How Massive DH CEO Gianluca Ruggiero grew Massive DH to $1.2M revenue and 8 customers in 2024.

massive dh.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 bucks 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 even maybe buy the business at 10 million 15 million today but again totally bootstrapped we'll see what happens next hey folks my guest today is Gianluca Ruggiero he is a global Innovation and marketing expert with more than 20 years of working 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 hyper comparative markets the URL if you want to follow along is massive DH that's d as in dog H as in hog.com all right uh Gianluca you ready to take us to the top hi how you doing everybody we are we are all doing well so tell us what are your customers paying you for uh sorry say it again whether what are your customers paying you for what do you do so the um basically we are uh data as a service platform that um provides our customers with a full cycle uh product strategy management so from product Innovation to assortment optimization all the way down to uh category management uh uh and uh everything that basically revolves around product uh our typical customer is a large cpg companies like Procter Gamble nestled that kind of companies espresso Melissa and uh these kinds of folks Olay Etc so are they paying you SAS fees or service fees SAS fees that's a subscription on a yearly basis uh the average price of our services goal is defined by the category uh that we analyze so for example in the case of um uh you know Cosmetics you can assume like for example facial moisturizers in one category facial cleanses is another category and the price goes between one hundred thousand dollars and 150 000 and is that based off number of skus analyzed or number of seats or something else it's um 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 because 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 course the price varies and and yeah in a my to a minor extent also the number of seats uh okay and how many of these customers are paying you today uh we have currently nine uh uh well no eight customers being okay and so can we take a eight times 150 000 bucks a year you're doing about 1.2 million a year right now we are currently at one because we are uh it's funny we started when we started in 2019 we were pricing a bit lower 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 SAS price and then we uh we grew basically and John Luca 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 foreign well one year ago was actually so it was forty thousand it was a bit less actually in that house oh what's going on there YouTube good to see you guys now imagine this you love watching these interviews with SAS Founders but imagine if we took all of the valuation data out from over 2807 interviews I've done manually saves you a lot of time well we've done this we've built the into the beautiful interface inside of founder path check this out I'll show you how you can access this in a second but you log in you connect your stripe account you see your valuation real time you can see what it changed over the past 88 days and even set goals for evaluation this year now the secret valuation 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all right let's jump back into the interview and so how have you driven this growth have you bootstrapped the company or do you raise outside Capital totally bootstrapped oh I love that congrats so how did you drive that growth what's your customer onboarding strategy here um yeah that's uh um I mean across of course a many many uh mistakes along the road but uh what we are doing is basically reaching out to them with cold emails and cold messages not very sophisticated strategy honestly and uh just with our story with our use cases uh and uh and you know we were lucky enough to strike uh from the get-go big customer prior contracts like Procter and Gamble which has been how did you land Pro everyone would love to land Proctor and Gamble as their first customer but but Procter again I was gonna say you're a startup I'm never gonna bet on you I'm not going to pay 150 Grand a year how'd you get that deal done 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 uh basically tasks 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 stuck a chord into what they were looking for which was new signals for uh you know to to find Alpha in product for product innovation and the way we actually got the the contract was that the guy told us an impossible gave us an impossible task he basically asked for uh to analyze a very difficult category out of China they were getting crazy about that they couldn't find uh you know value he was basically kind of saying okay he challenged you and you delivered challenged Us big time we came back with the answer it was uh that was the wow moment and then he said okay so Jean Luca I think the wow here that I think my audience is going to 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 third proprietary data You're Building Tech and getting data know what else has which one is it 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 uh we started developing in 2014 just uh as a as a comment our team is is in Italy and we have more than 100 papers published on AI so it's a serious stuff wow how many folks are full-time today uh three people in the engineering and uh we are like seven people right now uh 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 officers 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 okay this is going to be the office today now the the office I'm I'm here Ryan right now in Connecticut so we serve mostly U.S market because it's the most dynamic and uh responsive but still when it comes to Talent we have a very just to cut to the chase here though you don't necessarily have um a unique data set nobody else can get your IP is really...