Is that something that Mosaic found and that provides an indicator that, oh this brand new space that they built out in I guess it’s in New York City, that they’re sub leasing it, that’s kind of a negative sign?
Anand: Yeah, so that one was just a cold email from a real estate broker. So yeah, no Mosaic there. I mean, I think we, you know, we look for signals in terms of turnover, right. So in the companies, right, which is a signal or, you know, more specifically f the VP of sales is turning over every quarter, like clearly a bad sign. And then conversely, you know, you’re hiring a CFO, you’re hiring a head of HR, hiring lots of sales people, often a good sign. But yeah that particular one was just somebody cold emailing and happened to just land in our inbox and we said oh this is interesting.
Nick: Gotcha. So moving on, Anand, how do you measure if tools are helping your customers win and achieve their objectives?
Anand: Yeah, I mean. So it’s interesting because the market we deal in is still relatively opaque, right. So our customers, we have insights based on our conversations with them, what they’re focussed on , what they’re interested in. But ultimately they keep that, a lot of them still keep it fairly close to the vest, right. So for us it’s really our biggest metric of success is you stick around and you stay a customer, right. And so we had 99, I think we’re still got a couple left, but 99% revenue retention last year. So, you know, I think that’s the biggest thing, is like we’re making your life easier. You know, I think it sort of shows up in the fact that we’ve got 60 customer testimonials and people are really happy with us. But, you know, it is, it’s hard to know if somebody was developed a better strategy for their company based on data from us, right. We don’t have as much visibility into the end products. But I think they, I think they vote with their wallets, right. And they stay, tend to become stay customers. We’re seeing those customer average ticket with them growing over time. We’re seeing us is multiple parts of the organization because they keep referring us to their friends and different business units. So I guess we have to look at, and because we don’t have a direct line of sight to how they use the data, I think we have to use those as sort of proxies for the fact that we’re doing something right.
Nick: Yep. So there are other data players in the space. If I’m a VC, why am I using # CB Insights instead of one of the other major data players in the startup space or private market space?
Anand: Yeah. I mean, i think it’s a few things. You know, at the core, the data, the foundational element of our platform, which is the data, is very good. It’s the best in the business, right. And so, the analogy I like to use is, you know, you can paint a Honda but you can paint a Honda like and make it look really nice but it’s still a Honda, right. And so, and I , and I’m a Honda owner so I don’t mean that in any negative way. So it’s a Honda. But what we see with a lot of other data providers is they’re just putting a nice shine, sort of a nice coat of paint on crap data, right. And so I think like that’s the fundamental sort of nugget, that we’re really good there. We find more deals, the data’s got sort of a high integrity. And then I think the next piece is how do we help you make sense of the world, right. So just telling a customer that, who’s interested in payments, hey here’s 734 payments companies that were funded this year. Like, you know, that’s still a lot of work, right. Like how do I figure out who’s interesting in that group, right? So I think a lot of the work we’re doing on the predictive intel side that helps you get from data to insight to answer, is really important, right. So how do I figure out hey we want to do a partnership with the company that’s working on this problem, but that we know isn’t going to go away in 6 months, right. So how do I kind of use key words and lists and things to narrow that company list down? And then how do I use Mosaic to figure out which company is the best for me to, or you know, and we’re not going to tell you go work with this company. But I think we’ll take that list of 734 down to 20 pretty quickly, right. And I think like that is a big part of it, right. I think if you just want spreadsheets, I think we just do a lot more than that. You know, and then I think the other big thing like with a lot of the players in the space, like we’re going to be around. Like we’re a real company. We’re not lighting VC money on fire . You know, we’ve got a track record of being around. The media quoted us 1200 times last year. We are a really credible provider who just does this. This is our singular focus.
Nick: # Anand, is there anything else you’d like to highlight on # CB Insights?
Anand: No, I mean I think we covered it. I mean, I really think it’s if you want to know where the world is going using data and predictive intel, like we are the standard now. So I think that’s really kind of where we think the world is going in terms of data driven decision making. And I think we’re at the forefront of that.
Nick: If we could address any topic in venture, what topic do you think should be addressed and who would you like to hear speak about it?
Anand: I mean, I’d love to see, it’s not one person, but I’d love to see Bill Gurley and Marc Andreesson debate the current, the current, the current climate, right.
Nick: They would never sign up for that
Anand: Yeah they’d never sign up for that. But there’s, you know, given the back story and the history, but I mean that would be phenomenal. These are both like super smart folks and, you know, I think I see like Marc Andreesson’s optimism about technology and things. And like I love what we do because like we get a sneak peak into all of the big stuff of tomorrow. And then you see Bill Gurley, who has an amazing track record, but he’s obviously more tempered in his enthusiasm. And yeah, if you could make that happen, that would be amazing.
Nick: I don’t think there’s any chance, but it would be incredible.
Anand: It would be, yeah
Nick: Alright # Anand, and finally what’s the best way for listeners to connect with you?
Anand: So, you know, I live and breathe # CB Insights, so www.cbinsights.com We are @cbinsights on Twitter. We’re relatively entertaining on Twitter and as # Nick mentioned, sign up for the newsletter. We’ve got a hundred twenty three thousand people on it, growing by a 1000+ a week.
Nick: Wow
Anand: So yeah, sign up there. And if you like snark and graphs, we’re the place to be.
Nick: Well # Anand, thank you so much for coming on. Thanks for the time today. I know you’re a really busy guy, and any Series A, Series B or early stage investors out there in the audience, if you haven’t checked out # CB Insights, you should absolutely do it today. So thanks so much # Anand. Hope to connect again soon.
Anand: Alright, thanks # Nick, take care
We hear people say that they invest in marketplaces, education, drones, healthcare, IoT, SaaS, machine learning, etc… all in the same breath. Some classify them as sectors, others talk about horizontal themes. Clearly, something like SaaS is more of a business model than a sector. At CBInsights, how do you think about these categories and structure the data in a way that you’re not mixing apples and oranges?