Ocurate revenue, CEO Richard Purcell, team size, customer count, churn, and more in 2024.

hey folks my guest today is richard purcell he's building accurate that's accurate.com actionable ltv predictions richard are you ready to take us to the top let's do it all right sas folks here ltv so is this a tool specifically built for sas founders uh so we're primarily primarily working with b2c organizations and the biggest problem that we're seeing is that leading brands want to be able to measure their business their customers and and campaigns on ltv uh because if they know exactly how much a customer is going to spend in the future it'll inform their marketing investments forecasting and general health of the business but the biggest problem is they don't have the data and past purchase data alone does not predict the future and third party data has always been unreliable and it will seem it will soon cease to exist with all the changes and rules and regulations and so what acura does is we bring in external privacy first data on every adult american's in-depth behaviors and attitudes and when we match this database with a brand customer data the outcome is a 90 plus accurate l2v prediction at the individual level which helps brands make the right investments and the right customers throughout all phases of the life cycle and so if brands are paying you for this technology what are they paying you an average per month to use it yeah so we're primarily working with mid-sized direct consumer brands between 10 million to 500 million dollars in revenue and the way that we price is based on the size of the database and that's between six thousand to ten thousand dollars a month i see okay interesting and size of the database measured by what uh by like number of leads existing customers and labs customers okay so is that your most powerful way to upsell is just number no it's based off number of customers is the utility value [Music] yeah um it's either like um number of customers in the database uh and we hope to grow as the companies grow uh but also you know we're working with a publicly traded company where with one of their divisions we're predicting their ltv at the individual level and now we're going to expand to other divisions as well i see what's the back story here where'd you launch the business yeah so the back story is um the company was spun out of a previous company called predictwise and so predict wise was mapping every adult american over the course of five years in a very privacy first way and was primarily used uh for progressive political campaigns and accurate was was spun out to only target commercial enterprises and so what we've been able to do over the last year or so is only work with youtube find out just last year 2020. um no well ocarina was incorporated earlier this year and so um we were probably about you know nine months old nine to ten months old okay got it so so okay but when did the spin out happen uh the spin out happened around june of this year okay it was okay got it so so sorry what why were you referencing last year i'm i'm referencing the fact that um we were starting to think about building a company only to target commercial enterprises around sometime last year but we didn't actually do that until this year i see i see okay got it so so you spun out now does that mean the parent company is sitting on the cap tail of accurate right now uh that is correct okay so how do you structure that i mean why not just go out and start your own thing from scratch like what do you get from the parent company that like it was worth giving up a bunch of equity for um i think primarily was the biggest value add was being able to leverage the database uh that accurate built over the last five years sorry that accurate builder the parent company built i'm sorry that predict why it's built yes got it it's sorry it's called predict wise yes and they were exclusively working with e-commerce brands as well no predictwise is only working with political campaigns okay interesting so what does that have to do with predicting ltv now for mid-size e-commerce brands yeah so if you think about the problem that political campaigns face and how that relates to e-commerce is you know if you think about a political campaign there are a lot of swing voters and you're not quite sure which swing voters to actually target for different causes that they care about and so by understanding someone's foundational personalities behaviors and attitudes this would help figure out okay well let's target this voter in a different way because of what they care about the most and so it's very similar to e-commerce brands where you have a bunch of customers but it's not clear which ones to focus on and why and these e-commerce brands are primarily using purchase data but we know purchase data alone is not enough to predict future performance and so because we could bring in this external database to really understand who that customer is from a more holistic standpoint that helps really complete that view of who that customer is to inform when and how to intervene based on a combination of their ltv and their changes in behaviors interesting okay so got it so you get going about six seven eight nine months ago um coming up on your full year in business here how many customers are you now working with today yeah so uh since we launched acura officially we were able to close four enterprise customers in less than six months and so today we have a handful of customers but we plan to grow uh substantially next year and where'd those four come from was it do they come from product wise uh so all of our first customers aside for from two of them came from our existing network and we've been having a lot of uh success with outbound emailing campaigns to generate new customers interesting okay and so for customers times that uh i think you said six thousand dollars a month is sort of a fair average i mean you guys are doing like 20 30 000 bucks a month right now in revenue yeah that sounds about right and boots dropping or be raised so to date we've been revenue back but we're in the process of raising our first venture round okay got it oh and when you say revenue back has predict-wise uh like bootstrap so we were using um revenue we were getting from our customers to maintain the business okay so predict-wise when you did the spin out they didn't write you a big check to help fund early stage operations no so so how how did you fund yourself how did you pay your salary like the first month or two [Music] yeah so uh that first came from a first customer that we were able to close um more details are probably best to ask our co-founder and ceo but um i know what are you i'm on the founding team so i'm leading all of our go to market um i was one of the three uh first co-founders okay so how did you guys assemble that team did you just sort of say hey we're all equal we'll at least do 30 percent or what yeah so uh that's probably detail that our ceo is best uh share that with but um you know we started with these three that all started by working with predict-wise and decided to spin off into accurate but you shy away from answering like bigger questions which tells me like you you would they view you as a third co-founder do you have enough equity where they'd say yeah richard's a third co-founder um i have enough equity in the company where it makes me feel like i have ownership as one of the first people to join yeah so they might call you like head of head of marketing or something who's incentivized with equity versus like being a true sort of ground level stage one co-founder yeah i mean i think usually the co-founder title is when someone has over 10 equity um i have less than that okay fair enough fair enough got it okay cool talk to me about where you see future growth coming from what's what sort of go to market for the next 12 months yeah so um i'm confident that our total adjustable market is every single b2c organization in the united states uh but when we think about our service obtainable market like where we can land our first customers we're seeing the strongest traction in mobile gaming and companies that sell a good or a service as a subscription specifically with subscription brands um you know when people are purchasing at a similar purchase value it's really hard to figure out who to focus on and why and these subscription brands are usually the ones that are optimizing their business on ltv today and so we're seeing a lot of traction there as well interesting you mentioned you're thinking about raising now how much are you targeting uh so we're going to be raising um over seven figures in revenue um the exact number in that and the evaluation what do you what do you mean seven figures in revenue i'm sorry seven figures um in capital got it so you're raising more than a million dollars yes got it and so why is that the right amount uh it's right amount when we think about how much runway we need to get from our seed to our a and to close enough customers uh and grow the team in the meantime how many customers you can close if you have another million bucks so our goal for next year is to close a total of 20 new customers so 24 total which would you know obviously take you up past a million dollar run right uh yeah that sounds about right mm-hmm what's the team size today how many folks so we have about five full-time employees um i'm the only non-engineer on the team and we are currently hiring um more people for our first full-time sales people engineers and then we're also supported by a team of contractors that help us with sales marketing and engineering just to be clear...