How BodyBlock CEO Greg Moore grew to $900K revenue and 15 customers in 2019.

hello everyone my guest today is greg moore he's building a company called bodyblock.ai a consumer body platform for apparel all right greg you're ready to take us to the top yeah let's do it so what does this mean consumer body platform for apparel yeah it's a good question so back in 2012 we realized that nobody had really captured a lot of data on the human body especially on the surface of the human body nor its measurements yet almost everything we buy has to do with our body right we buy clothing that fits our body we sit in seats that are built for our body we lay in beds that are made for our body and nobody's really understood the body and so generally what we did is we laid out a 3d body scanning platform we developed scanners all throughout the world in 50 plus countries and we've scanned millions of human bodies so now we use all that data to help brands design products to better fit the human body and we help consumers get access to the appropriate size product for them with all the brands we work with which side are you making money on uh the b2b side okay so it's free for consumers that's right consumers don't pay us the thing okay and walk me through the onboarding funnel here so first off how many scanners do you have deployed across the world yes we deployed just over 2 000 scanners we deploy between 50 and 75 every single month okay and i mean i imagine these are not cheap what do they cost and do you do those sit on your balance sheet or do you have some relationship where they don't yeah good question um we actually sell them so we sell them into fitness weight loss wellness chiropractic physical therapy they use the scanners to increase membership drive retention increase consumer experience right there's all sorts of tools built around it we on the other hand anonymize the data and then we get to use the data for purposes like body block ai and so um from that perspective they only sit on our balance sheet as long as their inventory and we sell them out i'm into the b2b world there okay what do you charge for those uh anywhere between i think nine and twelve thousand dollars kind of depending on whether they're national or international okay and then what is it i mean do you basically give those out at cost or do you have a margin built on there for yourself what's it cost you to build no it's a it's a handsome margin right so we both profit on the distribution of scanning side of the business as well in the data set of the business that's great i mean can you give me a general sense there are we talking like a grand to build or three grand to build or what uh it's it's sort of in those ranges yeah okay okay i can't go into details where how do you set up that supply chain are we talking like china manufacturing typical process there or what no so we actually do it's not it's like huge batch right i mean we're doing between 50 and 75 units a month um so after running all the cost curves and comparisons we'll fabricate a little bit in china but predominantly uh we manufacture out of san jose california the whole thing even the manufacturing oh interesting are you in one of those like i was down there interviewing a guy that runs a big mattress company that comes with casper and i walked into his warehouse and i'm like it's like this big old hot air warehouse with no ac but he's doing all his manufacturing in there are you the same kind of way no so we're uh i think it's full iso 9003 compliant or something it's like it's a top end shop um and we have a really good really good system with them again i was going to say is this you does this all sit on your balance sheet or you are essentially you're paying a company that does this full time that's right yeah we pay a contract manufacturer to actually build them for us so we own all the research and development all the patents all the ip and then we own a lot of the supply chain and then they actually source it and assemble it for us so once they then we pay for it isn't the billion dollar business here like the data play and if so why would you wouldn't you want to just get these scanners down to as cheap as possible to just get up to billions of bodies scanned why build in a whatever it is a 40 50 60 margin on the hardware yeah i mean that's a good question the reality is is it comes down to funding right and i think as you've noted right you don't necessarily have to have a lot of investment to create a lot of capital um and so the reality is that yes um if funding were omnipresent then that's the play right the play is to reduce the cost down to nothing give them away for free aggregate the data on the back side and create services on that the challenge is that we live in good old silicon valley and there's a social media site every every day that pops up right and there's something that's promising billions of dollars to growth tomorrow and so for us as a company we've always had to be very scrappy we've had to make money from the beginning we've had to drive it close to profitable business in order to drive this thing and now that we have statistically relevant data sets now we fit that more traditional sort of vc infrastructure where if we wanted to raise money we could but right now we run through profits yeah not bootstrap we've raised about six just over six million dollars okay from like angels uh ventures um some big groups out of china actually out of hong kong and then uh quest venture partners projector venture partners a couple of entries here and there okay and so you say close to break even i mean how much are you burning today you're talking like 100 grand a month or something like that no like maybe five okay five out of five yeah we're very very close to profitability and we'll teeter like last month we were profitable a month before we weren't so we're basically hit sustainability on the business side when was last run of ec financing 2017 okay interesting so so most i mean once you're on the vc track you're like on the vc track and you're typically raising every 18 months otherwise it's kind of like a warning sign something's wrong like you couldn't get the valuation you wanted in your next round is that the case uh no i mean we we we knew that developing hardware is a tricky business and so we wanted to get that up and running break that even aggregate the data on the back side and then grow the revenue from the data side um and so and then as that grows valuation continues to grow right and so we don't need money right now and so the beauty that we have is that we can keep growing the business and we can take money at a valuation that we think makes sense for us but until that valuation comes is we just we don't need it when did you launch the company 2012 okay 2012 and then how much did you put into the mvp total total expenses before your first dollar of revenue oh god no idea um a lot of it was like i mean the beauty is we took advantage of like the 3d print revolution right um so a lot of the first systems where we first started making revenue were like literally 3d printed components off of our co-founder's desk so it didn't really cost us much outside of brain power and we put the three co-founders together i had a lot of expertise in computer vision data science or the co-founder of a lot of a lot of experience in full stack engineering and the other one in manufacturing okay and so the three of us together can pretty much create whatever product you want very cheaply what's the team size today i've got 20 24 full time i think and then we have another like 75 people here there um when you look at like who's manufacturing all the logistics and pipelining um temp work that we have here in there of the 24 how many are engineers versus quota carrying sales reps 10 about 10 engineers and how many sales reps uh seven they carry quota yeah do they carry quote on the hardware plus the software uh hardware only right now on software yeah on the software side it's it's pretty burgeoning right it's it's very new it's early um and so what i like to do as a founder is take on a lot of the biz dev stuff as we get it going because i'm going to feed all that information back to the product and then as we get some money back behind it then we start hiring sales reps um because we can repeat a process if i hire sales reps but i can't repeat a process then i'm just having people running the gun and it doesn't really work all that well yeah so a fully stated rails rep sorry a fully weighted sales rep how many how many physical devices are they going to be selling per month what's their quota target uh anywhere between 10 and 17 i think okay annual month month monthly okay interesting and how did you how did you come up with that number so what made sense um i think the biggest number that i could come up with when i when i did sales was about that um i think i hit 17 one month and then i'd sit around 10 um and that's with some other responsibilities so i figured that they should be better than me um so that's kind of how we came up with that number yep so 10 devices at a minimum quota right at 10 grand a pop they're basically having to close 100 grand in new business per month yeah close to that that's right yeah and do you structure i'm sure each salesperson is different so this is kind of sensitive information but generally speaking we're talking like a 20 or 30 percent commission on these sales yeah it's you know it's funny we we like to try new things um and so one of the commission structures that we created is what we call a tiered commission structure right so you know your first x amount of dollars in pays off at some percentage your next um tier up is off a double percentage and then your next hero pays off a triple percentage every month it resets every month um but i mean these guys are great man they hustle they work hard they get it and most of the times they're in that third tier um so they they bring home something so what so just i'm curious how powerful you've made this kind of incentive structure so if i get in that 30 or do i break 30 commissions you'd be close okay very close and the first here is what like five ten percent somewhere around there yep really interesting okay very interesting all right so we've talked a lot about the hardware side of your business is there a software is there a sas component yeah so if you go to uh bodyblock.ai as you mentioned the beginning of this yep actually let me take a step back the first part of the business we talked about was majorly fit 3d right so that's the 3d body scanning for four wellness companies on the other side the data side of the business is bodyblock.ai as you mentioned the very beginning and yeah that business is up and running right now um and it's pretty cool we took all the data that we captured from fit 3d and now we don't we don't really need scans to produce body measurements so for example if you go on rhone.com it's a site that we work with right really great company um you can go through it and if you go to a product you click on find my fit it's gonna pop up a little fit finder widget and then from there we're going to ask you some questions and we'll predict every measurement in your body and then we'll tell you which size clothes to wear but the beauty of that is that we are literally predicting within 97 accuracy of a scan the measurements in your body uh but it's not understand it's really it's really it's question it's a survey that you are then comparing to your sample cohort of scans you've already collected and doing essentially an analysis of what matches yep yeah right yeah that's right so we get where we get our benefit on that is that we regress that against our actual user base right so um instead of coming up with something and sort of guessing in numbers which a lot of companies do in this space we literally go back through and we will ask our fifth ready users that have validated scans to take our prediction quizzes um and so that gives us a lot of insight into what's accuracy and what's not accurate yeah you're saying cause you're still dependent on the me saying how long is your arm and god if i know i'm just gonna probably guess 22 inches right and maybe i'm actually 28 inches i don't know right the beauty of that is we never ask you a measure in your body so what kind of questions do you ask them to run the regression yeah it's height weight age and gender that's it and then from there we show you so we bucket all of our scans and then we segment them out and we show you like a bunch of images of a chest and we say which chest looks like yours and then we show you a bunch of images of a belly which belly looks like you're a bunch of images of legs and thighs and whatever right and so from there those are actual body scans on the platform that are just segmented down to help you focus on the specific area that we're talking about and so from those bits of selections we get a tremendous amount of information right you essentially act as the first part of the eye the intelligence you're cognitively looking at these things looking at the shape of your shoulder you know the muscular tone of your chest your belly whatever that may be the protrusion of your love handles whatever and so from all that stuff that feeds into our engine which then allows us to predict these measurements very accurately so okay so what's this i don't i don't understand what you're selling on a software on a sas platform then yeah so so two things so um two separate products one is called body block recommend right and that's a widget it's basically a sizing widget that we sell to brands so it runs a customer four laps some other big names that are launching right now does it make up the majority of your sas revenue no uh that's a that's a sliver of it um but so from there right they inject that widget onto their site and then we get paid every single time somebody uses it so every time we provide a recommendation we make money um and then they make huge money on that right tell me the main sas one though tell me your main software product yeah the other one is called body block insights and so what happens is that brands they can log into this platform and it allows them to select the bodies or the population that they actually want to design clothing or product for right and so then from there they can manipulate what they call it's a sort of industry jargon but their body their sizing constructs to make sure that when they're producing a size small that that size small is matching the vast majority of that i see the most overlap like a venn diagram you want to get the most area overlap yeah interesting so with all that data that we have they can then go through and increase what's called fit coverage right so like when they're designing a product they know they're designing it that's going to fit a mass majority of the human bodies they actually want to sell to and that to them like you know i don't know take nike for example that's gold 33 and their fit their fit coverage is like eight percent so greg what on average i'm sure you have tons of cohorts and we don't have time to go on all of them though but on average what are these companies going to pay for for that piece of your technology per year yeah it really depends um so we're not an exclusive company we really like to allow people to get in and then sort of grow with us and the more they take part of the ecosystem the better um so an average like contract value is probably going to be anywhere between 50 and probably half a million fifty thousand to half a million dollars a year anything that has to do with fitting product to human body it all comes from this platform and how many people since 2012 have you signed up on that platform uh we just launched that platform in january actually um and we've got i think over 15 brands on it already we're growing by anywhere between five and probably about five brands per month that's great okay so 15 folks signed up brands on that platform all paying north of kind of 50 60 000 a year so that's doing more than 75 grand a month right now at this point yeah we're very happy with that when do you think you'll break a million a month just on the sas block sorry a million in terms of run rate annual run rate yeah we're close um a month yeah we're pretty close i think we'll probably do it next month after that's cool and where were you on this exactly a year ago zero right nothing yeah all this is so the way we did is we did a lot of consulting work right we learned from the consultation work and we built a platform on top of it um the consulting work was all built around our data and like what do we do with it and so this just allows us to create a platform for that and we make passive income that's really a really cool goal there right now it's smart man i listen i love the data play you know you you're you are going to have a much in my opinion look i'm projecting here but a much more valuable sas company than most because of the hardware component here it's just a moat that would be very hard for other people to overcome quickly yeah heavily defensible that's right i think it is i mean it all just depends on how you like use this data right it sounds like you're just i mean you've based on from nothing to a million dollar sas company leveraging the the hardware you built over the past six to eight years and gotten that deployed all over the place so i mean it's interesting um let me ask you another question um do would you ever consider raising something like venture debt non-diluted venture debt to grow the company or or will your next round definitely be like an equity round where you're taking dilution uh it really depends it's a great question um i think that you kind of have to take those as they come and whatever the deal flow states is whatever makes sense for the shareholders and the board is what we'll agree to right yeah you own the majority of the company though right uh yeah me and and our co-founders yeah how many of you are there if you said four three three total yeah okay very cool all right anyone churned on the sass platform since they signed up in january nope okay so no church it's just too early to tell yeah one it's too early um and then two right they're using this to make some multi-billion dollar decisions um so churn would be pretty devastating not only to to them but to their customers well how do they do it before you they didn't i guess um i walked into the largest apparel company in the world and i said tell me a little bit about the body shape of your consumer and they said we have no idea we've never done a study we don't know what it is we just build clothing based on industry standards so they really don't know um but how do you know you don't necessarily know their customers you just have a cohort of like everyone you've scanned across gyms uh isn't that the beauty though of having users right so i've got these people that i've scanned they are users of my platform and i can survey them anytime i want and so for example if i want to know if you shop at kohl's amazon walmart target nordstrom's bloomingdale's whatever i can ask you that question i can add that to your product so the last survey you did when you emailed everyone that's going to scan with you and you said do you shop at x company how many responded now we got over 25 response rates but what does that give me an actual flat number what does that mean is that 250 000 or something like that so is that meaningful that's a meaningful sample size yeah the the statistically relevant sample size that most consumer insights team will use is like 2500 okay so that's what they're using to work with and we're 100x more than that right so it's it's a it's one of those things like it's not only the body shape data but it's also consumer psychographic data and from that perspective we can go off and gain that any time we want and consumers like they want better fitting clothing nobody likes to buy stuff in return it just sucks um so from that perspective and from that that lens they're very happy to share information very good all right greg let's wrap up the famous five here number one what's your favorite business book oh hard thing about hard things number two is there a ceo you're following or studying ah bezos is a good one man he's all sorts of crazy stuff but he's a smart guy number three what's your favorite online tool for building your company oh uh gusto has probably been the most beneficial yep yep if you're managing a team yourself and you don't have like a full-time like hr yeah yeah like filing returns in every state and all this and it would be unbearable without a tool like gusto all right number four how many hours i'll sleep in every night five okay and how old are you 38 38 good and situation married single kids uh married three kids busy guy last question what is your 20 year old self what do you wish you knew when you were 20 uh nothing man life is uh is a gain of wisdom right so you got to come at it and you got to take it one step at a time and 20 i knew what i knew and that was okay guys there you have it bodybox.ai they've deployed over 2000 physical scanners across the world to scan bodies they then use that sample size turn regression analysis for big brands looking to get max basically body fits for you know the next t-shirt they're going to design our next shoe they're going to design they currently launched a sas product around that they have about 15 brands paying north of 50 000 acvs on that just launched six months ago so 75 grand a month already on that product also obviously making money uh on the on selling the hardware at healthy margins they raised six million today burning about five grand a month 24 folks on the team uh zero percent churned too early to talk about that as they look to scale greg thanks for taking us to the top awesome nathan thank you very much