Vainu Revenue & Funding (2024)

[00:00] Hey, folks. My guest today is Pietari Suvantu. He's the cofounder and CEO of Vainu. His mission is to generate revenue for his customers by collecting firmographic data and making it actionable by integrating it to his customers' business processes, such as their CRMs, market automation tools, and data warehouses. Alright. Peetar, are you ready to take us to the top? [00:18] >> Yes. Of course. Let's do it. [00:20] So in The States, folks are really familiar with maybe Pitchbooks or or CB Insights or sort of some of these companies. Would you put yourself in that same category? Would you say you're different? [00:31] >> Maybe a little bit of different. I think I'd put ourselves in the ZoomInfo, Cognism, Clearbit mostly in that category. I think that's more more closer, to marketing and sales instead of instead of like venture capitals and financial people. [00:47] Makes tons of sense. Now you came on. We're just joking about this back in '19. Actually, you came on in 2017 and 2019. Yeah. So regular guest. Regular guest. Well, we we got to catch up. It's been three years. So help me understand today, how is the product different or is it pretty much still the exact same thing? [01:03] >> Well, I think 2019, we were a little bit more focused for the sales people and now we're more focused to the revenue ops people. So how it differs in the product is really that we've built good integrations, good connectors so that we are very good at integrating our data into the platforms where the actual work really these days happen. The other thing that has been a big difference, I think we served the Nordic audience back in three [01:31] >> years ago, we just launched a global product. So now we can serve the customers all over the world and we're very specialized, not specifically globally, not in contact data, but the firmographic data and that specifically data from company websites to understand and analyze that. And that's what we do globally these days. [01:50] And why did you use firmographic data as sort of your beachhead, your first thing versus technographic data or some other dataset about a company? [01:58] >> Well, I think there's an just to understand understood understand content from company website and sort of categorize segment the company. We felt this is space that hasn't been filled yet. There's a lot of contact providers. There's a lot of technographic providers. There's a lot. But we're very good at segmenting the company, giving sort of a confidence score on certain values. I think that's our sweet spot on a global basis. Of course, The Nordics, we're like full [02:31] >> suite when it comes to company data. So where we can offer really anything. It's a tiny piece of the whole world. [02:38] Now when you came on last time, I asked you what's the average customer paying and you said about $600 a month, which was up from $400 a month in 2017. I'm gonna guess you've probably expanded that even more. What's the average customer paying per month today? [02:52] >> Is the average customer is around annually, it's like 10,000. So it's it's gone. It increased a bit. So not that much. But if we look at the spread, how much is the biggest customer paying versus the lowest, that has increased significantly. So we have customers that pay several hundreds of thousands, and then we have customers that pay 1 or 2,000. [03:12] So Tell me that story. [03:14] So your if your biggest customer, what, pays $300,000, $400,000 a year? [03:17] >> Something like that. Yeah. Yeah. [03:19] So if if if don't name the customer, obviously. But if someone's paying you $400,000 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? [03:29] >> It's really the amount of data and then how we deliver that data. And for these customers that pay hundreds of thousands of dollars per year, it's really about a lot of data. And then it's delivered really to their Snowflake or AWS, some core processes in those enterprises are run with our data. So for example, if there's a CRM and they want to form a new company or they want to send a bill or whatever they want to do, [03:57] >> that data comes from our database and it's very crucial for them. So that's why they want want that it flows securely and surely. That's why they're willing to pay for it. [04:06] Oh, what's going on there, YouTube? Good to see you guys. Now imagine this. You love watching these interviews with SaaS founders. But imagine if we took all of the valuation data out from over 2,807 interviews I've done manually saves you a lot of time. Well, we've done this. We've built it into the beautiful interface inside of Founderpath. Check this out. I'll show you how you can access this in a second, but you log in, you connect [04:30] your Stripe account, you see your valuation real time. You can see what it changed over the past eighty eight days and even set goals for valuation this year. Now the secret evaluation is there's many different ways to value a SaaS business. So the reason you're gonna see three or four different valuations inside of your Founderpath dashboard, this is all free by the way, is because depending on who's doing the buying of your SaaS company, you're gonna [04:54] get a different valuation. A VC is gonna pay a different valuation. Private equity firm is different. If you're gonna do a minority sale, that's different. And if you sell the whole business, that's a different valuation. You can see all those when I hover over here. [05:07] Right? So [05:08] the teal is what a VC would pay. Yellow is what private equity and red is if you sold the whole thing outright. Now what's cool about this is this is not built off random data. Again, you guys hear these interviews on YouTube. All these datas are built from real time valuation data points founder share with us on the show. So traction, 1,200,000 seed round, 3.7 raise. They sold 22% of their business. Go in here and filter [05:31] by the event. Maybe you only wanna see companies that have sold the whole business. Well, here are a bunch that have been acquired, the valuation and the multiple. Maybe you're going out right now and you're raising your seed round. We'll go in here and look at all this recent seed deals that went down, what they raised, what valuation they raised at, and what percent that they sold. There's never been a larger dataset of SaaS valuations than [05:57] what you can get now inside of Founderpath. And we're thrilled to bring it to you. Alright. We're gonna go back to the YouTube video here in a second. But if you wanna check this tool out, if you wanna jump in and sign up, you can check it out for free to get your valuation at this link. This link, founderpath.com/products/valuations. Or if you go to founderpath.com and hover over products, click on get your valuation here, and go [06:22] ahead and sign up to give it a whirl. Again, all that valuation data live right inside the platform. I hope to see you there. Alright. Let's jump back into the interview. Can you give me an example of the a kind of piece of data you might deliver to someone's Snowflake database or AWS database or servers on a on a on a monthly basis who's paying some of the enterprise enterprise prices? [06:45] >> Yeah. I mean, for for some cases, might be official data, very likely business ID related data. And for some, it's really about the segmentation models I was just talking about on a global basis that that we deliver, like, continuously for a few million companies that segmentation data in the Snowflake. And then they operate, for example, their marketing campaigns to the marketing automation CRM systems, data and take actions from there forward. So that's that's that's really the [07:17] >> the the more of the data, the the k, really. The seeds that [07:21] matter the amount of data? Like, what is it quantified by? Is it bits transferred per month? Or how do you [07:28] >> We we charge today, we charge practically per account and then per data point. So I mean, if there's a let's say you want 1,000,000 companies and then you want, like, five different data points, then it has a certain certain price for it. And then we don't charge per update. We charge sort of per annually that we keep that updated on an annual basis. [07:51] So at least one update per year or something like that? [07:54] >> Yeah. Yeah. Something like what they really pay for us is that they they feel secure that that company data is updated. And never if it's 100 times or zero, that doesn't matter. [08:04] Okay. I see. I see. That makes sense. Got it. And then again, officially, I forget, launched it was 2013 or 2014? [08:12] >> As a company, it's 2014. [08:15] It was 2014. Okay. [08:16] >> Yeah. [08:17] And then fast forward to today, how many customers are you now working with? [08:22] >> It's actually a funny story. I think we had 2,500 when we talked last time. Now we have 1,200. So we've actually because we've shifted the strategy a bit. We get rid of those customers that we felt is not good for our strategy and double down on those at work. And then, yeah, that's the situation now. So we have actually half of the amount we had last time. Not the typical story I would imagine in your podcast, [08:47] >> I think It it has been a big [08:49] takes so much discipline to fire effectively fire customers. So Yeah. Exactly. Someone else listening want to learn from you, they might go, man, I don't know how to tell customers to stop paying me. I don't wanna piss them off and have them tweet about it. How do you how do you, like, nicely tell people we don't want you as a customer anymore? [09:03] >> Well well, we don't pay attention to them. So, I mean, if they wanna pay, then then they do. But but, of course, that that customer segment that that we don't wanna keep, typically, churn is very high. So the problem sort of takes care of them itself on a natural basis, I would say. And then you put your time and money to those that you want to keep. Then of course, the churn and the returns just go [09:27] >> significantly up. [09:30] Even with less customers, so has you been have you been able to grow revenue since 2019 or is it have you been flat? [09:36] >> It's been more or less grown a little bit, but more or less flat, I mean, in that sense. So but now I think that that thing is done and next year we're expecting like good growth and good profit. So next year is really a testament of our transformation that it's been working. So I'm looking very excited for it. [09:54] That's awesome. Now, have you guys bootstrapped or raised capital? [09:58] >> We have like 4,000,000. We raised 4,000,000. So there's an VC owns maybe a few percentages of us. So we're not significantly. That that was last year, I think. Yeah. Last year, it's been two different sets. So last year and the year before. [10:14] Okay. So last year okay. Got it. So 4 sort of 4,000,000. You call those like I mean, you're bigger because but you bootstrapped to so much revenue before you raise any external capital. Right? I mean, you had what? Like, $7, 8, 9,000,000 in ARR before you took on external capital. Right? [10:28] >> Yeah. Like, 10,000,000, something like that. Yeah. [10:30] 10,000,000. Yeah. And today, like, if I take 1,200 customers times $800 a month, you're doing, like, $12,000,000, $13,000,000 run rate, something like that. [10:37] >> Yeah. Yeah. Twelve, thirteen. That's pretty accurate. Yeah. [10:40] Yeah. This this is still great. So, I mean, anytime a founder to me, if you've raised less than what your total ARR is, I call you bootstrapped. I think it's very capital efficient. Right? It's very capital efficient. [10:51] >> Yeah. Yeah. Yeah. That's true. [10:53] Compared to, like look. I'm I'm friends with James, right, at Cognism. Right? They've got 34,000,000 in ARR, but they've raised, I think, like, 50 or something. Right? So he's backwards in that sense. ZoomInfo is a different story. [11:04] >> Yeah. Of course. Yeah. [11:05] Now what I will say is when you watch how Henry approached the Chorus deal, right, when he bought Chorus for 450,000,000, he could have bought Gong. Like, there's a lot of you could bought SalesLoft. There's a bunch of other tools. But because Chorus was more capital efficient, their valuation was, like, lower, and he didn't have to negotiate with VCs. They already get that deal done for $500,000,000. Are you have you had any conversations with Henry [11:27] about exiting to ZoomInfo? [11:29] >> No. Not not not not really. I think, of course, the market is very active. The go to market space is very active these days. So, of course, discussions are all over the place, but nothing like nothing concrete and not not really with the zooming for today's funky. [11:45] 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? [11:55] >> Yeah. Well, I would look at from what are advantages and then what would be a good fit. I think our advantage is definitely the firmographic data. And that's one thing. And then the other thing is like the connectors and the integrations to these. We put a lot of effort that our company data integrates well with these most known CRMs and the data flows well into these data warehouses and such. So that's our strength. Of course, where [12:24] >> we lack things is contact data is one, IP based data is one, [12:31] >> outreach tools. 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 is being asked most by our customers. So maybe somewhere around there. I don't know. [12:47] Okay. Interesting. Would you ever go? I mean, assume you guys are very profitable. Right? Would you ever go buy a company in that space or would you prefer to build it from scratch? [12:55] >> Well, [12:57] >> it really depends. I think it's how how I think we need to look at is that what is best for the company and what's the best possible deal? Is it that we would buy some somebody? I don't know. Is it that we would join somebody? I don't know. Would we go bootstrapped along the way? I don't know. I think it just needs to be the best possible decision for the company. And yet there's nothing like that. [13:18] >> Now we're just focused on what we are what we're doing or what we wanna do now. [13:21] And who is we? How many folks on the team today? [13:25] >> So we have, like, three three o three main owners, two founders that are still active, and the the third one is a shareholder. Then we have around 130, 140 people working, and then a very big chunk of those also own the company through share shares or option program. [13:45] How big? I mean, there's a lot of bootstrappers or capital efficient founders that always go, Nathan, how big I don't want VCs, so they're the board's not gonna set the ESOP pool, but I wanna give a little bit of equity to founders. How did you guys decide how big to set up your employee stock option pool? [13:59] >> Well, I mean, I think we just came up with the number really and and something that felt right. I think we we combined the amount of how we feel back then when we did the option plan, felt right for the existing people that were there. And then also we thought that there will be in the future, there will be also good people. So we need to secure some for them. And then we added sort of those [14:23] >> two and came up with the numbers. So I think today, [14:28] >> around 10% of the company is owned by outside founders and then we [14:33] just Now you mentioned earlier, three co founders, two are still active, one's one's not. Are you one obviously, you're one of the two that are still active. Right? [14:41] >> Yep. Yeah. Yeah. Definitely. Yeah. [14:43] There's a lot of founding teams listening where there's, like, a third cofounder or even a second cofounder that's just not active anymore. It sounds like you guys sort of went through this. It can be hard sometimes. It can be even nasty sometimes. So when when that third co founder for you guys told you, hey, I don't wanna be sort of actively involved in operations anymore. How did you handle that? [15:00] >> Well, I think we handled it very well. Of course, those discussions are always very truthful. You need to discuss what do you really want, what are the ambitions. But I think all of us three, we are like, we think for the company's best interest in the end when those kind of decisions come. And I think we're all very happy where we are right now and we talk to each other and discuss with each other and we're [15:23] >> still friends and all that. There's not like that sort of drama involved. It's just how life evolves sometimes. [15:30] That's good. All right. So you three own a big chunk. The ESOP is about 10%. And then you said the 4,000,000 from the seed they own, what, under 5%, a couple percentage points? [15:39] >> Yeah. Some yeah. Ballpark that. Yeah. [15:42] Okay. Interesting. Got it. I mean, I guess, look, if you raised 4,000,000 and sold 5%, I mean, what would that valuation be? Something like what? That's like a 100,000,000 valuation. [15:52] >> Oh, I mean, you can do the math. Yeah. Well, I I won't comment on that, but you can do the math from there. I [15:58] guess the reason I'm asking is you've taken a nontraditional approach. I mean, would you ever go buy out the investors so you can go back to being fully bootstrapped? [16:06] >> I mean, never thought. I mean, never thought about that. I think right now when it comes to all these, you know, raising raising money, doing MMAs, all these things, it's really we're focused on what we're doing right now. So that's why I'm I'm just shouting out thoughts. No thinking, no ideas, you know, just focusing on focus. [16:25] Well, if your investors are going, hey, markets are terrible. Our LPs won't give us any more money. We'd love to get our money back. And you say, fine, we'll pay you two x what you put in. So 8,000,000 on four. Let me know. I'll give you 8,000,000 out of our fund. It's debt. You pay it back over five years. Well, it'll be a beautiful deal. [16:41] >> Alright. Alright. Yeah. Yeah. That's that's good to know. That's good to know. [16:45] So we [16:45] >> have at least one one one chance. [16:47] Yeah. I I'm kidding. No. It's look. I I've I've long admired what you've built. When I was focused on GetLatka, my data engine was this audio data. Obviously, it doesn't it doesn't scale, but I've done 3,500 episodes now. You've done a much better job building this. So 143 folks, I guess last thing I'll talk about is productized SEO. I mean, you guys are killing it because I mean, it it works nicely with your business, but walk [17:10] me through how you guys thought about your SEO strategy in terms of getting free traffic. [17:15] >> Well, that's actually a good question. So I think what we started out with, we're very sales focused, so how a salesperson could do a better job in their life. So that's how we got at least very good traction in Finland and we create a lot of content. With this new product, with this new strategy, we've sort of focused and then we're speaking more about RevenueOps and RevOps and how the importance of data and we speak about [17:42] >> what consists of good quality of data. So it sort of shifted a bit. So that's the space what we want to win. I know in The US, the rev ops is already booming in Europe. It's sort of coming a few steps back. And I think that's the space we're gradually getting. And it seems to work very well. And we get a lot of good traffic by just being sort of the opinion leader in that sense, you [18:06] >> could say. First, when it was the active data driven salesperson, now it's with the RevOps, and that's how we get it. So it's really about creating good quality content, not only blogs, but videos on demand stuff. We go to the events and talk to people, to RevOps people and all that kind of stuff. It works for us very well. [18:26] Got it. Of the 145 people on the team, how many are a sales rep that that carries carries a quota? [18:33] >> New business sales reps, it's, I would say, like 15 at the moment. So it's it's not too we don't spend actually that much. I mean, compared to our competition, we don't spend that much on on sales and marketing out of out of our revenue. So it's it's more of product development where we put a lot on yeah. And then [18:53] How many engineers? [18:55] >> Like, 50, maybe something like that. So it's for bootstrap. Yeah. For bootstrap. Yeah. It's a lot. It's it's a lot when when when you're when it's not like this money. [19:05] Yeah. Yeah. So and you guys are based in Finland, you said? [19:09] >> Yeah. That's right. [19:10] Yeah. So 50 engineers, 15 sales reps that carry a quota. What are the other 80 employees doing? [19:17] >> There's a lot actually. Well, we have 20 to 30 now in CS working with the customers. Then we have admin marketing, that kind of stuff, the rest. That's and then we have few few just onboarded. I counted to 140. A few onboarded, a few new people that doesn't I don't count yet to be salespeople because they don't have a quota. That's when they will. [19:45] Fair enough. Fair enough. Well, hey, listen. This is a super exciting story. I'm thrilled to hear you're still doing well. Last question before we wrap up. When we last spoke, I asked you about net dollar retention. Right? To your point, smaller customers who churned a bunch, you said that you had 12% gross annual churn and 10% expansion for 98% net dollar retention in 2019. What is that today? [20:07] >> The net yeah. The dollar net retention is is it's actually a 100, a little bit over a 100, and then the gross is on 85 to 90. So they actually remained more or less same actually. And now when we speak about it. Yeah. [20:21] Yeah. Looks like 90. So if you churn 10% gross and you add 15% expansion, your net dollar retention gets up to that 105 number. But that's a big I mean, look, going from under 100% to above 100%, that's a big move. So congratulations. [20:34] >> Yeah. Yeah. Thank you. Thank you. It's cool. [20:36] All right. On that note, let's wrap up with a famous five. Number one, favorite book. [20:40] >> Favorite book. The last one I read, it's Moby Dick. I think it was very good. [20:44] Moby Dick. [20:45] Love that. Number two, is there a CEO you're following or studying? [20:50] >> Actually, let me see. Currently, actually, no. I have a lot of lot of of ones I follow. And let me see. Let me let me put you on my it's one thing is one. You don't know it. But Give me [21:02] give me me give me a founder, a SaaS founder in Finland that you really like. [21:06] >> Well, I really like. Well, I like actually I know you interviewed him as well, the the Supermetrics CEO is I like him a lot. He's cool. [21:14] Do you also have a sauna on your rooftop? [21:20] >> In our in our office. Actually, we do have in the office buildings, but there is a sauna, but it's not only for us. So not quite not quite where where Supermetrics is, unfortunately. [21:29] That's amazing. Alright. Number three. What's your favorite online tool for building Vainu? [21:34] >> Favorite tool for well, I need to say it's from the sales center, HubSpot. I like HubSpot on on the sales. That's the number one. [21:42] Number four. [21:43] >> How many [21:43] hours of sleep do you get every night? [21:45] >> I sleep seven hours per night. [21:47] And situation, married, single, kids? [21:50] >> I'm married. No kids. [21:52] Married. No kids. And how old are you? [21:54] >> I'm 39. [21:55] 39. [21:56] Last question. Something you wish you knew when you were 20. [22:01] >> To tell myself that things take time. I think that's good. [22:05] Guys, things take time. Vainu.com launched back in 2014, broke 4,000,000 in revenue in 2017, broke 10,000,000 revenue in 2019. They're now doing about 12,000,000 in revenue. But the nice thing is, might go, why do they not grow faster over the past four years? Well, the thing they're very capital efficient. Only 4,000,000 raise for 12,000,000 ARR, very capital efficient founder here. Again, helping folks understand and get firmographic data to feed into their CRMs, their their their [22:32] databases, their Snowflake instances, etcetera, growing nicely as they move upstream. Less customers, higher ARPU. We'll see what happens next. Pietary, thank you for taking us to the top. [22:42] >> Thank you. Thank you very much. [22:45] One more thing before you go. We have a brand new show every Thursday at 1PM central. It's called Shark Tank for SaaS. We call it deal or bust. One founder comes on, three hungry buyers, they try and do a deal live and the founder shares back end dashboards, their expenses, their revenue, ARPU, CAC, LTV, you name it, they share it and the buyers try and make a deal live. It is fun to watch every Thursday one [23:10] p. M. Central. Additionally, remember these recorded Founder interviews go live. We release them here on YouTube every day at two p. M. Central. To make sure you don't miss any of that, make sure you click the subscribe button below here on YouTube, the big red button and then click the little bell notification to make sure you get notifications when we do go live. I wouldn't want you to miss breaking news in the SaaS world, whether it's [23:31] an acquisition, a big fundraise, a big sale, a big profitability statement or something else. I don't want you to miss it. Additionally, if you wanna take this conversation deeper and further, we have by far the largest private Slack community for B2B SaaS founders. You want to get in there. We've probably talked about your tool if you're running a company or your firm if you're investing. You can go in there and quickly search and see what people [23:53] are saying. Sign up for that at nathanlatka.com slack. In the meantime, I'm hanging out with you here on YouTube. I'll be in the comments for the next thirty minutes. Feel free to let me know what you thought about this episode. And if you enjoyed it, click the thumbs up. We get a lot of haters that are mad at how aggressive I am on these shows, but I do it so that we can all learn. We have [24:12] to counter those people. We got to push them away. Click the thumbs up below to counter them and know that I appreciate your guys'support. Alright, I'll be in the comments. See you.

hello everyone my guest today is piatari suvanto he is the co-founder of a company called avainu the leading provider of company data in the world the company has over 2000 customers around the europe and around europe and u.s small and large companies alike such as basman oracle uh use vinus data all right piata are you ready to take us to the top i am definitely okay so you last came on the show january 18th of 2017. at that point you were just passing about i think you told me a thousand customers who pay on average 400 bucks a month so you were just passing i think like 4.8 million bucks in arr um were you i think let me see here were you bootstrapped back then too yep we were and we still are actually oh i love that bootstrap you had a team size of about 80 people um and churn was about 12 annually so let's jump forward to today first off tell people what the company does who are not from people who are not familiar uh yeah sure so what we do is we we collect company data we have around 120 million uh companies in our database and then we create technology to get all the best data available about those companies and what we do on top of that is that we we build applications on top of the data our biggest biggest app is at the moment it's a sales prospecting platform but we are releasing new new products as we go from zero and is kind of monthly you know the average the average company paying you still about 400 bucks a month or is that changed uh that's increased around to six thousand uh and then we also are uh we have our highest highest paid clients are above a hundred thousand uh euros or so hundred twenty hundred thirty over over one 130 000 uh usd per year and the lowest end is is around thousand thousand dollars per uh per year so it's uh the variety of the paying customers have gone uh way way further yeah our ar yeah and our error r is uh so basically what we've done since last time we talked um we've doubled our head count and tripled our um arr so doubled head count so you're 160 people today something like that 170. and you're doing about 15 million dollars in arr yeah exactly okay and price point is still about it you said the average person is paying about six thousand dollars a month uh six thousand uh per year and the uh highest highest paying customers are around 150 000 uh per year and the lowest are around 1 000 per year okay so 500 rpoo and sorry how many customers are you now serving uh 2 000 oh 2 000 customers great a little bit more maybe 2 300 something like that i'm not quite sure about the actual numbers at the moment yeah no no that's grown nicely too so 200 customers at 500 bucks a month puts you at a million a month now on revenue or about kind of call it 12 million annually is that right uh yeah something like that maybe a little bit more i think our arr is something uh 15 15 million usd a little bit more i think we passed it just just two seconds ago that's very good so so yeah let's talk a little bit about growth so if you're doing that today where were you about a year ago we were a year ago we were around um 10 million i would say uh somewhere around that yeah okay and then we know what you were doing a year before that you were doing about about 480 000 a month yeah something like that yeah so this is this is great growth that you've driven phytari totally bootstrapped i imagine a lot of this is probably you're eating your own dog food right you're using your own tool to get new customers is that right uh yeah pretty much so so what we do is we use a lot of other company data to drive our lead generation and then what we do is uh we have our own data and then we combine uh marketing data and of course our crm data and then we package that to the best possible leads our sales goals uh goes after so we definitely eat our own dog food that's for sure so so who you know i would say in the us the most comparable companies would be like zoom info or discoverorg now discoverorg bought zoom info would you compare yourself to them or no uh i would say to some extent uh some extent yes uh but yeah i would say to some extent yeah if you need like a one-on-one uh comparison that would be it i think the biggest uh biggest market is is uh when it comes to company data it's something that has not yet been revealed sort of so i think the real question is how can we integrate company data into other uh like sales workflow systems like you know crms and outreach systems and and and such and i think that the huge leap in in these systems uh will come when when when those two uh company dates and workflow systems integrate seamlessly and that's how how this next generation sales platforms i mean shouldn't that just be via an api and isn't clear bit really in that space right now um well yeah i mean i i guess that's one uh one way to approach it it's it's purely like a product and a company strategy question i think uh api is definitely a one uh one uh way of looking at it and it specifically works for the enterprise customers because they they don't want to take another uh other platform uh to be used they have sales force and and all the system place so they want to use our in our case as well the api to just pull in the data that's interesting okay so so give me a use case here if i go to your website and i want to look up a company let's say i want to look up um hubspot.com right i'm curious about hubspot what data what data fields will you return for me for hubspot uh well uh well that that uh varies a lot from uh which which year do you uh where you are but let's say um and in in in us uh hubspot uh we will return of course uh all the other companies so associated to the hubspot uh the revenues uh the locations the technologies the events and some of the some of the decision making data we're not in the contact data business and so only some some of that and then also our proprietary data things things that we have uh predicted using our own existing uh data uh that that we can give so for example just to be clear sorry you're so you're not providing like email address of the ceo you're providing like company level detail like team size revenue location yeah yeah yeah exactly and our our sweet spot is definitely not on the on the bigger end of the customers because i mean everybody understands where to get information about hubspot and there's plenty of stuff hubspot out there so you don't really need technology to know who is the ceo of you know hubspot and what are their revenues but our sweet spot is in the smb smb company so we understand we because of our technology we can uh understand a lot of lot of things around the small and medium businesses that that really uh data that is not that well available and easily understandable you mean like if someone sells someone that pays you right now sells them to restaurants you could tell them of all the small you know restaurants in london these this is the order of the ones making the most money versus the ones making the least uh yeah for for example in that that use case specifically in in where we are the strongest in the nordics i guess there's we have companies that use it specifically for that uh that use case uh and then uh specifically in the like like the big companies uh the enterprises such as like say uh let's have a ah intercom for example uh they i i think are our customers so for them uh it's not that so for them they don't look for big companies that could use intercom because they know them by heart they know the you know top thousand companies that they should be using intercom rather it's the smaller ones that uh our revenue you know 500 000 to 1 million to 10 million dollars uh because that data uh is it can't be like manually searched you need you need technology to find uh find data on the smaller so so yeah let's peel that back here for a second so how i know intercom obviously you have to install on a website so you're only dealing with like digital like companies that have a website um how do you find in the let's say like a us example how do you find the revenue of a company in the us that doesn't report it they're a private company yeah so we first of all the the data we get is the the base data we get is data that uh that the companies all legal entities need to report to the authorities and as we know in u.s it's not much and most of the companies are registered in delaware and that's sort of the fun of it so then uh we we start to look into places where we can find uh find the data and then uh to answer your question there uh of course we don't know the exact revenue number of a small company but because of the dataset that we have we we give predictions of the data so we cannot say that uh company a's revenue is 1.235 million dollars but we can give an estimate that it's between one million and two million dollars based off usually based off what couple of factors i imagine at some imagine like team count and head count and things like that well well that's that's one part of it and the other part of it is that uh companies around the world they are pretty much alike you know uh so so uh what we can do is we can compare those company data sets uh where we have a lot of lot of data good quality data for example you know dutch and nordic and data and use that as a sort of a teaching data set to understand uh understand data around for example u.s companies so you can give an example of a company that we know exactly that has a revenue of of 2 million dollars and then then we know exactly how their website looks like you know how many people there are what kind of technologies they use what is their activity in their website and use that as a training data to give an estimate of of the company be in us that doesn't give out its numbers to give sort of the size point of of the company as uh what it is and so that's sort of the way we we do it so we use our existing data set to uncover other data points that are not so much available let me repeat some of this back to you in the nordics you have to the small any company has to report way more data to the governments right than the us so you're using that data which includes i believe revenue points to essentially teach your algorithm to try and better guess what u.s companies where you have less access to data are doing on top of that for u.s companies you might look at technographic data like what things they have installed on their website javascript embeds things like that um in addition yeah like the tech stack stuff are there any other kind of things that you haven't mentioned yet that you look at to predict this kind of stuff uh yeah and then i mean uh we don't what we do to predict stuff is is rather like the core core points of the company so you know the size size the industry and the head count those kinds of things that small companies do not need to report those are the things that we use are basically our existing data set that we have in eu to uncover in the u.s but of course on top of that what we get we have a extremely good uh coverage of classified events of of any any of company's eyes i think we index 1.5 million uh news articles per day which we then classify to certain categories and connected them to the uh to the to the companies and that's that's something that is very very uh a good data set that nobody else else has at the moment categorized events of of companies and specifically this goes to us and more specifically to be a small and medium business segment yeah yeah so people are paying on average 500 bucks kind of a month for this kind of thing let's say intercom is paying you six grand a year you give them this huge this big data set right but then they still have to do all the work of going and looking up how to actually reach those people to try and close them right because you're not giving them like email contact information so besides just giving them the data i mean how do you what do they do with the data once they get it uh yeah i mean let's put it this way if a company wants to purchase all the data as a data dump it's definitely not six thousand uh six thousand uh per year but what it typically is is that uh our our platform and our data is as i said used to find the company uh and then what it is of course we have integrations to other systems so that data can be uh straight by the push of a button to be distributed to other other platforms so it might be so that uh depending on a company but if typically it saw that they have a crm and they use our our platform to find companies and they push it to salesforce or whatever their crm is and and then there the sales process starts from uh from there yeah yeah they're enriching context they already have yeah yeah yeah not necessarily enriching uh they're they're finding new companies that they specifically don't have and pushing that to salesforce and there might be another provider uh uh in usa specifically get the emails to assume info you have to get the emails in uh but on but on you because of the gdpr the contact business is not uh i mean we did a decision not to go there because there are much better alternatives to get the get hold of the right right person are you are you right now in acquisition talks with henry at discoverorg no no we're not you wouldn't you wouldn't entertain an offer from them and i mean i even we haven't even talked to him at all no talk to me about churn last time we spoke it was 12 percent annually which turn like today uh it's about the same it's about the same so yeah do you have it sounds like though you've matured though in terms of upselling or do you have meaningful expansion revenue now uh yeah yeah we do uh and where we where we specifically do have that is on the uh on the bigger end of the customer so typically a big big company they buy five five to ten seats for sales team to check how the how the data what's the cost per seat uh well the call it's 100 euros uh so 100 dollars per month per per user basically that's that's how it goes uh so they use a sales team uh tries it out and they they like it and and the next step is that they want to integrate the data into their system uh so then then we start uh start discussing with the uh corporations how to integrate our data into there obviously yeah yeah and that's a that's a big big big opportunity for us and is that like you know like if people want to do that it's an additional usually like 10 grand a year for a team of three or or 100 grand a year uh for um i mean for 10 10 users it's around yeah well i mean it's it's 12 12 grand uh crown a year but then when you integrate the data into into like you know marketing automation and salesforce crm systems and such then then we're talking tenfold at least oh good okay so someone that's paying you for five seats at 100 bucks a pop so 500 bucks a month or 6 000 a year when they then call you and say this is working really well we want this to automatically feed into our salesforce accounts you're going okay well that's going to be you know you know you know a thirty thousand dollar kind of integration yeah i mean yeah well not not only well that's the integration piece one but then the arr goes tenfold as well uh if if used in in salesforce by big corporation so the per seat cost to go from 100 per seat for that team of five up to like a thousand per seat for that team of five well yeah basically the thing is that when you push the data to a crm and it's extremely hard to limit who can see that who can use the data or not so then we need to make an assumption that the whole company is using the data and then they understand the fact as well and and then when they want that data to their crm they they want it for the whole company uh and then you know then there's different pricing tiers in terms of how many companies they want to enrich the whole company so you get like two or three users addicted then when the company calls and says we want this you know integrated to our crm you're saying well guess what you have 100 sales people so now you have to pay a hundred bucks for all those seats yeah exactly exactly so it's all moving for them if they want to enter credit that's really smart okay so do you know what net revenue retention is right now annually uh it's about the same than it was uh what was last time so closing the zero uh [Music] yeah not not beyond negative but getting there so about like call it 98 99 net revenue retention something like that super close sounds like yeah something like that um you meant are you guys profitable or you break even uh piano uh we're not profitable uh but just talk to our cfo we're getting their end of the year and so that's also one of our strategy uh to get profitable uh because it's uh yeah you need to do well you're bootstrapped though how are you burning capital where's that money coming from that you're burning if you haven't raised uh well that uh it comes from uh from the customers so what they do is they pay one year up front yeah so it's cash flow you're saying then when you divide the annual contract by 12 and you recognize it monthly you're technically burning but cash wise you're actually collecting and you're good uh yeah yeah yeah exactly and then piano wise we also will be profitable end of the year uh so that's uh that's good as well that's great okay last question here before we wrap up um how aggressive are you being in terms of customer acquisition costs what will you pay to get a new 500 a month customer uh we pay around 12 12 months of revenue okay so you'll spend up to six thousand bucks to get a 500 a month customer for about a 12-month payback exactly that's right that's good where are you spending most that money ads or sales team or what uh we're we're spending it basically on uh yeah uh products more or less product and data and there there it is uh where we're spending uh spending all and that we can yeah i imagine you probably pay for a lot of other subscription services to suck in their data as well right uh yeah not that actually what we pay the most is this the amazon uh it's a mechanical turrican and aws and and although all those though those start to become very expensive when you have high calculation power i would say do you use mechanical turk a lot to like manually comb your data to do like checks and stuff uh no we use mechanical third to uh create like training data sets so that's what we do interesting very cool all right let's wrap up with the famous five number one what's your favorite business book my favorite uh business book i need to come with the uh same one that i told last time so how to win friends and influence people number two is there a ceo you're following or studying uh i'm sorry can you come again yeah is there a is there a ceo you're following or studying uh yeah i i think i told michael bloomberg last time and i think i i i still still enjoy him yeah he said yeah you're building a new version of bloomberg terminal all right number number three what's your favorite online tool for building your company besides your own yeah besides besides our own uh well you know i don't know if i said last time half spot i think but i think that's the uh still is we're really hooked into it i need to say number four how many hours of sleep to get every night uh a seven and what's your situation married single kids i'm married no kids and how old are you i'm i'm thirty-five thirty-five all right peter take us home what do you wish your twenty-year-old self knew uh to take it a little bit more easier i would say take it easy guys yeah guys take it easy if i knew now up north of uh 11 12 13 million bucks in arr that's up from again growth wise 430 000 a month at the end of 2018 now doing about 830 000 sorry 12 months ago during 830 000 a month growing now to about 1.2 million per month serving 2000 customers that pay 600 per month on average but huge range ranges in terms of minimum and maximum acvs 160 people on the team they are bootstrapped which i love almost to net revenue retention of 100 spending the first full year of acv on acquiring the customer so nice growth therapy atari thanks for taking us to the top thank you very much