SaaS Interviews with CEOs, Startups, Founders
He Sold his First Company for $425m, Here's What He Did Next
12 Jan 2023
Chapter 1: What insights does the guest share about company valuation?
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Again, both plural founderpath.com forward slash products forward slash valuations. You are listening to Conversations with Nathan Latka, where I sit down and interview the top SaaS founders, like Eric Wan from Zoom. If you'd like to subscribe, go to getlatka.com.
We've published thousands of these interviews, and if you want to sort through them quickly by revenue or churn, CAC, valuation, or other metrics, the easiest way to do that is to go to getlatka.com and use our filtering tool. It's like a big Excel sheet for all of these podcast interviews. Check it out right now actual pipeline looks like based off a contributor model.
There's a free tool they use to get this data. They've got 101 folks on the team today. They've quote unquote bootstrapped it, put in a lot of their own money to fund it up to date as they look to continue to scale. Got their first paying customer in 2012, broke a million dollar run rate in 2014. Hey, folks, my guest today is Stephen Messer.
He currently serves as co-founder and vice chairman of Collective Eye. Prior to Collective Eye, he co-founded and served as CEO of LinkShare until its sale to Rakuten for $425 million. He received a Bachelor of Arts degree from Lafayette University and his Juris Doctorate from Cardozo School of Law. All right, Stephen, you ready to take us to the top? I'm going to do our best. All right.
What was it like? I guess before we talk about Collective, what was it like at Recruit? I mean, were you sort of joining in as Art of the Titanic? You just had to drive the right way? Or were you still in building mode? No. So when LinkShare got acquired, I mean, we had been doing it for about 10 years. So affiliate marketing became a thing under LinkShare. We were the first affiliate marketer.
We became the global player. I think when we finally sold the business to Rakuten, it was... probably 96% of the affiliate market globally, and still is today. It's just behind the scenes that most people don't know. So when we came there, it was the first American acquisition they had made.
And I think to this day, it's probably still the greatest revenue producer outside of Japan that Rakuten has ever had. Robert Leonardus Interesting. So everyone's going to want to know, a $425 million acquisition price, do you get filthy rich on this? Or how did that work out? Robert Leonardus Well, Filthy Rich is always in anyone's eyes, right? It depends what you want.
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Chapter 2: How did Stephen Messer's experience at LinkShare shape his career?
Right. The odds are going to start changing as the buyer's behavior starts changing, as they don't bring in the right people, as they start communicating different things or they say things like, oh, that's really interesting. Can you send me this piece of information? But that always means they're not interested in buying.
The thing is, you just don't know it because for you, it's your first experience with this buyer. But when an AI is observing multiple people selling that same person, it can spot it cold. Oh, I see. And it starts guiding you and figuring it out. So you're not looking in the inbox of the ClickUp prospect. ClickUp is giving you access to their sales team's inbox.
And you're looking at response times or length of the email or the questions asked by the potential buyer in the ClickUp head of sales email inbox. Down to that individual. We're talking about almost close to a million different data features. So that's a lot of data that we're able to observe that say, okay, this person is likely to buy or not likely to buy. And it helps us really understand it.
And today we track about 5% of the globe's B2B economy. So we see a lot of that data and we see that interaction. So we can tell you, here's what's happening. So how many companies like ClickUp have Collective AI basically installed? They're using you. It's everyone from Fortune 5 companies down to SMB. But how many? We don't disclose the actual number.
We usually just disclose about 5% of the globe's B2B economy is passing through us every day. We have no idea what that number is, so we don't know what 5% means. Let me put it in perspective. Amazon is the equivalent of 5% of B2C. So it's the Amazon of B2B data. It's a lot of transactional data. Billions of dollars are passing through us.
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Chapter 3: How did LinkShare revolutionize affiliate marketing?
And we're just observing how people are buying and selling and getting their deals done. Do people have to go to Collective AI and sign up? Is there a way for you to get access to inboxes like ClickUp Sales Team without ClickUp CRO signing up for Collective AI? You can go to intelligence.com and get the free version.
And for sales professionals or any individual contributor, they'll always be able to get access to the product for free forever, which includes free contacts. You don't have to pay for it if you're going to Zoom or Seamless or those other players. You get free contacts forever.
You get free relationship mapping, free activity capture, free deep collaboration, daily forecasting and daily odds on your deals. You will get that free forever just by going in and signing up and connecting two APIs, email calendar and CRM to start. Okay. If a company wants it, they pay. They always say if it's free, you're their product.
So people sort of understand that's what's happening here. You're using collective intelligence, which is great. I guess walk me through the backstory here. So how many folks are on the team full time today? About 140 in the company. Okay, 140. How many are engineers? Almost the entire company is engineering. Who does marketing, sales, products, CFO? Very small team.
And the product spreads itself very quickly. It's very viral for sales organizations. When you join, the first thing you do is you have the ability to automatically add anybody who's helping work with you on a deal. So the first thing is, let's say I'm a sales professional and I'm working with three other people, a sales engineer, a finance person, a legal person.
It will automatically invite them to join for free. That brings them in where they can actually work collaboratively on a single deal. There's no cost for that. That helps it grow. When you have connectors, which is a product that helps you find which friends of yours actually know the buyers that you're trying to reach and how well do they know them? Well, you just click for free.
They can invite and join people. That's predominantly how we scale.
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Chapter 4: What was the impact of the $425 million acquisition on Stephen's life?
But Steven, Gabriel Koning on LinkedIn is listed as one of your content writing folks on your marketing team. How many people are non-engineers like Gabriel? Maybe 15, 20. 20 folks. Okay. Not a large group. Yeah. Okay. Got it. So about 120 engineers. Obviously, that's expensive. Are these all in the US? Engineers in the US? Mostly in the US. A few are around the world.
Again, deep learning is not a simple piece of technology to build, manage, and scale. They call it the Game of Kings for a reason. Yeah. And is this all freemium right now? Or do you have folks that pay? And if they're paying, what do they pay for? So the people who pay in our products, if you think of our model, it's not a SaaS model. It's what's called the data network or community model.
So if you're familiar with Waze, you know that as a consumer, I'm sorry, as a contributor of data, by using the product, you get the product for free. That's the individual contributor. When you're a consumer of the data, in the B2C world, that's usually advertisers. So that would be like Dunkin' Donuts or Starbucks paying for an ad. They're the person who pays. In our world, it's B2B.
So it's really leaders and managers of a sales organization who want to get visibility into daily forecasting, know which deals are real, which ones aren't, to be able to do deal inspection, to understand what's going on. For those people, they're going to buy the product on a per seat basis while their team gets it for free. I see. Okay. That makes sense. And give me a sort of range here.
Are we talking like $10,000 a month contracts, $100,000 a year contract? What's sort of the range of ACVs you're looking at? Usually you're looking at per manager, roughly around $9,000 a year per manager. So depending on how big your team is. So our ACV is usually above $100,000, but we have SMBs all the way up. Got it. And someone paying you $100,000 a year, that would be like what?
Like a team of seven or eight, something like that? Yeah, exactly. And then you're talking about also their sales organization. They might use us for another product we offer called Intelligent Writeback. For those of you who have CRM, we're trying to give your CRM hygiene. If you want all the activity data and contact data that we capture, push back into your CRM.
That's another product we offer called Intelligent Writeback. Okay. Now, I don't think you've bootstrapped. I think you've raised a bunch. Walk me through your funding history and why you decided to raise it. No, we actually bootstrapped the whole thing. The business has been funded by us. Oh, you were the $20 million Series A?
There is no $20 million Series A. It's actually much more money than that into this company. AI companies, you're usually talking about usually north of $100 million to get these companies off the ground. Why do I see a Series A $20 million deal on your profile on Crunchbase? Not accurate? We have no idea how that got there or who even put that in there. People keep asking.
I have no idea where that came from. Got it. Got it. So you guys are... I mean, look, you had a nice exit. So you've basically funded this yourself. No outside investors. No outside investors. Okay. I love that. So then you're bootstrapped. I mean... In the grand scheme of things, I guess, yes, you could call it that.
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Chapter 5: What challenges did Collective Eye face during its early years?
Do you remember how you got your first paying customer? Tell that story. Yeah. Look, it's funny. In data networks like ours, you're actually not trying to get paying customers in the beginning. You're trying to figure out how to get data. And the challenge with neural nets in particular is they tend to be really bad until you get data scale.
And so the first ways we went out and signed our customers up were people were trying to solve the hardest problem in sales that's out there, which is forecasting. We went to one of the largest publicly traded companies in the world and said, let us be your first partner. Let us be your data science arm outsourced.
Sign up for this new model that allows for sharing of data, but in a confidential way. The thing about neural nets is they're black boxes. People used to beat up on that a few years ago. Oh, it won't explain to you why it's working, even though it's really good. Today, that black box is actually the reason why people realize, if I contribute my most proprietary data, it won't matter.
It's totally safe. It's a black box because it can never tell me about what's going on. These guys realized that early on and said, if you're willing to bring that technology to bear, you're willing to fund that, we'll sign up. And that is to this day, our first customer still exists. Got to be. 20, probably 2011, 2012. Okay. So that's, I mean, you're on a big check.
I mean, 2008 to 2012, all pre-revenue, all about getting data. You're putting your money out going, okay, I hope this bad boy works. Well, we weren't 140 people at that point. And you have to remember neural net technologies while they've been around since the sixties, that was when Google brain first proved that it really worked well.
And a lot of my buddies were over at Google Brain at the time, and they were the ones saying, you've got to get back into this. You've got to look at this. And so we spent a good four years trying to figure out, how do you make this stuff work? How do you make it work at scale? Because remember, most people weren't really able to get this stuff working very well.
They were going to areas like transformers, like NLP, where they thought, okay, maybe we can get this stuff to work. It really took a lot of R&D, and we spent a lot of time figuring out how these business models worked. I think it's why it worked so well for us and why we're still the only one in our marketplace who's able to use these technologies as successfully as we've been.
It's also why our business model is the only one like it. So 2012, first customer, it was this publicly traded company. How many customers are you now serving today? I mentioned we only give out the 5% of B2B GDP that we track.
And we do that intentionally because our customers are contributing their data and they want to know that they're not helping this person or that person's not helping this person. So we give them a sense of scale, just like ways to say, hey, look, there's more drivers on the road than any other solution out there. Steven, I understand you can only share so much data.
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Chapter 6: Who are the main customers of Collective Eye and what do they need?
How much time do you think you need to get up above 100 million? uh so again we're not disclosing revenue numbers out here but what i can tell you is that number would be wrong um and remember that's because you're thinking about it as a sas business we are not a sas business we're a data network business We scale it in a vastly different way. All I'm doing is I'm looking at your headcount.
So unless you're burning millions of dollars per month and you're continuing to fund it, which you could be, by the way, that's probably your revenue per employee is going to be around 120 to 180. You're saying it's not. It could be higher. It could be lower. You're not wanting to share. It's the same thing, by the way, LinkShare.
If you look at LinkShare, the revenues, if you try to look at it as a SaaS model, that's not how we grew exponentially. We didn't grow linearly. I'm not talking SaaS model. SaaS businesses are linear. I'm not talking tax. I'm just talking revenue per employee in general. It's a different metric the way you'd look at it.
It's like saying, look at a revenue like Facebook or TikTok on a revenue per individual. That wouldn't work the same model. Well, I'm not talking about individual. I'm not talking about individuals and the network. I'm talking about revenue per employee.
Chapter 7: How does Collective Eye utilize AI for sales forecasting?
No, no. Employee. Yeah. Yeah. So you're saying your revenue per employee is more analogous to a Facebook, right? Which is millions per employee versus a traditional B2B SaaS. I think that'd probably be a better way to think about it. Yeah. Yeah. That's fair. That's fair. All right. Very cool. Let's wrap up here with the famous five. Number one, favorite business book?
Of all time, Crossing the Chasm. Number two, is there a CEO you're following or studying? I think it's always Reed Hastings. Number three, what's your favorite online tool for building collective? Recently, chat GPT. Number four, how many hours of sleep are you getting every night? I always get eight, no matter what. That is good. Situation, married, single kids? Single. Any kids? No kids.
No kiddos. And how old are you? I'm 52. 52. Last question, something you wish you knew when you were 20. I'll give you the piece of advice that I wish I knew when I was younger that one of my board members gave me, which is you have a choice in life. You can work really hard when you're young or work really hard when you're old, but you're going to be one of the two.
So I pick young if you're smart. Guys, work hard when you're young. He built his first company over nine years, sold it for $425 million. It's called LinkShare. Very nice, obviously, business model there. Two years later, went into a new business called CollectiveEye.com. Think of it as building neural nets, really trying to help CROs at
companies understand what their actual pipeline looks like based off a contributor model. There's a free tool they use to get this data. They've got 101 folks on the team today. They've quote unquote bootstrapped it, but put in a lot of their own money to fund it up to date as they look to continue to scale.
Got their first paying customer in 2012, broke a million dollar run rate in 2014, scaling from there. Stephen, thanks for taking us to the top. Thank you for having me here. Really great opportunity to speak with you and I love your show.
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