The Exchanges

Q Regular guest. Well, we, we got to catch up. It's been three years. So, Help me understand today. How's the product different? Or is it pretty much still the exact same thing?

A Um, well, I think, uh, we were a little bit more focused for the sales people and now we're more focused to the revenue ops people. Uh, so how it differs in the product is really that we've built like good integrations, good connectors, uh, so that we are very good at integrating our data, uh, into, into the platforms where the actual work really these days happen. Uh, the other thing that has been is big difference. I think we served Nordic audience. Back in three years ago, we just launched a global product. So now we have, uh, now we can serve the customers all over the world. And we're very specialized, not specifically globally, not in contact data, but the firm graphic data, and that's specifically data from company websites to understand and analyze that. And that's, that's what we do globally these days.

AI assessment note: “how it differs in the product is really that we've built like good integrations”

Q So if, if, if don't name the customer, obviously, but if someone's paying you 400,000 dollars per year, what are they getting for that? Why is it, is it number of bits of information, number of seats, what allows you to upsell?

A It's really, uh, the amount of the data and then how we deliver that data. And for, for, for these customers that pay hundreds of thousands per year, it's, it's really about a lot of data and then it's delivered really to their Snowflake or AWS and, and, and some core processes in those enterprises are run with our data. So for example, there's a CRM and they want, want to, um, uh, form a new company or they want to send a bill or whatever they want to do. That data comes from our database and it's, it's very crucial for them. So that's why they want, want that it, you know, flows securely and surely, and that's why they're willing to pay for it.

AI assessment note: “It's really, uh, the amount of the data and then how we deliver that data.”

Q What, what would you look for, right? If you saw someone else and you sort of chatted with him or her, another founder, like, hey, we should think about coming together. Like, what would you look for in someone like that, whether it's a merger or an acquisition?

A Yeah. Well, I would look at from, from what are our, our advantages and then what would be a good fit. I think our advantage is definitely the firmographic data. And that's one thing. Uh, and then the other thing is, um, like the connectors and the integrations to these, uh, we put a lot of effort that our company data integrates well with these most known CRMs and the data flows well into this, uh, data warehouses and such. So that's our strength. Of course, Where we lack things is, yeah, contact data is one, IP-based data is one, uh, like, uh, outreach tools. I don't, that's something we're not that much into, but of course, if you look at the whole puzzle, I think IP and contact data are the ones that really, uh, is being asked most by our customers. So maybe, maybe somewhere around there. I don't know.

AI assessment note: “Where we lack things is, yeah, contact data is one, IP-based data is one”

Q So, so how do I use this? Like it's interesting. And I just clicked on one of the Salesforce results and I see social media events, predictions, identities, similar companies. How do I use this?

A Uh, it is, well, there's a lot of, a lot of use cases, but if you're, if you're a salesperson and you want to understand, for example, I want to find companies that are, uh, in our interpretation, they are digitally oriented. Uh, they focus on a lot of marketing activities. You can search for those kinds of filters, uh, those kinds of queries in our system. And it, what it gives you companies, uh, that, uh, are digitally oriented, for example, and then on clicking on the company, you can find a lot of other information about it and then Start contacting them on, on that basis. That is, that is a one, one way to do it. And then the bigger, bigger companies, what you just, uh, read out, uh, they use, they use the data that we produce and then they plug it into their existing other systems. They might be, for example, BI tool, uh, or, or of course, uh, CRMs and, and, and, and other, other platforms they want to use in their internal ecosystem. So that's two ways.

AI assessment note: “if you're a salesperson and you want to understand... That is a one way to do it.”

Q And why did you use firmographic data as sort of your beachhead, your first thing versus technographic data or some other data set about a company?

A Well, I think there's an, um, just to understand, uh, understood, understand content from company website and then sort of categorize segment the company. Uh, there's, we felt there's a space that hasn't been filled yet. Uh, there's a lot of like contact providers. There's a lot of technographic providers. There's a lot, but, uh, we're very good at segmenting the company, uh, giving sort of a confidence score on certain values. And, uh, and I think that's, that's our sweet spot on a global. Basis. Of course, in the Nordics, we're like full suit when it comes to company data. So that's, that's where we can offer really anything. So that's, it's a tiny piece of the whole world.

AI assessment note: “we felt there's a space that hasn't been filled yet. Uh, there's a lot”

Q And so how do you like, what's some of the data that you would say you have that other people don't have when I, when I look up a company, like, do you, do you have revenue data or like how many customers they have or things like that?

A Uh, yeah, we have, we have some of those. And I think the, uh, you might ask that, uh, why is it good to start a company like this in the Nordics? Uh, but I think that is the, one of the best assets we have because the, uh, organizational data in, in, in, in Nordics, uh, is, uh, is the best in the world because, uh, we need to be very open about, for example, the revenue figures and everybody needs to follow those. So what we have is, uh, we have a very good, uh, material, very good teaching set of, of, of, Uh, ten million companies, which we can use, uh, as I said, as a teaching material to understand other companies around the world. So we can acquire data and understand data that is not available publicly. So I think that is a one, one big thing. So for example, we can predict fairly closely like revenue figures, uh, for example, in the, in the Dutch market where they are not very public. So those kinds of things is something that, uh, How do you get access to that data though? Uh, to the, uh, when it comes to the noting data, that's, uh, that's something that is, uh, It's something that you need to just make a, make a deal with the, uh, local government officials, because that is something that is required to file, uh, by every company, every organization, they're public in the Nordic. So that is something that we get as a, uh, you know, just by asking it more or less.

AI assessment note: “we can predict fairly closely like revenue figures, uh, for example, in the Dutch market”