How Versium Reached a $7M Run Rate, Growing 50 to 60% a Year (Interview with Chris Matty)

Introduction and Company Overview

Nathan Latka

00:00Hello everyone. My guest today is Chris Matty. He is leading a company called Versium, which delivered, which delivers automated predictive analytics solutions, which provide actionable data intelligence faster, more accurately, and at a fraction of the cost of hiring expensive data science teams or professional services organizations. Chris are you ready to take us to the top?

Chris Matty

00:18I'm ready.

Nathan Latka

00:19Alright. Well we're gonna talk everything Versium today. Tell me about the company. What do you guys do and what's your revenue model? How do you make money?

What Versium Does for Marketing Teams

Chris Matty

00:25Yeah. So we are we're data technology company. We help marketing organizations become highly data driven. What that means is we help them use data more effectively to drive all their marketing initiatives ultimately to drive significant improvements in marketing ROI.

Nathan Latka

00:39Okay and how do you... So there's a lot of tools out there that will do the predictive analytics. The biggest challenge is churn goes through the roof because you can't get them to actually take the data you give them and make actionable insights on it that improves their bot you know their top or bottom line. So what do you have to do in the first month to make your new users sticky?

The Three-Step Data Framework: Fix, Enrich, Model

Chris Matty

00:56Yeah, know the first step is and there's really three blocks to what we do, but the very first thing any organization has to do is fix the existing data they have. For example, 40 to 50% of data in a CRM is not usable. It's old, outdated, not formatted properly, errors, omissions. Data is a mess. Lots of times data resides in silos. The first step is you've got to get in and fix the data. That makes it

01:19more actionable. It allows you to reach your existing customers and prospects better, and it's the first step before you can do anything that has to do with predictive analytics machine learning or artificial intelligence because if you got the garbage going in you get garbage coming out. The first step is fix the data. The next step we do is we enrich the data. So we own over 1,500,000,000,000 data attributes and we're able to overlay that onto the

01:43existing data the organization has. That helps the company understand who their customers are better, makes it helps them understand their behaviors, their characteristics. We use clustering to create new segments that were previously not known or identified that had common characteristics. This then allows you to personalize your messaging. And then the last thing is we take those combined data sets and we train our artificial predictive models so that we can determine or build a predictive model to

02:11predict who's most likely to buy the products and services of our customers in the future and we use those models to guide the marketing efforts. First we fix it and clean it, then we enrich it, and then we model it.

Nathan Latka

02:22Great and give me the backstory here. So so we'll actually before I go to that in terms of when you launch the company, customers that are paying for this. Are you talking kind of a no touch high volume sales model or very much enterprise based? What's the average customer paying per month?

Pricing Tiers and Customer Segments

Chris Matty

02:35We've got two different tiers, right? Small, medium, or three different small, medium, and large. We've got a self-service tool with the average price point of 1,000 then we go to sort of mid tier markets. Per month. Mid tier markets which where it's five to seven and then the big enterprise grade which is you know 20 to $30,000. Based upon volume of exercising our platform which would generally ties to volume of customer records.

Nathan Latka

02:55Okay. Got it. So so I mean if I was if I was to just because I don't we don't have time to go on every customer cohort, but if I forced you on an average is it closer to a grand a month or $2 a month?

Chris Matty

03:05$10,000 a month.

Nathan Latka

03:06$10,000 a month. Okay. So this that's very much... That's a price point where you can afford to have an inside sales team. You can afford to have them spend six to twelve months closing the deal. It's a very different model than a a you know thousand dollar a month no touch sale.

Chris Matty

03:17That's right. Okay. We've productized this so we've automated the ability to do all of these things. Automation is a key theme here so we're not doing professional services. We run a high gross margin and so we've set out to productize all of these different data technologies which allows us to offer it at scale very effectively and cost effectively to our customers.

Nathan Latka

03:37Yeah sorry what I meant in terms of putting touch on each sale was before they've purchased right? So what the sales organization looks like? What is your team size today and how many of those folks are focused on sales?

Team Size and Channel Go-to-Market Strategy

Chris Matty

03:46We have a pretty small team on the sales side right and so primarily because we're using a channel strategy to go to market. We're working with marketing agencies and helping them to help their clients become more data driven so that they ensure their spend goes through the agency. So we are the data technology partner to agencies so we launched a business development effort to work with agencies as well as consulting services companies to help take our

04:08solutions to market. We do have a small direct sales team but we're seeing substantial growth using channel strategies and partners to get to market.

Nathan Latka

04:15And so Chris, what is the team size today?

Chris Matty

04:17Six people.

Nathan Latka

04:18Six people. Okay. Great. And then when was year one?

Chris Matty

04:22Year one was 2012.

Nathan Latka

04:232012. Okay. Very good. And then have you bootstrapped this or have you raised capital?

Funding History and Profitability Milestone

Chris Matty

04:26We've raised two seed rounds so a very capital efficient. 4,200,000 over two years. The last round was two years ago and we just notched our seventh consecutive quarter of being profitable. So we pretty much bootstrapped it. We didn't take big institutional money.

Nathan Latka

04:40Hey Chris congratulations. I wish more people celebrated folks like yourself. You need your own TechCrunch headline. Know we turned down a billion dollars of VC money because we're profitable right? That's that would be much better.

Chris Matty

04:50Well you know you control your destiny when you're not burning

Nathan Latka

04:53That's right. Okay, good. So bootstrapped, you raised... How many customers are you working with today?

Customer Count Breakdown

Chris Matty

04:58Oh gosh, we've got hundreds of customers. We got 300 companies using our APIs directly. We've got two fifty to 300 on a monthly basis that are the small mid tier folks and then we got about 50 enterprise clients that are paying us the bigger month, big money.

Nathan Latka

05:10Okay. So so if you just add it up just because I I'm adding all those together in my head, I can't do quickly. If you had just total customers, sounds like about 400, 500 something like that?

Chris Matty

05:18A 100 per month roughly.

Revenue Run Rate and Year-Over-Year Growth

Nathan Latka

05:20500 ish. Okay. And I mean can I take that 500 times the $10,000 a month number you just gave me and kind of back into a revenue figure of about 5,000,000 a month or no?

Chris Matty

05:29No. You'd have to go lower than that. So when you think about the volume of numbers, lower end skews that considerably. So when I said 10,000, that... That's probably not accurate average on on a per per customer basis.

Nathan Latka

05:40Okay. Got it. Well, if we go back down even to your minimum, right, of a grand per month, it sounds like that was what you gotta spend to get started. That's still about $500,000 in revenue. Is that more accurate in terms of your monthly?

Chris Matty

05:48Yeah. Yes. Pretty pretty accurate.

05:50We're at

05:507,000,000 run rate right now.

Nathan Latka

05:53Oh, great.

Chris Matty

05:54Targeting about 9,000,000... Eight to 9,000,000 this year.

Nathan Latka

05:56That's great. And take me back, give me a sense of growth. So you're at 7,000,000 right now. Where were you in July 2017 in terms of run rate?

Chris Matty

06:03So we've pretty much, we've grown about 50 to 60% year over year. So if we go back about a year ago, we were probably, I don't know four or five million run rate.

Nathan Latka

06:10Got it. So call it maybe 280, something like $280,000 a month?

Chris Matty

06:15Yeah, maybe 300. Yeah.

Nathan Latka

06:16That's good and where is most that most that growth come from? Is it coming from expansion revenue on accounts you already had or brand new accounts coming in?

Where Growth Is Coming From: Channel Partners

Chris Matty

06:23It's coming from working with agencies and the reason being is that the agencies are getting beaten up by the consulting service companies right Accenture is the fastest growing digital agency now the reason for that is that they're going in and solving these data problems and using data to guide the marketing effort we see 200, 300, 400% improvement in marketing ROI when we start helping organizations become data driven and so what's happening is that these you know Cognizant's, Wipro's,

06:48Accenture's, Capgemini's are going and solving data problems but all those organizations have created digital agencies now. So the traditional digital agency is getting beat up pretty bad. We come in and we say we will be your data technology partner. We will solve data problems, solve data silos, use our engine to drive your marketing targeting, and it's a great winning strategy and they're embracing us quite quite rapidly.

Nathan Latka

07:08Chris, what I was trying to get at there though is are you driving more growth over the past year from expanding customer accounts you already had upselling them or bringing on brand new accounts from channel partners?

Chris Matty

07:18Brand new accounts.

Nathan Latka

07:19Brand new from channel. Okay. And what's the kickback you give the channels? Why do they do it?

Revenue Share and Channel Partner Economics

Chris Matty

07:23Oh, they make dope. Couple of reasons. Right? In the case of the the consulting services company, make billable hours wrapping professional services around our capabilities but we also provide revenue share as an on an annuity basis for everything that comes through the pipe right so when you hit the Versium platform for data data cleansing or for data enrichment or for predictive targeting you know it's an ongoing SaaS based recurring revenue model and we're able to share

07:46in that revenue ongoing with those partners.

Nathan Latka

07:48So what is that like 30%? What's the percentage?

Chris Matty

07:5030 to 50%.

Nathan Latka

07:51Yeah. 30 to 50. Okay. So if I back into your CAC, right, if you're acquiring a $12,000 a year customer or a grand per month, you're willing to spend up to 3,000 or $4,000 in terms of the kickback to the channel partner to acquire that customer?

Chris Matty

08:03You know, I'd have to look at, you know, I don't know what our... I have to get our CFO to look at the CAC numbers to be able to answer that fully accurately, but we're definitely willing to invest in the partner to grow the business because it's an ongoing revenue stream. Early on with some of the new adopters we're just launching a new dev portal that allows developers to access via API. We'll be a bit more

08:21aggressive on the revenue share initially but we figured it'll settle out around 20 to 30% because they're also making money writing to those APIs or they're making money on the creatives that drive through the channel. So it's very it's a very synergistic partnership so we don't have to be too aggressive on our revenue share.

Nathan Latka

08:36Sure. Well, mean, would say though if you give them 50%, that's pretty aggressive. 30% is, know, a little obviously more or less aggressive, but...

Chris Matty

08:42Maybe the first year, right, to get the...

Nathan Latka

08:44Yeah. What's churn today?

Churn and Net Revenue Retention

Chris Matty

08:46Churn is very low. It's like below five to 7%.

Nathan Latka

08:49And that's revenue churn net per month?

Chris Matty

08:52You know, I don't know if that's on a logo. That's gonna be on a revenue basis, not logo basis.

Nathan Latka

08:56Okay. But monthly or annually?

Chris Matty

09:00Annually.

Nathan Latka

09:00Oh, and... Okay. Good. Yeah. That's really healthy. Good. And and that's net or gross?

Chris Matty

09:05You know, that's a financial question. I have get my CFO to answer that. I don't know. I'm not sure what

09:10you're

Nathan Latka

09:10Are you are you... It's a big difference though. Right? So five to 7% rev, you know, churn annually. Basically, are you adding back expansion revenue or not? Do you know?

Chris Matty

09:18We're adding back expansion.

Nathan Latka

09:19Okay. Got it. Got it. So so good. That's helpful to understand. So five, five to 7% revenue, churn annually, and that's on a, on a net basis. That's great. Well, I mean, what do you think you have to do to get to kind of net revenue retention annually of over a 100%?

Chris Matty

09:35Net revenue to

Nathan Latka

09:36Sorry, sorry. What that would mean is you would build an inside organization to basically drive more expansion revenue. The only way to get to net revenue retention like higher than a 100 is to basically drive significant expansion revenue. It sounds like you've got some pricing axes that allow you to drive upgrades pretty easily, but you don't have an inside sales team built yet to drive that you... That adoption.

Chris Matty

09:54Well, know, the the interesting thing is as we start getting in the ad tech space and start having our AI engine driving recurring revenue in the digital spend, that's where the expansion grows substantially because the the... Then it correlates to the ad spend of the business. And so where we're doing some interesting things is in the b to b ad tech arena. The b to b ad tech arena in terms of digital has been pretty nascent

10:14because most of the the targeting in the ad digital ad tech is tied to consumer entity data. We have the unique ability to overlay consumer entity data on the business data that allows us to target and increase reach by 4x. So we're seeing big growth in B2B digital spend and that spend is a ramp up which is how you get to expand revenue on a per logo basis.

Nathan Latka

10:35Yep. I'm an enterprise. I just signed up with you. Janefreshworks.com is in my CRM. She, I don't know this, but she moved jobs to, you know, a year ago and has a new email address. I just signed up for you. How do you know that she's moved that's not her email anymore? What is your source of truth?

Data Sources and Competitive Differentiation

Chris Matty

10:51We're constantly... We pull in... So we've got literally 10,000 files. So we've got 60 or 70 different sources that we're pulling in from a business data standpoint as well as we're doing our own crawling and indexing looking at resume website things of that nature.

Nathan Latka

11:07So unstructured data on kind of crawlers web scraping?

Chris Matty

11:11All of the above right and so there are different types of sources you have. Now you're not gonna be 100% accurate with any one file, but we will be industry leading based upon all of that, as well as applying ML based models to predict certain things. Now that's all in the business data. Now you start... What gets really interesting is when you're able to overlay consumer perspectives on top of that as well. So that gives you

11:32insight. If all of sudden you see a physical address from the household which is a non consumer based attribute and that changes, now you might have an indication of change of city, there's probably likelihood there's been a job change. Right? So that's an example of how get insights from something that might be more of a consumer app to it I. E. Household.

Nathan Latka

11:49Where are you getting that consumer data from? Same thing unstructured data?

Chris Matty

11:53It's same type of thing. We've got over 20,000 different fields of data columns of data we can overlay both business and consumer and so you think about it when you're building a consumer model who you are as a business person there's signal there right if you're a CPA at a fortune 100 company.

Nathan Latka

12:09Yeah no because I get I get the product. I get the value. I'm just trying to understand where you're unique. Let me ask you a different question. How much are you spending per year on your own data sources, data you're ingesting?

Chris Matty

12:20So what's interesting, we own all of our data, right? So we're not licensing data from the Acxioms and DFBs or in fact we supply data to companies like that.

Nathan Latka

12:28What about the FullContacts, the Clearbits, things like that. DiscoverOrgs.

Chris Matty

12:32Talk to all those folks, supply data to some of those folks, get data from some of those folks, depending on the nature's right? So

Nathan Latka

12:39That's problem. That's where I get confused in this market, Chris. Sorry. I hate to cut you off. We're running out of time though, but this is the part like, it seems so incestual. Everyone buys everyone else's data or if they don't wanna use the word buy, they trade it. You give and they get... The problem is like, there's... What is the source of truth? Like, what is your unique data capturing thing that I would pay you

12:56for versus I wouldn't get from anybody else if everyone just shares the data anyway?

Why Technology Beats Data as a Commodity

Chris Matty

12:59So data is a commodity. That's the fact of the matter unless you have a very unique source. So there are some unique source. I certainly wouldn't probably share that on the airway source or how we get those. We apply certain technologies that allow us to do some things but even if you have a unique source I give that a you know a somewhat fraction of value because eventually becomes a commodity. It's about the technology you wrap

13:20around the data. Our identity matching engine, which is leveraging thirty years of experience dealing with the challenges of consumer business entity data. Our automated ETL processing and data hygiene engine that cleans up data very rapidly. Our automated pipeline. I'll give you an example. One of the competitors in the space to quote one of our customers it takes them nine years to build a predictive model they may have met nine weeks or even if they met nine

13:44days we can build a predictive model in a matter of a couple hours and that's that takes the data in it cleanses it it standardizes it, it enriches it with our proprietary data, and then it pops it into an automated AI based modeling pipeline. Throughout that entire process, I mean that's six years of work we've done productizing and automating a technology layer around the data. So the differentiation yes, data is unique. Yes, data is powerful. We'll

14:10go head to head against anybody that has Acxiom's data or any other data source, any other data source. Even if we gave them our data source, we would beat them because it's what we do with the data with technology layered or around it. So data is a commodity. If you're just a data business, then you're gonna be treated as a commodity. If you're a technology company, you're gonna get the multiples.

Nathan Latka

14:28Let's wrap up here in a second. Two quick questions before that though. Are you raising capital right now?

Potential Capital Raise and Growth Plans

Chris Matty

14:32We are in process looking at various ways to grow the company. Capital raise is certainly one of them and you know, we've got some good things coming down the future.

Nathan Latka

14:41If you are considering raise, you've modeled kind of where you would spend the money. So I am curious, right? So if you did raise today, how much ideally would you be looking to raise to fund your growth plans?

Chris Matty

14:49Yeah so where this whole industry is going there's a lot of companies that are being features I should say being run as companies. You're either the platform or you plug into the platform so we believe that the future is the customer data platform which is going to be the centralized data storage within the enterprise from which all marketing is driven if you want to achieve the benefits. So that's the direction we're headed. We believe we'll have

15:11a unique solution in that direction. Dollars 20,000,000 to $30,000,000 gives you the funding. You don't need to go raise 50, 60, 70. I mean 20 to 30 gives you enough to build out the team on the tech side, mostly invest in sales and marketing.

Nathan Latka

15:23Is that what you're aiming right now? You're gonna go raise about 20 or 16 to give you a total 20?

Chris Matty

15:27Somewhere between 15 to 25 depending on structure of the deal.

Nathan Latka

15:32Okay. And you'll sell somewhere between call it 10 to 30% of the business something like that?

Chris Matty

15:35Target 20%. Yeah.

Famous Five Rapid-Fire Questions

Nathan Latka

15:36Yeah. Very good. Okay. Good. Let's wrap up here with the famous five. Number one, what's your favorite business book?

Chris Matty

15:41Oh, my favorite business book. Let's see.

Nathan Latka

15:46Or when you read?

Chris Matty

15:48I

15:50said I don't have much time to read books to be honest, but you know, subtle art of not giving f.

Nathan Latka

15:55Very good. That's a good one. Number two, is there a CEO that you are following or studying right now?

Chris Matty

16:00You know, I kinda find Elon Musk to be pretty interesting.

Nathan Latka

16:03Yep.

16:04Number three, is there a favorite online tool that you have to build your business besides your own?

Chris Matty

16:08Favorite online tool? Oh, that's an easy one. Email. You'd everything done from me in three

Nathan Latka

16:08What do you use?

Chris Matty

16:08You didn't have email, you'd be dead.

Nathan Latka

16:15What do you... Gmail?

Chris Matty

16:17Yeah. Gmail.

Nathan Latka

16:18Number four. How many hours of sleep are you getting every night?

Chris Matty

16:21Oh, five or six.

Nathan Latka

16:22And what's your situation? Married, single, kiddos?

Chris Matty

16:25I got two boys, 11... I got three startups, Versium, [...].

Nathan Latka

16:29Good.

Chris Matty

16:2911 and 13. So between running around the soccer and being a single dad and a CEO, I got my hands full.

Nathan Latka

16:35I was about to say you surely do have your hands full. And how old are you?

Chris Matty

16:39Shoot. I forgot.

Nathan Latka

16:41That's probably

Chris Matty

16:41That's not I think I'm only as old as my... As relative age of my kids. Right? I just turned 50.

Nathan Latka

16:4650. Okay. Last question. Take us back thirty years. What do you wish your 20 year old self knew?

Chris Matty

16:52What do I wish my 20 year old self knew?

16:57Wow, jeez, when I was 20, I didn't know a whole lot.

Nathan Latka

17:01That means you can answer almost anything and be right.

Chris Matty

17:04You know, I think

17:07my 20 year old self, what did my you know, I think I think this question is a deep philosophical and I don't know whether I make it personal or business. Think...

Nathan Latka

17:16Give me personal.

Chris Matty

17:16Extreme confidence.

Nathan Latka

17:17Have extreme Success will come.

17:21Guys, there you have it. You're confident Move with passion. If you're confident, you move with passion, success will come. Coming from Chris, launched Versium back in '2, 2012, ended up raising about $4,200,000 to service about 500 customers paying a grand per month, doing about $580,000 per month right now, about $7,000,000 per year. That's up from about a 4 or $5,000,000 run rate just about a year ago. So healthy growth. A lot of his growth right now

17:43is coming from channel partners. He pays 30 to 50%. They're churning about five to seven percent five to 7% of the revenue annually again. And what they're doing is again, you connect up your data source with them, your CRM, they first make sure all the data is accurate, but more importantly, he's really focused on wrapping proprietary technology tools around the data so you can get more value out of it faster. Potentially going out right now raising

18:02call it, know, $20,000,000 or something like that selling call it 10, 20% of the business. Chris, thank you so much for taking us to the top.

Chris Matty

18:09Thank you very much.