How Hover, Inc CEO A.J. Altman grew Hover, Inc to $9.6M revenue and 10K customers in 2019.

hello everyone my guest today is aj altman he's the founder and ceo of hover a mobile app that is transforming home ownership by creating 3d home models from smartphone photos prior to founding the company he was an engineer at intel corporation and served as an infantry officer in the united states marine corps aj are you ready to take us to the top hi nathan yes all right great thanks for the time you bet all right so tell us about this company hover what's the first off what do you guys do and then what's your revenue model is it a pure play sas company uh yes so not not quite uh what we do you know in the boring way of saying is we generate generate property data um i think that the interesting way of saying it and what's truly unique about it there are two things um one you know in a simple way you pull out a smartphone with our app and you take a few photos of your home or any building object and within about an hour you have a complete structured 3d data set of of that building on your phone or in the cloud so cool technology we use computer vision and deep learning to do that to turn grids of 2d pixels into structured 3d why is that interesting well because effectively what it does is it unlocks the 100 to 200 billion dollar exterior property services business that no one's ever been able to sell online right it effectively allows us to create ways to sell products that go on buildings online for the first time ever you're talking whether it's shingles or typically or vinyl that's right yeah any exterior property service or product so when you think products yes it'd be siding roofing paint windows um gutters shutters um etc etc right um when you think services well the biggest service that goes effectively on a property is is your insurance policy right so similarly if you want to scope the work that goes into applying a policy to a specific home you need a bunch of data about it and that's what we generate so how do we get paid that was your second question we get paid transactionally today we effectively every time we generate that data set that data package for our professional customer someone who's working on a building or selling a service or product to that building they pay us some flat fee of um typically in the vicinity of forty or fifty dollars walk me through who that actual customer is is it the homeowner or home depot trying to sell paint like who is it actually yeah today it's it's not so much the homeowner we do have a small number of diy homeowners that that that segment is growing rapidly but the lion's share of our customer base and nearly all of our paying customers are our contractors they're people who are selling those products on and hence the service of labor onto that home for the homeowner at the kitchen table so you sit down as a homeowner and you're buying a new exterior project and a contractor who uses hover will open up their laptop and show you a 3d model of your home that we generated they'll spin it around they'll work through the design interactively with you on the laptop in front of you and put those new products on your home and show you what it would look like and then quickly get to a quote that's based upon the measurement data that we generate so each time that that that that home that contractor let's say you know a painter right is doing that scan they're paying essentially 40 bucks to you each time that's correct interesting um how do you plan in terms of your own expenses related to team or you know the next dev cycle when these are these are kind of a per scan basis or are they pretty predictable they do grow over time and you can count on them yes they're actually shockingly predictable this is a giant market we've touched a small percentage of it but we not only have customers who when they join us they never leave nearly anyone who joins our product and starts to generate this data on a you know once they've done it two or three times they are not leaving this product but aj sorry what does that mean what does that mean never leave they use it once they pay to use it once so what do you how do you measure never leave they they never return to a tape measure right they never stop using our solution in their sales cycle and so you can look at the predictability of our solution in the context of the exterior the exterior home improvement segment and if there are a couple of hundred thousand contracting companies in america and we start to convert them and using our platform every day at the kitchen table they not only don't leave our platform and go back to a tape measure and doing it by hand but they they continue to grow their usage into their total book of business right so they start by using this as a one-off they try us on one property and then they realize it really helps them with their measurements and then pretty quickly they realize oh wow homeowners actually are more likely to buy from me if they if i use this presentation and use this 3d model in front of them and then before you know it they're using us on every single lead that they run and can you give me a sense today in terms of maybe volume you're working with so you know in a given month maybe last month how many total scans are you processing yeah so we're not public about either the the number of transactions or or the revenue um i can tell you we've grown 4x year over year over year but i we haven't exposed actual uh actual numbers there i can tell you how many um how many roughly how many estimates happen across north america every year for these types of projects it's between 20 and 30 million uh that you said that's per year just north america that's correct okay for exterior projects only okay great uh put this on a timeline for me when'd you launch the company what year we launched the company in march of 2011 but we launched this product it took us almost three and a half years to get this product in the market so we launched this product at the end of 2015 so we've had now three full seasons of the product in the market 16 17 and 18. how did you fund yourself for the first three years when you were developing our first four years uh well actually the first product we sold was we sold to dod department of defense um i don't know if you saw my well you did you mentioned it earlier so i i had a brief hiatus from being a software guy um in the marine corps as an infantry officer and uh when i returned from that experience back to the bay here um told everyone i knew i was curious to join a small team or join someone trying to build a new product and be a part of that and met a couple of engineers that introduced me to photogram tree or i guess what you call state of the art 3d reconstruction at the time and um that was the first space that was evident to me you know it was evident to me that this would be a very powerful solution for folks trying to get a sense of a place remotely um before they're about to you know to enter a dangerous situation so we bootstrapped the company off of revenues through that first product as well as of course um and that was just to be clear it was a dod control event it was a number of dod contracts um yes deals we did um selling software to help help uh the us government um in in in tough places just to be to try and really make this ring home for my audience this might be obviously it's very dangerous to go up to the zombie line compound but if they had images of it it makes it easier to recreate what that might look like for seal training or things like that certainly uh you know what we generate today is a scale accurate digital version of that physical building in the real world so you can imagine how that's useful for contractors but of course it's it's useful for people dealing with buildings and other scenarios as well sure yeah so you've raised obviously additional capital since then what's total capital into the company today uh again we haven't just lost the total amount raised um we we closed our series b last december um you can see that publicly it's a 25 million dollar round led by gv yeah uh what do you mean you don't don't disclose that i mean most of you have to file the sec publicly it says you raise about 42 million dollars is that accurate uh it's it's not too far off but it's not accurate okay what um how would you be able to raise where you don't have to do things to file with the sec and make that public yeah i mean look you can look online and see what uh various third parties will say we we've raised but yeah i can just tell you you know you can see that last round was a series b of 25 million yeah no no the re look the reason i'm asking you i mean these are these are not third parties these are government forms that you file i'm just if you've if you found a way to be able to raise capital without having to disclose it via the government forms that's valuable for my audience so is there something you're doing that allows you to bring additional capital without reporting it certainly not okay got it you want to make sure there wasn't something so why would that number not be accurate if we're just adding up the government forms i i i guess i'd have to look at the forms that you're adding up but um what's the numbers so i understood i i guess i can't speak to what numbers what what data you're looking at specifically i know we we certainly file the way we the way the way is appropriate um but i can just say the number isn't 42. um i i don't know where the discrepancy is coming from because i can't i don't i haven't seen i guess what you're looking at but fair enough no problem let's move on um talk to me more about how you've scaled the team so obviously you got paired up with these three engineers now were you obviously your ceo today were you brought in really as a co-founder as you guys pivoted away from just dod contracts uh no so i i was you know part of the founding of hover this the engineers i met was prior to hover you know they um one of those engineers along with myself were the first two employees as we founded hover okay about a year after i met them and what's the team look like today aj how many folks so yeah yeah so the team we just crossed 115 employees uh we went from 50 to 110 in the last 12 months so we're growing rapidly uh but yes um you know the number was the number was in the 20s the year before that so we've doubled and doubled and we're looking at about another doubling again this year yeah well look and and by the way team growth is great but i always hesitate to let people brag about team growth because really that just means more expenses right so help me understand how you're making what kinds of hires are you making to make sure it correlates back to revenue growth yeah certainly um bragging about being able to spend money a lot of people can do that right exactly yeah yeah talk to me about your hiring strategy yeah so well look it as you know it's tough um we're competing against uh frankly the five or six companies vying for world domination in the areas of deep learning and computer vision and those companies all have thankfully have a different story to tell than we do we we believe we have a center of excellence around those two disciplines particularly in 3d reconstruction that is is as good as there is on the planet we think we're we know we're doing things here that others aren't doing um and so we have that story to tell about hey come here and and and take research and and turn it into to code that ships to as you said make money literally make money in the core product uh but also um you know when you're competing against a google google has a lot of things that we can't bring to the table but we have one thing they can't which is we're not google and so it takes a unique type of person but we're looking for people who not only want to work on problems that have never been solved before that turn into products that get shipped and drive revenue around the core product but um for a company that hasn't already been there that that isn't the company and and and be and want to be a part of of like creating the the next company that does something special in this realm so that's sort of our our strength in in those areas deep learning and computer vision but as you can imagine again like the the volume that we're starting to hit of course all of those platform and infrastructure challenges that come from scaling come into play here with you know front end full stack back-end development um the data set that we're building of course is um is large and processing and as compared to most products that are moving toward consumer and the kind of consumer scale we're touching the amount of processing that happens transactionally for us is is you know quite quite intensive so a lot of cool problems here from a technical perspective uh it's never been our challenge we've been under the radar for the last two years in part by intention uh but you know of course at this level of scale we we need to start to tell a little more of our story and um and we find engineers get really excited about it yeah no it makes i think it makes sense why they'd get excited about it can you give me a sense you said most your customers are contractors can you give me kind of order of magnitude how many kinds of contractors you're working with today how many how many kinds of contractors yeah some order of magnitudes are we talking hundreds of contractors thousands tens of thousands and millions uh yeah you're talking about um again hundreds of thousands of contracting companies in the country and we're dealing with tens of thousands of them today okay so you still so you would put i mean you can you really back into your market share at this point what would you put your market share at right now i'm sorry no problem you know there's a definite amount of contractors in say north america you also know how many are working with you what would you what do you put your market share at today oh a single digit percentage okay so plenty you have to say that right it means plenty of room for growth absolutely when you were when you were negotiating the last round did you sorry when you were negotiating the last round and uh were you obviously valuations on sas companies are higher because their revenue is more predictable uh i could see investors pushing back and going hey but this isn't really a this this is less predictable it's transaction based how did you kind of fight that in any kind of valuation conversations yeah well the the beauty is the data shows it right the beauty shows that it's quite predictable that uh that it is um recurring uh you know i i i haven't seen uber's data specifically but i could imagine in a similar corollary way they're able to show at scale that customers join them and there's a thing called negative churn that's happening that is uh is becomes relatively predictable within a band and we see the same thing with thousands of companies then tens of thousands of companies with um many employees per company that uh join us and then just increase their usage over time which we can model out and is this uh the reason i'm asking is because i'm trying to get sense if you're selling directly to the individual small business paint contractor in some suburb of you know ohio or if you're selling to a massive amount kind of one-to-many approach where you'd be leveraging an inside sales team selling multi-seat kind of plans which one is it more where's most your growth coming from yes we yes i'm sorry you're cutting out so i hope i'm not but i'll just continue uh so the answer is both the answer is we have a very long tail of uh small smbs who have um maybe a couple of employees who do uh 10 or 20 roofs a year right they replace 10 or 20 roofs on buildings a year um and there's a very long tail of those customers who find us purely organically and our self-service and find our product and download our app put their credit card on and and start using our product without us ever touching them but then of course there there is a subset of very large contracting corporations in the country who maybe have a few hundred sales people and they're multi-regional they have uh they have four or five offices across a couple of metros and they might do a couple of hundred million dollars a year in exterior projects and in those cases of course those opportunities are large enough that we have a direct sales model and um we engage those larger customers to help educate and train their workforce and help them understand the value of what we do what is a leading indicator for you guys when you're looking at your cohort data that a customer is potentially at risk for shrinking or using you less everyone has some kind of shrinkage i'm curious how you identify that is it just number of scans per month yes um the the amount of quote unquote like shrinkage of you know a customer that becomes from our view active right they're doing they're doing one to three hovers per month is nearly zero it's very small for us the the true indicator is just um a a um when a customer much more common in that one those first three hovers in their life they drop off right because of a lack of understanding of saying what our product can do for them or maybe they had a bad onboarding experience you know we're continually removing friction from that process or maybe they uh have confusion about the data that we need from them to collect to uh to generate our output and so that onboarding funnel is a challenge because unlike say instagram or any other sort of easy to download experience where one creates an account is off to the races in our case step one is excuse me step two is after you've downloaded and created an account is put your shoes on and go outside and take some photos of your house which as you can imagine is a big point friction frequently that's not possible frequently someone thinks of us at work and they're not able to go outside or they're on their couch and they don't want to get up and go outside and so that portion of our funnel has quite a pinch on it um thankfully again the data shows that there is an extreme pain point because those folks usually do come back very good last few questions here aj before we wrap up um you know there it's a nice point to be in where your annual revenues are greater than what you've raised it gives any entrepreneur significant leverage there do you have 50 million insights here in 2019 or do you think you need another year to grow into that it's possible yeah like comfortable possible or stretch uncomfortable goal possible uh honestly at 4x year over year over year it becomes very hard to even answer your question um and that's the truth like uh i won't be surprised if we beat that number but i frankly won't be surprised if we're sure on it but yes certainly you're in the right order of magnitude in terms of growth i know you're trying to pin that down but you're certainly you're in it's a viable number yeah no it's good it's and thanks by the way for answering the question uh forexing every year eventually becomes not possible when you get to a certain size you're quickly i think approaching that size right i mean we can kind of back into a minimum you won't like me doing this but i'm going to do it for my audience right if if you've got you so you know you know the tens of thousands of customers and you said your long tail are ones doing call it 20 roofs a year right and you're doing 40 bucks to scan so say two scans two roofs a month right at 40 bucks a scan that's 80 bucks a month there at least 10 000. that puts you at around 800 grand a month minimum i assume you're way bigger than this minimum at that point right so if you're gonna that's 12 million bucks a year if you're gonna forex that year over here that puts you obviously in the range where you start you know getting close to that 50 million dollar mark it's a it's a it's a great boston consulting group exercise yes why do you call it a boston consulting group exercise these are minimums you gave me no no i mean uh just because it's a traditional way of of yeah white boarding these things yeah i i get it your your logic makes sense yeah very good and then last question on hiring oh you said you've gone from 50 to 115 people are most these people kind of inside sales reps going after larger accounts are they more engineers working on additional things to patent and productize yeah the largest group is uh is r d yeah very good all right let's wrap up with the famous five quick answers here number one what's your favorite business book oh geez uh i um i don't read business books much um favorite book probably good to great um john uh just i guess because the book is about how teams win you know team always wins uh and and i guess that's the only book i can think of that's like a quote-unquote business book that really stuck with me number two aj is there a ceo you're following or studying um well elon musk is in the news a lot um i i don't wouldn't say i follow him but i certainly appreciate the fact that uh he's a very purpose-driven guy obviously i appreciate that number three what billing tool are you using i'm sorry what what am i using what billing tool do you guys use to process all these payments uh stripe oh you're all on stripe okay well that's great number four how many hours of sleep to get every night uh six to eight okay not bad and what's your situation married single kiddos uh single no kids that's great total total free time to go on in the business and how old are you [Music] uh 41 today for oh today's your birthday yes that's great happy birthday all right last question what do you wish your 20 year old self knew uh i i guess i wish he'd known he should have trusted himself a little more guys trust yourself more again founded hover after serving in the military now serving tens of thousands of contractors they simply take pictures of houses or things they're doing repairs or painting or roofing on and they using you know really incredible technology they put together create a 3d model which unlocks all kinds of value they charge anywhere between 40 and kind of 60 dollars per scan have a big long tail but also big corporate accounts as well 115 people on the team 42 million dollars raised obviously burning capital to drive growth hoping to stay at you know three or four x year over year growth and you know wouldn't be surprised if he hits 50 million bucks this year in revenue we'll see what happens aj thanks for taking us to the top thank you appreciate the time