How Vainu CEO Pietari Suvanto grew to $17.3M revenue and 1.2K customers in 2024.

hey folks my guest today is pi Atari suvantu he's the co-founder 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 all right Peter are you ready to take us to the top yes of course let's do it so in the states folks are really familiar with maybe pitch books or CB insights or sort of some of these companies would you put yourself in that same category would you say you're different um maybe a little bit of different I think uh I'll put ourselves in the zoom in for communism clear a bit uh mostly in that category I think that's more more closer more to marketing and sales instead of uh instead of uh like Venture capitals and financial people makes tons of sense now you came on we were just joking about this back in 29 actually it came on in 2017 and 2019. yeah um so regular case regular guess well we got to catch up it's been three years so yeah help me understand today how is the product different or is it pretty much still the exact same thing um 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 and 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 happened the other thing that has been this big difference I think we served Nordic audience uh 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 specifically globally not in contact data but the firm graphic data and that specifically data from company websites to understand and analyze that and that's that's what we do globally these days and why did you use formographic data as sort of your beachhead your first thing versus technographic data or some other data set about a company but I think there's an um just to understand understood understand content from company website and then sort of categorize segment the company uh this we felt there's a space that hasn't been filled yet 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 giving sort of a confidence score on earn certain values and uh and I think that's that's our sweet spot on a global basis of course in the nordics uh 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 so now when you came on last time I asked you what's the average customer paying and you said about 600 bucks which a month which was up from 400 bucks a month in 2017. I'm gonna guess you've probably expanded that even more what's the average customer paying per month today is the average customer is around uh annually it's like 10 000 uh so 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 and that has increased uh significantly so we have customers that pay several hundreds of thousands and then we have customers that pay one or two thousand uh so tell me that story so your if your biggest customer what pays 300 400 Grand a year something like that yeah yeah so 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 truly uh the amount of the data and then how we deliver that data and for for these customers that pay hundreds of dollars per year it's really about a lot of data and then it's delivered really to their snowflake or AWS and and some core process in those Enterprises are run with our data so for example this is CRM and they won't wanna 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 very crucial for them so that's why and they want wanted it you know flows securely and surely and that's what they're willing to pay for it oh what's going on there YouTube good to see you guys now imagine this you love watching these interviews with SAS Founders but imagine if we took all of the valuation data out from over 2807 interviews I've done manually saves you a lot of time well we've done this we've built the into the beautiful interface inside of founder path check this out I'll show you how you can access this in a second but you log in you connect your stripe account you see your valuation real time you can see what it changed over the past 88 days and even set goals for evaluation this year now the secret evaluation is 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right let's jump back into the interview can you give me an example of um a kind of piece of data you might deliver to someone's snowflake database or AWS database or servers on on a monthly basis who's paying some of the enemies for Enterprise prices yeah if I mean for uh for some cases it might be uh official data uh very like the business ID related data and for some it's really about these segmentation models I was just talking about on a global basis that uh that we deliver like continuously uh for a few million companies and that segment segmentation data uh and in the Snowflake and then they operate for example their marketing campaigns uh to the marketing automation CRM systems the data and take actions from there forward so that's that's that's really the the more the data the more they pay really the seeds how do you manage the amount of data like what is it Quantified by is it bits transferred per month or how do you we we charge uh today we charge practically per account and then per data point so I mean if there's a let's say you want one million companies and then you want like five different data points and then it has a certain certain price for it and then we don't charge uh per update we charge sort of uh per annually that we keep that updated on an annual basis so at least one update per year or something like that yeah yes or 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 okay I see I see that makes sense um got it and then again official I forget launched it was 2013 or 2014. uh as a company it's 2014. it was 2014. okay yeah and then um fast forward to today how many customers are you now working with this is actually a funny story I think we had uh 2500 when when we talked last time now we have 1200. so we'll do it actually because we've shift the strategy a bit and we've get rid of those customers that we felt is not good for our strategy and double down on those at work and then uh yeah and that that's the situation now so we have actually half of the amount we had last time another typical story I would I would imagine in your in your podcast but but uh it takes so much discipline to fi effectively fire customers so for 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 want to 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 well uh well uh we don't pay attention to them so I mean if they want to pay then then they do uh but but of course that that customer segment that uh that we don't want to keep typically the journey is very high yeah so it's other problems that takes care of them itself on a natural basis I would say and then but you put your time and money to those that you want to keep and then of course the turn and the retention score significantly absolutely so living with well even with less customers so has you been have you been able to grow Revenue since 2019 or have you been flat it's been more like grown a little bit but more or less flat I mean in that sense so but uh 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 The Testament of our transformation that it's been working so I'm looking looking very excited for it that's awesome now have you guys bootstrap to raise capital uh we have like four million we raised four million so there's some VC almost maybe a few percentages of us so so but not significantly that that was last year I think yeah last year it's been two different sets so last year under the year before okay so last year okay got it so for sort of four million you call those like I mean you're bigger because but you bootstrapped to so much revenue before you raised anyhow external Capital right I mean you had what like seven eight nine million in AR before you took on external Capital right yeah like 10 million something like that yeah 10 million yeah and today like if I take 1200 customers times 800 bucks a month you're doing like 12 13 million run rate something like that yeah yeah 12 13. that's pretty accurate yeah 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 yeah um yeah that's true compared to like look I'm I'm friends with James right at cognizant right they've got 34 million in AR but they've raised I think like 50 or something right so he's backwards in that sense um Zoom info is a different story um now what I will say is when you watch how Henry approached the chorus deal right when he bought Chorus for 450 million he could have bought dong like there's a lot of good about sales Loft there's a bunch of other tools but because chorus was more Capital efficient their valuation was like Lord he didn't have to negotiate with VCS they were able to get that deal done for half a million bucks or half a billion dollars um are you have you had any conversations with Henry about exiting to zoom info um no not not not really I think of course the market is very active go to market uh space is very active these days so of course discussions all over the place but nothing like nothing corporate and not not really with the yeah zooming 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 yeah well I would look at from from what our our advantages and then what would be a good fit I think our advantage is definitely the thermographic 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 a lot of effort that our company data integrates well with these most known as crms and and then the data flows well in into this uh data warehouses and such so that's our strength of course where we lack things is yeah content 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 we look at the whole puzzle I think IP and contact data are the ones that really uh it is being asked most by our customers so maybe maybe somewhere around there I don't know okay interesting would you ever go I mean I 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 well um it really depends I think it's it's how how I think we need to look at is that what is best for the company uh 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 now we're just focused on what we are what we're doing and what we want to do now and who is we how many folks on the team today uh so we have like uh three three or three main owners uh two Founders that are still active and the third one is a shareholder then we have around 130 140 people working on and then uh a very big chunk of those also own the company through share shares or option program how big I mean there's a lot of bootstrappers or Capital Vision Founders that always go Nathan how big I don't want VCS so they're the board's not going to set the ESOP pool but I want to give a little bit of equity to Founders how did you guys decide how big to set up your employee stock option pool well I mean I think we just came up with the number really uh and and something that felt right I think we we combined the amount of how we feel back then when we did the the option plan that what 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 two and came up with the numbers so I think today maybe around 10 of the companies owned by uh outside Founders now you mentioned earlier I had three co-founders two are still active one's and one's not are you one obviously you're one of the two that are still active right yeah yeah yeah definitely yeah there's a lot of founding teams listening where there's like a third co-founder or even a second co-founder 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 guys I don't want to be sort of actively involved in operations anymore how did you handle that well I think we handle it very well of course those discusses are always very truthful you need to discuss what you really want uh what what are the Ambitions but I think all of us three we're like we think for the company's best interest in the end when those kind of decisions come and I think we're all all very happy uh where we are where we are right now and we we talk to each other and discuss with each other and we're still friends and all that so there's there's not not like that sort of uh you know a drama involved it's just how life evolves sometimes yeah that's good all right so you three own a big chunk uh the ESOP poll is about 10 and then you said the four million from the seed they own what under five percent a couple percentage points yeah yeah more parts of that yeah okay interesting um got it I mean I guess look if you raised four million and sold five percent I mean what would that valuation be something like uh it's like 100 evaluation I mean you can do the math yeah well I I won't comment on that but you can do the math I guess the reason I'm asking is you've taken a non-traditional approach I mean would you ever go buy out the investors so you can go back to being fully bootstrapped of I mean I never thought I mean never thought about it I think right now when it comes all this uh you know raising raising money doing Ms all these things it's really we're focused on what we're doing right now so that's why I mean I'm just shouting out thoughts no no thinking no ideas you know just focusing on Focus 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 2x what you put in so 8 million on four let me know I'll give you eight million out of our fund it's debt you pay it back over five years it'll be a beautiful deal all right all right yeah yeah let's let's get to that's look I've I've long admired what you've built when I was focused on get Latka 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 um so 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 works nicely with your business but walk me through how you guys thought about your SEO strategy in terms of getting free traffic um well uh that's actually a good question so I think when we started out with we're very sales focused so how a sales person could do a better job in their life so that's that's how we got at least very good Traction in in in uh Finland and we create a lot of content now we now with this new product with this new strategy we've sort of focused and we're speaking more about Revenue Ops and rev-ops and how the importance of data and we we speak about what consists a good quality of data and so it sort of shifted a bit so that's that's the space what we want to win I know in us the rev-ops is is already booming in Europe it's sort of coming few steps back and I think that's the space we're gradually getting and and it seems to work very well uh and and we get we get a lot of good traffic by just being sort of the opinion leader in in that sense you could say uh first when it was the active data driven salesperson now it's with the Rev Ops and that's how we we get it so it's really about creating good quality content uh not only books but but videos on demand stuff we go to the events and talk to people to revox people and all that kind of stuff so it it works for us very well 145 people on the team how many are a sales rep that carry us carries a quota um new business sales reps it's I would say like 15 at the moment uh so it's it's not to we don't spend actually that much I mean compared to our competition we don't spend that much on on sales and marketing uh out of out of our Revenue so it's more of product development where we put a lot uh and yeah and then how many engineers I like uh 50 maybe something like that so it's for a bootstrap yeah yeah it's a lot it's it's a lot when when you're when it's not like busy money yeah yeah so and you guys are based in Finland you said yeah that's right yeah so 50 Engineers one five sales reps that carry a quota what are the other 80 employees doing that uh there's a lot actually um well we have 20 to 30 now uh in CS working with the uh with the customers then we have admin marketing you know that kind of stuff uh the uh the rest so yeah that's that's and then we have few uh a few just onboarded I counted to 140 if you onboard a few new people that doesn't uh I don't count yet to be sales people because they don't have a quota that's when they were fair enough fair enough well Hey listen this is a super exciting story uh I'm thrilled to hear what 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 yeah 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 uh the net yeah the dollar net retention uh is is uh it's actually 100 a little bit over 100 and then the gross is on on 85 to 90. so if they actually remained more or less the same actually and now when we spoke about it yeah yeah well it's like 90 so if you turn 10 gross and you add 15 expansion your net dollar attention 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 yeah yeah thank you thank you that's cool all right on that note let's wrap up with a famous five number one favorite book third book uh the last one I read it's Moby Dick I think it was very good I love that number two is there a CEO you're following or studying um actually let me see currently actually uh no I have a lot of a lot of uh a lot of ones I follow and let me see let me let me put you on right it's one thing is what you don't know give me give me give me a Founder a SAS founder in Finland that you really like what I really like well um I like actually I know you interviewed him as well but the super metrics CEO is uh I I like him a lot do you also have a sauna on your rooftop um in our in our office actually we do have in the office building through the very Society but it's not only for us so not quite not quite where where super metrics is unfortunate that's amazing all right number three what's your favorite online tool for building value uh favorite tool for well I need to say uh it's from the sales Center HubSpot I like HubSpot on on the sales that's the number number four how many hours of sleep do you get every night I sleep seven hours per night and situation married single kids uh I'm married no kids married no kids and how old are you I'm 39. 39 last question something you wish you knew when you were 20. to tell myself that things take time I think that's good guys things take time if I knew.com launch back in 2014 uh broke 4 million in Revenue in 2017 broke 10 million Revenue in 2019. they're now doing about 12 million in Revenue but the nice thing is you might go why do they not grow fast over the past four years well the thing is they're very Capital efficient only 4 million raised for 12 million AR very Capital efficient founder here again helping folks understand and get firmographic data to feed into their Sierra cms's uh their their their databases their snowflake instances Etc growing nicely as they move Upstream less customers higher arp we will see what happens next uh pietary thank you for taking us to the top thank you thank you very much one more thing before you go we have a brand new show every Thursday at 1pm Central it's called Shark Tank for SAS 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 our poo CAC LTV you name it they share it and the buyers try and make a deal live it is fun to 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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