The Exchanges

Q Well, now we know. So teach us you launched in 20, 20. How'd you get your first hundred customers?

A So it was all partnerships, uh, and, uh, partnerships and product-led growth. Uh, we connected, as I said, with CRMs, like HubSpot, Pipedrive, and we reached out quite early because we are Bootstrap founders. We Bootstrap for the first two years. Later took a bit of revenue, so a pre-series A seat and a pre-series A. But Bootstrap founders, so we needed to find revenue, uh, very effectively. And we thought, okay, let's see if we can grow with our partners. So what we've actually done is we looked at our partners like HubSpot and Pipedrive, and why are they growing? What is their North Star metric, let's say? And then we tried to find a product angle, how we can improve that North Star metric. So let's say, for instance, HubSpot. HubSpot's pricing plans, they work according to the number of users. So if you have more users, let's say in your marketing hub, in HubSpot, um, you need to pay up a higher price. And, uh, we came to them and said, hey, listen, When people use Surf plus HubSpot from day one, you will have faster, um, upsells, um, because people have more contacts, uh, in a shorter time. And then they've realized that we have a few common customers. And I said, okay, great. And I kicked off some certain go-to-market motions with the CRMs, with, uh, Pipedrive. We have even a product partnership now. But yeah, the first one million we've reached in one and a half years. So…

AI assessment note: “So it was all partnerships, uh, and, uh, partnerships and product-led growth.”

Q Interesting. I want to go deeper on something that you've done ahead of the market, which is the API you keep referencing. I want people to visually see it. So here it is. This is off of your LinkedIn. Walk us through, you said this is where most of your investment is happening. Why is this expensive to build?

A I mean, first of all, you need to understand what you need to pull from providers. What are the individual provider strengths in terms of coverage, in terms of accuracy, in terms of industry-specific certain markets. You also need to look at the input data. So is the input data rich enough, or do we need to do some pre-enrichment? Then we do some pre-enrichment until we have a rich enough input data to then go to our providers. And then, um, basically take the first provider who's the best for your particular search. Um, so that's the, the, the waterfall, um, behind our, our API endpoints for, for enrichment. That's not easy to, to build and maintain, especially at the, at the big scale, um, where you also look at speed, um, because for most of our partners, sure, coverage is one thing. Accuracy is even more important, uh, now for, for email and phone data. But speed, um, is, is very critical for, for these partners, because of course when they offer something like this in their own product, you don't want heavier users to complain and support because of the loading times. Um, so yeah, these three things in combination makes it harder on the waterfall side to build an API which is robust and which can, yeah, have enrichments for fifty million data points to, to be processed.

AI assessment note: “these three things in combination makes it harder on the waterfall side to build”

Q your education. You watch my show. So sign up at founderpath.com and when you get the onboarding email, I reply and I see all those. Just reply and say, Nathan, I found you through YouTube and I'll make sure to prioritize you. I would love to cut you a check. Check out founderpath.com. Why do you need to, you know, sell, you know, ten million worth of your business's equity?

A So yeah, we are aggregating different data providers. Um, so first of all, getting into the market and buying data from, um, other providers is very costly. We now handle fifty million. We process fifty million data, um, points like per, per year so that Means enrichment in our own product UI for our users. That means enrichment for our partners. So we are, for instance, behind a couple of folks, AISDR, as I said, a pipe drive in CRM enrichment. We are now one of the partners of HubSpot's prospecting agent next to ZoomInfo and Apollo, which are massive brands. So for, for us to be the third tweaks for the quality, and that's where we have investing most of the money in the quality of the data. By aggregating 15 resources now, um, on, on, on the data enrichment side, on the search side as well, where we have several resources, and, um, of course, then growing a company, a team across, uh, now offices in Paris, Barcelona, which we opened this year, and New York, which we opened as well. Um, so yeah, there we, we of course need some money to grow for go to market as well, and that's where we have been investing it mostly, yeah.

AI assessment note: “getting into the market and buying data from, um, other providers is very costly.”

Q Yeah. Fill in the growth story for us. We know 1.5 million of ARR in the first year. That's 2021. We know you're around fifteen million today, but fill in the middle. When did you break five million of ARR?

A That was, um, we had a party, Christmas party, where we reached 4.5, and which was a year before last year, so it was 24, right? Yes, end of 24. We reached 4.5. Last year's growth was, our API has a big part of the growth story. We developed this API, I think, a bit ahead of the market, at least in our sales intelligence market. We developed it, uh, three years ago, three and a half years ago, and it's now at the, it's very robust. It's, uh, like for high-scale companies. As I said, we are partnering with HubSpot's prospecting agent, um, on that front as well. So, yeah, it needs to be very stable to support companies and, and, and logos like that. Um, and that's where we have invested most of the money, and that's where we've been seeing growth last year. Especially, and that API growth is from, from partners. Again, um, plus, of course, also an enrichment. We enabled, uh, for our users that they can buy credits in product. Um, so we additionally sold, on top of the licenses, now, um, usage credits, uh, which then also increased, um, our, our revenue with, um, our, our, uh, customers.

AI assessment note: “we had a party, Christmas party, where we reached 4.5”

Q You're doing fifteen million a year of revenue today. What percent of that revenue would you say actually comes from usage happening via your MCP, via people using it like we're seeing on the screen?

A It's now a third, roughly, um, as we have been launching it, as we have been launching it, uh, partially, I would say, beginning of last year, um, it's now roughly a third, and that combines API, um, that combines credits in product, um, and recently MCP. MCP is very new. It's better, so we don't have yet much revenue on the MCP side, but we see some, some customers and partners Using the MCP, for instance, Dust is, is one of the companies who enable, uh, companies to, to get AI ready, or be, um, like, uh, yet companies towards AI, AI readiness. They have been using our MCP, and companies who are using Dust, um, are using our MCP, but it's very new stuff. It's very much embedded.

AI assessment note: “we don't have yet much revenue on the MCP side”

Q Someone listening today, if they want the best data and they just want to pay for one platform, what is the actual alpha? Like, why should they pick you guys versus Fullenrich versus ZoomInfo directly?

A Yeah, so first of all, I would always go for a waterfall provider. When we came into the market and we built the, the product, um, not because we wanted to, to build this product or this company, we built it because we had our own pain point. And for us, it was tough to find the right data provider and the right, um, tool or product to sync our different flows, so we've built it ourselves, and we said we want to bring transparency into this market, so we want to show you Uh, openly where the data has been sourced from and where it's coming from. So that's why we've had said, okay, why not, uh, connecting to all the possible data in the world and show you exactly on the result, um, whose provider, uh, brought it up. So that's the first thing, because with a waterfall, and especially if you have a go-to-market motion, which is internationally, so you need more data providers as you may go abroad, so you need to add some specificity, a waterfall makes sense. Just Pure coverage-wise.

AI assessment note: “we want to bring transparency into this market, so we want to show you”