Massive DH Revenue (2024)

[00:00] Massivedh.com. Big consumer brands pay him for data. It's data as a service. He was doing $40,000 a month a year ago, now doing $83,000 a month. Just broke a million dollar run rate, which is great. But what I love is he's done this bootstrapped with a team of seven. So pretty high revenue per employee. You know, he maybe buy the business at 10,000,000, 15,000,000 today. But, again, totally bootstrapped. We'll see what happens next. Hey, folks. My [00:21] guest today is Gianluca Ruggiero. He is a global innovation and marketing expert with more than twenty years of working in cons in consulting for Fortune 500 companies across five continents. After five years of working on proprietary AI technology, he launched Massive in 2019 to help companies launch successful products in today's hypercompetitive markets. The URL, if you wanna follow along, is massivedh. That's d as in dog, h as in hog, .com. Alright. Gianluca, you ready to take us to the top? [00:47] >> Hi. How are doing, everybody? [00:49] We are we are all doing well. So tell us, what are your customers paying you for? [00:55] >> Sorry. Say it again? What are [00:57] What are your customers paying you for? What do you do? [01:00] >> So the, basically we are a data as a service platform that, provides our customers with a full cycle, product strategy management. So from product innovation to assortment optimization, all the way down to category management and everything that basically revolves around product. Our typical customer customer is is a large CPG companies like Procter and Gamble, Nestle, that kind of companies. [01:34] >> And Espresso, Melissa and Doug, the these kinds of folks. Olay, etcetera. [01:38] So are they paying you SaaS fees or service fees? [01:42] >> SaaS fees. Okay. Subscription on a yearly basis, the average price of our services goal is defined by the category, that we analyze. So for example, in the case of, you know, cosmetics, you can assume, like, for example, facial moisturizers in one category, facial cleansers is another category, and the price goes between $100,000 and $150,000. [02:07] And is that based off number of SKUs analyzed or number of seats or something else? [02:12] >> It's, actually not very much based on it's based on how many retailers, for example, we have to analyze for customers, depending to your point of, yeah, a bit about the extensions of the category in terms of SKU that needs to be monitored Cause we take a census of the categories that we analyze. So we in our database, there is always every single SKU is included. But depending on how many SKUs the customer wants to monitor, of [02:39] >> course, the price varies. Yeah, in a to a minor extent, also the number of seats. [02:45] Okay. And how many of these customers are paying you today? [02:50] >> We have currently nine well, no. Eight customers paying. [02:55] Okay. And so can we take eight times a $150,000 a year? You're doing about 1,200,000 a year right now? [03:01] >> We are currently at one because we are it's funny. We started when we started in 2019, we were pricing actually much lower. As we grew, we extended the pricing because we we noticed that the problem that we were solving was much bigger than the price we had. So we started at a typical more normal SaaS price and then we we grew basically. [03:26] And Gianluca, if you're doing $83,000 a month today or a million dollar run rate, what were you doing exactly one year ago? Do you remember? [03:32] >> Well, one year ago was actually half. So it was 40,000. It's a bit less actually than half. [03:41] 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 [04:04] your Stripe account, you see your valuation real time, you can see what it 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 [04:28] gonna 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 [04:50] is 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 [05:16] you're 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, [05:38] but 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 [06:04] into the interview. And so how have you driven this growth? Have you bootstrapped the company, or do you raise outside capital? [06:10] >> Totally bootstrapped. [06:11] Oh, I love that. Congrats. So how did you drive that growth? What's your customer onboarding strategy here? [06:17] >> Yeah. That's [06:20] >> I mean, across, of course, many, many mistakes along the road. But what we are doing is basically reaching out to them with cold emails and cold messages. Not very sophisticated strategy, honestly, and just with our story, with our use cases. And and, you know, we were lucky enough to strike from the get go big customer pilot contracts like Procter and Gamble, which has been [06:50] a How did you land Procter Everyone would love to land Procter and Gamble as their first customer. [06:53] >> But but Procter and Gamble, I was gonna say you're a startup. [06:56] I'm never gonna bet on you. I'm not gonna pay you a $150,000 a year. How'd you get that deal done? [07:00] >> Yeah. So actually, these large companies for since a few years ago, since actually five years ago, they have people in the company who are basically tasked with finding startups which can up their game. And we were lucky we actually reached out with a very basic and very actually bad cold email, I must say, which was not very sophisticated. But somehow it struck a chord into what they were looking for, which was new signals for, you know, [07:33] >> to find alpha in product for product innovation. [07:38] >> And the way we actually got the contract was that the guy told us an impossible gave us an impossible task. He basically asked for a tool analyze a very difficult category out of China. They were getting crazy about that. They couldn't find, you know, value. He was basically kind of saying, okay, you [07:59] He claimed challenged you and you delivered. [08:02] >> Challenged us big time. We came back with the answer. It was, that was the wow moment. And then he said, okay. So that [08:09] Gianluca, I think the wow here that I think my audience is gonna be curious about is you mentioned your data as a service. Now data as a service, you're only as strong as the data you're getting. And there's two kinds of data that you're buying it from someone else or proprietary data, you're building tech and getting data no one else has. Which one is it? [08:22] >> We have proprietary data, which are basically a transformation of public data. What we do is we take e commerce data, like everything that you find on e commerce retailer that is public. And we have an artificial intelligence, a true artificial intelligence that we developed. We started developing in 2014. Just as a as a comment, our team is is in Italy, we have more than 100 papers published on AI. So it's serious stuff. [08:52] Wow. How how many folks are full time today? [08:55] >> Three people in the engineering, and, we are, like, seven people right now, but we are very much scattered. We almost we have two offices, but basically, they're empty because we have our CFO is out of Paris. Our SDR is in Chicago, the chief revenue officer is in Germany. It's just, you know, the way we built. I am very happy with the team that I built and that and a lot of talent, but we we didn't decide, [09:28] >> okay, this is going to be the office today. Now the office, I'm here right right now in Connecticut. So we serve mostly US market because it's the most dynamic and responsive. But still when it comes to talent, we have a very diverse [09:45] So Gianluca, just to cut to the chase here, though, you you don't necessarily have a unique data set nobody else can get. Your IP is really how you process public data to organize it and then use it to do analysis. [09:56] >> Correct. Yeah. [09:57] Okay. Yeah. So your IP is a it's process IP. It's not some secret data source only you have access to. Correct. [10:03] >> Yeah. It's process IP. Very good. [10:05] And why has no one else thought about running the same process? [10:08] >> Well, I think it's because, it's very difficult to put together, competence in, marketing marketing strategy and AI for transformation. And, in during my career, I was lucky enough to put together these two things. One thing that I noticed from typical Silicon Valley data as a service company is that they don't know very well the marketing the market they are targeting to. So they don't what happens in companies, what they're really looking for. And there is always [10:40] >> this misunderstanding between what is a data point and an insight, which are two totally different things. So they tend to provide data points instead of insights. The transformative power of our technology is to transform these data points into actionable insights. [10:56] Are you ex CPG though? I mean, are you I mean, someone to trust for P and G to trust you to take data and put it in a sentence to make it insights and to drive strategy, don't you have to have experience in like the moisturizer industry if you're giving P and G, you know, feedback on how to sell more moisturizer? [11:13] >> Well, this is interesting. We actually, when we get the information from our AI, so the AI that we have does not require training. It's designed for that purpose because otherwise it wouldn't be But it's interesting that we gather information from the first data that we receive from AI that gives us more information than usually the customer has. And I know it sounds arrogant, but when we come into a meeting with customers because, yes, we do meetings [11:45] >> with customers. Although it's SaaS, customer success is a big part, especially with a platform that is very big like ours. So we do training. But when we come into the meeting, we usually know almost, I would say, more than the customer because you see markets today, and I know it's your experience as well, are flooded with new products coming from small brands and things like that. And big companies have lost contact with reality because they don't [12:14] >> have the data. So we come in with a fresher view. We understand straight from the voice of the customer what's going on in that market, what are the real trends. And also we can pinpoint what are the new players that they never heard about before. I see. [12:30] So you're you're when you say you're pulling data, you're going to like a big ecommerce thing like Walmart, for example, and you are pulling a bunch of metadata and you're using this kind of stuff to determine how many things are being sold and where and at what price point and margins and things like that. [12:44] >> Exactly. Yep. [12:46] Interesting. Okay. And are all your customers brands or the hedge funds? I mean, is valuable data for hedge funds. [12:52] >> Well, yeah, hedge funds, so we had experience with both hedge funds and private equity. I think that for a go to market strategy, we are more viable or let's put it this way, private equity is more viable for us because for example, we do play a role in the M and A strategy. We had a private equity fund for which we did a pilot, which is the fund that is behind the Philadelphia seventy sixers and they [13:25] >> were looking to purchase new live events like stadiums, arenas, things like that, and they used our data to assess which was the best [13:35] But Gianluca, sorry, because we're short on time. They're not your current customer. That's not your focus today. [13:40] >> It's not. But we are now expanding. For example, now one of our customers is Changi Airport, which is the largest airport in the world out of Singapore because we can actually so I'm messing up. Actually that came, we are opening to service them and that came out of the experience with the private equity hedge funds. Back to your question, not really good target because they're used to buy alternative data by the kilo. So quantity versus quality, [14:12] >> we are very qualitative. So we are not exactly a target for them. [14:17] Understood. Well, this is a heck of a thing you're building. I love that you're just three people with your revenue, the revenue per employee is through roof and I always love high revenue per employee. Now plan to stay bootstrapped or any plans to raise capital? [14:28] >> We that's a very we don't know. Actually, we think with this at the time being, we can actually do without funding. Funding would be fine if we can because we wanna grow and we wanna hire [14:43] What would you value the business at today? Sorry? What would you value the business at today? Valuation. [14:49] >> I mean, if I go by a 10 factor, I would say, of course, $10,000,000 or $15,000,000. [14:57] So somewhat offered you here listening. There's there's investors that listen all the time. If they offered you a $2,000,000 seed round on a 10,000,000 post money valuation, so they're buying 20% of the business, would you accept? [15:07] >> I don't know, actually. [15:10] Good answer. Leave yourself some negotiation room. Alright. On that note though, Gianluca, let's wrap up with the famous five. Number one, what's your favorite business book? [15:21] >> I know the the title in Italian. It's a it's a book from [15:28] >> oh my god. I don't remember. Anyway, let's put it this way. [15:31] We'll skip it. Number two, is there a CEO you're following or studying? [15:36] >> No. My former my first CEO who's not working anymore back in Unilever, Umberto Ruggiero, he was a total genius, and I still looking for something as a genius as he was. [15:49] Number three, what's your favorite online tool for building a business? [15:57] >> Well, we currently use [16:00] >> Pipedrive, but I am looking I'm exploring a lot, so I don't have an answer, but I'm very excited about many things that are coming up with AI. [16:09] Number four, how many hours of sleep do you get every night? [16:13] >> Yeah. Eight eight hours, seven hours. [16:15] And what's your situation? Married, single, kids? [16:19] >> Married with two kids. We just did an twenty years of marriage. [16:25] Wow. Congratulations. And how old are you? [16:28] >> I am 53. [16:29] >> 53. [16:30] Last question. Something you wish you knew when you were 20. [16:35] >> Yoga. [16:36] Yeah. There you guys have it, guys. Massivedh.com. Big consumer brands pay him for data. It's data as a service. He was doing $40,000 a month a year ago, now doing $83,000 a month. Just broke a million dollar run rate, which is great. But what I love is he's done this bootstrapped with a team of seven. So pretty high revenue per employee. Know, You he maybe buy the business at 10,000,000, 15,000,000 today. But again, totally bootstrapped. [16:58] We'll see what happens next. Gianluca, thank you for taking us to the top. [17:01] >> Thank you. Bye. [17:03] 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 1PM [17:28] Central. Additionally, remember these recorded founder interviews go live. We release them here on YouTube every day at 2PM 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 an acquisition, a big [17:50] fundraise, a big sale, a big profitability statement or 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 can go in there and quickly search and see what people are saying. Sign up [18:12] for that @nathanlatka.comslashslack. 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. And 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 to counter those people. We got [18:32] 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. See you.