Vainurevenue & funding

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