Collective[i] Revenue (2024)

[00:00] Guys, work hard when you're young. He built his first company over nine years, sold it for $425,000,000. It's called LinkShare. Very nice, obviously, business model there. And two years later, went into a new business called collectivei.com. Think of it, you know, 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 a 101 [00:23] folks on the team today. They've quote, unquote, bootstrapped it, put 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 cofounder and vice chairman of collectivei. Prior to collectivei, he cofounded and served as CEO of LinkShare until its sale to [00:45] Rakuten for $425,000,000. He received a bachelor of arts degree from Lafayette University and his Juris doctorate from Cardozo School of Law. Alright. Stephen, you ready to take us to top? [00:56] >> I'm gonna do our best. [00:57] Alright. What was it like just, I guess, before we talk about collective, what was it like at Rakuten? I mean, were you sort of joining it as already the Titanic? You just had to drive the right way, or were you still in building mode? [01:07] >> No. So when LinkShare got acquired, I mean, we had been doing it for about ten years. So affiliate marketing became a thing under LinkShare. We were the first affiliate marketer. We became the global player. I think when we when we finally sold the business through 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 [01:29] >> 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. [01:38] Interesting. So, I mean, everyone's gonna wanna know a $425,000,000 acquisition price you were CEO. I mean, do you get filthy rich on this, or how did that work out? [01:45] >> Well, filthy rich is always in anyone's eyes. Right? It's what depends what you want. Look. We were fortunate in the sense that we didn't come from a lot of means, but we had worked really hard, we had built the business, it had become quite successful, it had grown really quickly. More importantly, it had enabled every other entrepreneur to make a living off their business in a way they couldn't have done today. So when you look at [02:05] >> the creator economy, when you look at people who had blogs, podcasts, well, all of them were making commissions on sales from referring people to other websites. And that was really what LinkShare enabled. For us, it was just a joy to be there. So while I think we did very well and I'm very happy with how we performed and the results we got, what I'm most happy is every month we were sending out millions of dollars worth [02:28] >> of checks to people and changing their lives. So I hope that business continues to change lives of all the great entrepreneurs that are out there probably listening to this amazing podcast. [02:39] I love that. Yeah. You found it in 1996, sold on 2005, so it's a while ago now. Do you ever look back and go, oh gosh. We could have taken that to, like, 10,000,000,000, or no. It was the right time. 425 was the right number. [02:49] >> You know, I don't think you ever look back as a founder. You know this. Right? Nathan, you speak to great people all the time. You've built great things. What you know more than anything else is that there's always another thing to build and always another opportunity to scale. And I'm really proud that LinkShare to this day is still a dominant provider in its space. I'm happy that collectivei is a dominant provider in its space as well. [03:11] >> And I'm happy to be associated with a whole bunch of other companies, whether it be on their boards or helping them get started. And I don't I don't think that'll ever stop. [03:20] Alright. Let's talk about collectivei. You launched, I think, in 2008. Walk us through who who's who's paying for this, and what are you giving them? [03:27] >> I mean, look, the benefit of having the exit that we had and a whole bunch of others is that it enabled us to fund something that probably people wouldn't have done. We are neural net based technology. So for anyone who's used ChatGPT recently or stable diffusion, you're starting to, for the first time as an individual, feel the power of this neural net AI that people like us have been talking about, but you had to be a [03:50] >> real practitioner in this stuff. And we just had a great opportunity to be on that forefront of that group that today is, OpenAI is not a young company, it's been around for almost a decade as well. We have all started at the same time. We're all getting to this inflection point where these technologies are just dominating the way we think about how the future of work will be. [04:13] Oh, what's going on there, YouTube? Good to see you guys. Now imagine this, you love watching these interviews with SaaS founders, but imagine if we took all of the valuation data out from over 2,807 interviews I've done manually, saves you a lot of time. Well, we've done this. We've built it into the beautiful interface inside of Founderpath. Check this out. I'll show you how you can access this in a second. But you log in, you connect [04:37] your Stripe account, you see your valuation real time. You can see what it changed over the past eighty eight days and even set goals for valuation this year. Now the secret evaluation is there's many different ways to value a SaaS business. So the reason you're gonna see three or four different valuations inside of your Founderpath dashboard, this is all free by the way, is because depending on who's doing the buying of your SaaS company, you're gonna [05:01] get a different valuation. A VC is gonna pay a different valuation, Private equity firm is different. If you're gonna do a minority sale, that's different. And if you sell the whole business, that's a different valuation. You can see all those when I hover over here. Right? So the teal is what a VC would pay. Yellow is what private equity And red is if you sold the whole thing outright. Now what's cool about this is this is [05:23] not built off random data. Again, you guys hear these interviews on YouTube. All these datas are built from real time valuation data points founder share with us on the show. So traction 1,200,000 seed round 3.7 raise. They sold 22% of their business. Go in here and filter by the event. Maybe you only wanna see companies that have sold the whole business. Well, here are a bunch that have been acquired the valuation and the multiple. Maybe you're [05:49] going out right now and you're raising your seed round. We'll go in here and look at all this recent seed deals that went down, what they raised, what valuation they raised at, and what percent that they sold. There's never been a larger dataset of SaaS valuations than what you can get now inside of Founderpath. And we're thrilled to bring it to you. All right, we're gonna go back to the YouTube video here in a second, but [06:10] if you wanna check this tool out, if you wanna jump in and sign up, you can check it out for free to get your valuation at this link, this link, founderpath.com/products/valuations. Or if you go to founderpath.com and hover over products, click on get your valuation here, and go ahead and sign up to give it a whirl. Again, all that valuation data live right inside the platform. I hope to see you there. Alright. Let's jump back into [06:37] the interview. So who who is buying collectivei today? What's your main customer segment? [06:42] >> Yeah, so we sell predominantly to sales organizations. So when you're thinking about it, if you run a sales org, you probably have no idea what they're working on, have probably no idea what revenue they're going to bring in. You're trying to figure out what's changing in the market because it's always changing, and you're trying to figure out how to manage more effectively. Well, that is essentially what we saw. We removed the need to log anything for [07:02] >> those people who are suffering in CRM every day. Imagine a world where the AI did the work of logging all the people you spoke to, the conversations you had, the communications that went back and forth. Imagine if it did that automatically. Then imagine if it told you which deals were real. And the reason it did that was because just like Waze, it's observing other sellers in our network and seeing how the buyer's behaving when they buy, [07:24] >> when they don't buy, down to the individual. So it's telling you every day if this is a deal you should actually pursue. And you may not know this in sales. They had this saying, Buyers lie, because you never really know if they're interested or not. Well, imagine if the AI could tell you, No. No. They are really interested or- [07:39] mean, are you buying or sitting on the same intent data that Bombora and some of these other providers are sitting on, or do you have a unique dataset? [07:46] >> It's a unique dataset. So if you think about it in sales, my experience when I close a deal is mine. I you can only find out about it if you hire me to work on them again. But in our model, we're observing every transaction of every customer, just like Waze observing your journey without Well, having to do it they're giving us access to their CRM through the API, email, calendar, phone, video conference. So just behind the [08:10] >> scenes, we're logging all that activity. We're also observing what's actually taking place. And in a confidential way, it's all all abstracted away. Like, no one knows that you've left your home, but they know the fastest route because when you've been driving, it's guiding ways to learn about that journey that they can share with the next person who's behind them to find the fastest route. [08:29] So, Stephen, me give an example here. ClickUp ClickUp's CRO might pay for your software so that they can get an understanding of their top 10 deals. They think they're gonna close in q one, but, oh, crap. They just saw that one of those deals purchased Basecamp, a competitor. They're now not a deal. How do how do you give them the information that the ClickUp prospect just bought a competitor? Do you get receipt data from that person's [08:54] inbox, or how does that work? [08:55] >> So the way we deal with it is we're actually it's a better way of thinking about it is by observing sellers across multiple buyers, I can spot when that particular buyer is behaving like they're gonna buy or not. Because for all the AI knows, they may buy both, right? I don't think they're going to. But let's say they make a mistake and they buy the wrong product. Right? The odds are gonna start changing as the buyer's [09:16] >> 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 [09:36] >> starts guiding you and figuring it out. [09:39] So So you're you're not looking in the inbox 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, like, response times or length of the email or the questions asked by the potential buyer in the ClickUp head of sales email inbox? [09:57] >> Down to that individual. We're 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. [10:18] How many companies like ClickUp, [10:20] how many companies like ClickUp have Collective[i] basically installed? They're using you. [10:25] >> It's everyone from Fortune five companies down to SMB. It doesn't [10:29] But how many? [10:31] >> We don't disclose the actual number. We usually just disclose about five percent of the globe's b two b economy is passing through us every day. [10:37] Well, I have no we have no idea what that number is, so we don't know what 5% means. [10:40] >> Well, let me put it in perspective. Amazon is the equivalent of 5% of b two c. So it's the Amazon of b two b data. It's a lot of transactional data. Billions of dollars are passing through us that we're just observing how people are buying and selling and getting their deals done. [10:56] Do people have to go to collectivei and sign up? Like, is there a way for you to get access to inboxes like ClickUp sales team without ClickUp CRO signing up for collectivei? [11:08] >> 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 that you don't have to pay for if you're going to Zoom or Seamless or there's 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 [11:33] >> that free forever just by going in and signing up and connecting two APIs, email, calendar, and CRM to start. [11:39] Okay. A company wants it, they pay. [11:42] They always say if it's free, you're the product so that they 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 so how many folks are on the team full time today? [11:55] >> About a 140 in the company. [11:57] Okay. 140. How many are engineers? [12:00] >> Almost the entire company is engineering. [12:02] Oh, who does marketing, sales, products, CFO? [12:06] >> 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 [12:29] >> 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, that you just click for free. They can invite and join people. That's predominantly how we scale. [12:49] But, Stephen, like Gabriel Koning on LinkedIn is listed as one of your content writing folks on your marketing team. Right? How many people are non engineers like Gabriela? [12:59] >> Maybe fifteen, twenty. [13:01] 20 folks. Okay. [13:02] >> Not a large not a large group. [13:04] Yeah. Okay. Got it. So about a 120 engineers. Obviously, that's expensive. Are these all in The US, engineers in The US? [13:10] >> Mostly in The US, but fewer 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. [13:19] 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? [13:25] >> So the people who pay in our products so if you think of our model, it's not a SaaS model. It's what'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. The individual contributor. You're a consumer of the data, in the B2C world, that's usually advertisers. So that would be like [13:45] >> 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 wanna 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 gonna buy the product on a per seat basis. [14:07] Okay. [14:07] >> While their team gets it for free. [14:09] I see. Okay. That makes sense. And and give me a sort of range here. Are we talking like a $10,000 a month contracts, a $100,000 a year contract? What's sort of the range of ACVs you're looking at? [14:18] >> Usually, you're looking at per per manager roughly around $9,000 a year per manager. So depending on how big your team is. So our ACV is usually above a $100,000, but we have SMBs all the way up. [14:31] Got it. And someone paying you a $100,000 a year, that would be like, what, like a team of seven or eight, something like that? [14:36] >> 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 are CRM who are trying to give your CRM hygiene, if you want all the activity data and contact data that we capture pushed back into your CRM, that's another product we offer called Intelligent Writeback. [14:53] Okay. Now you I don't think 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. [15:01] >> No. We actually bootstrapped the whole thing. The business has been funded by us. And [15:06] Oh, you were the 20,000,000 series a? [15:08] >> There there is no $20,000,000 series a. It's actually much more money than that into this company. AI companies, you're usually talking about, you know, no usually north of a $100,000,000 to get these companies off the ground. [15:20] Why do I see series a why do I see a series a $20,000,000 deal on your profile on Crunchbase? Not accurate? [15:28] >> We have no idea how that got there or who even put that in there. [15:33] >> People keep asking, I have no idea where that came from. [15:36] 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. [15:46] >> I mean Well In in in the grand scheme of things, I guess, yes, you could call it that. I think I think we've acted as the venture capital investor in this deal as as we think this is just probably the biggest opportunity we've ever come across. [16:00] I mean, are you comfortable sharing how much you've put on the line here? I mean, how much does this mean to you? [16:05] >> Look. I I I think, like all investors, you put everything out there. You know? Elon, who's an old friend, you know, will tell you, you put everything you have into these things, your heart, your soul, and your wallet. And and we are proud to be doing that because we believe in this mission. [16:20] So no safety net. Let's assume you made a $100,000,000 on there on the deal when you sold LinkShare. You put all a $100,000,000 into collective. [16:27] >> Well, let's hope one one, I hope we made more than that, which we did. And thankfully, we it's not a question of putting all of it in. I think it's a question of is how big is the opportunity? How fast is it growing? And can we make this a multibillion dollar business, if not trillion dollar business? And we believe we can. [16:43] Alright. Very cool. Any plans to raise outside funding or no? You'll keep keep doing what you've been doing? [16:48] >> Look. I think the business is you know, I had a great one of our our our old investors and now board members, a guy named Julian Brodsky, who's the cofounder of Comcast, told us, you know, focus on building a great business. You you can determine whatever it takes to get there as you go. And and that's exactly what we're doing. If someone said, hey. Here's a huge amount of money. I don't know if it would make [17:11] >> a difference, but if they said, hey. Here's some money and some some other way to grow the business faster, we'd always consider it. But I don't think we're we're necessarily looking for money other than to keep building and building and building as fast as we can. [17:21] Yep. I guess last set of questions here before we wrap up. You get going in 2008. Do you remember how you got your first paying customer? Tell that story. [17:28] >> Yeah, look, it's funny, 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. And we [17:49] >> 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. And 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. [18:11] >> 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 [18:28] year was that? [18:30] >> Customer, still looks at gotta be '20 probably [18:34] >> 2011, 2012. [18:36] Okay. So that's something we gotta understand. A big check. I mean, 2008 to 2012, you know, all pre revenue, all about getting data. You're putting your money out going, okay. I hope this bad boy works. [18:45] >> Well, we weren't a 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 [19:04] >> 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 and D and we spent a lot of time figuring out how these business models work. I think it's why it worked [19:22] >> 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. [19:31] So 2012, first customer, it was this publicly traded company. How many customers are now serving today? [19:38] >> I mentioned we only give out the 5% 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. [19:57] So even so when I the best understand you can only share so much data. Can you share when you guys passed a million bucks in terms of revenue what year that was? I assume it was many, many years ago. [20:05] >> Yeah. That was many years ago. I mean, that had to be eight years ago, nine years ago. I'm trying to remember. [20:11] Okay. So that would have been sick 2014, something like that? [20:15] >> Yeah. It was a while ago. [20:17] Okay. And then if I take I mean, look. We can look at, you know, if you're not necessarily a b two b SaaS company. Right? But if we take a 101 customers times average sort of revenue per employee of a $120 k at most b two b SaaS companies, that puts you somewhere around sort of a $12,000,000 run rate. How much time do you think you need to get up above a 100,000,000? [20:34] >> Oh, so, again, we're not disclosing revenue numbers out here, but what I can tell you is that number would be wrong. And remember, that's because you're thinking about it as a SaaS business. We are not a SaaS business. We're a data network business. We scale [20:45] >> up very different way. [20:46] All I'm doing is I'm looking at your headcount. Right? So unless you're burning millions of dollars per month and you're continuing to fund it, which you could be, by the way. Right? You're that's probably your revenue per employee is gonna be around 120 to one eighty. [20:58] You're saying it's not. [20:59] It could be higher. It could be lower. You're not wanting to share. [21:03] >> 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 we grew exponentially. We didn't grow linearly. [21:12] Not talking about SaaS model. I'm not talking SaaS. I'm talking about revenue per employee in general. [21:17] >> It's a different metric the way you'd look at it. It's like saying, look at a revenue like Facebook or TikTok about a revenue per per per individual, that wouldn't work the same model. [21:26] Well, not I'm not It doesn't work same model. I'm I'm not talking about individuals in the in the network. I'm talking about revenue per employee [21:31] >> at least it's point five million. [21:32] Yeah. [21:33] Yeah. Yeah. So you're saying your revenue per employee is more analogous to a Facebook, right, which is in, you know, millions per employee versus a traditional b to b SaaS. [21:42] >> I think that'd probably be a better way to think about it. [21:44] Yeah. Yeah. Yeah. That's fair. That's fair. Alright. Very cool. Let's wrap up here with the famous five. Number one, favorite business book. [21:50] >> Of all time, Crossing the Chasm. [21:52] Number two, is there a CEO you're following or studying? [21:57] >> I think it's always Reed Hastings. [21:59] Number three, what's your favorite online tool for building collective? [22:05] >> Recently, ChatGPT. [22:08] Number four, favorite or sorry. How many hours of sleep are you getting every night? [22:12] >> I always get eight no matter what. [22:14] That is good. Situation, married, single, kids? [22:16] >> Single. [22:18] No. Any kids? [22:19] >> No kids. [22:20] No kiddos. And how old are you? [22:23] >> 52. [22:24] 52. [22:25] Last question. Something you wish you knew when you were 20. [22:30] >> 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 it's gonna be one of the two. So I'll pick young if you're smart. [22:47] Guys, work hard when you're young. He built his first company over nine years, sold it for $425,000,000. It's called LinkShare. Very nice, obviously, business model there. And two years later, went into a new business called collectivei.com. Think of it, you know, 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 a 101 [23:11] folks on the team today. They've, quote, unquote, bootstrapped it, put 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 top. [23:25] >> Thank you for having me here. Really great opportunity to speak with you, and I love your show. [23:29] One more thing before you go. We have a brand new show every Thursday at 1PM central. It's called Shark Tank for SaaS. 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, ARPU, CAC, LTV, you name it, they share it and the buyers try and make a deal live. It is fun to watch every Thursday one [23:53] p. M. Central. Additionally, remember these recorded founder interviews go live. We release them here on YouTube every day at two p. M. Central. To make sure you don't miss any of that, make sure you click the subscribe button below here on YouTube, the big red button and then click the little bell notification to make sure you get notifications when we do go live. I wouldn't want you to miss breaking news in the SaaS world, whether it's [24:15] an acquisition, a big fundraise, a big sale, a big profitability statement or something else. I don't want you to miss it. Additionally, if you want to take this conversation deeper and further, we have by far the largest private Slack community for B2B SaaS founders. You want to get in there. We've probably talked about your tool if you're running a company or your firm if you're investing. You You can go in there and quickly search and see [24:36] what people are saying. Sign up for that at nathanlatka.com/slack. In the meantime, I'm hanging out with you here on YouTube. I'll be in the comments for the next thirty minutes. Feel free to let me know what you thought about this episode. If you enjoyed it, click the thumbs up. We get a lot of haters that are mad at how aggressive I am on these shows, but I do it so that we can all learn. We have [24:56] to counter those people. We got to push them away. Click the thumbs up below to counter them and know that I appreciate your guys'support. Alright, I'll be in the comments. [25:04] See you.