Enodo Revenue & Funding (2023)

hello everybody my guest today is mark rudson he's the co-founder and ceo of enodo an automated underwriting platform for multifamily real estate the company helps users analyze more deals in less time and make better investment decisions backed by data science utilizing machine learning the platform collects cleans and analyzes real-time multi-family rent and availability data from over 2 million properties nationwide mark are you ready to take us to the top i'm ready all right so um interesting tool here help us understand maybe a specific use case of a customer using your tool and then what your revenue model is is it a peer play sas company yeah so uh we are a pure play sas company um so what we do uh if there's a value-add investor who's looking to tell you know if i'm going to do a value add what happens if i add the granite countertops the hardwood floors the roof deck what if i do this to a multi-family property what am i going to be able to get and rent for each of those improvements the simplest use case is evaluated investor can put in their their deal parameters toggle those amenities on and off and actually see what rent lift they'll get before they spend money in those improvements using our machine learning algorithm okay and what would a value investor like this pay on average maybe per month or per year to get access to this technology you've built the top tier is 500 a month and the bottom tier is 100 a month and then we'll get a middle 300. so would you say like a fair average is like 200 something like that i'd say actually more lean toward the 500 okay okay cool historical data that are included there good then we'll go between you know 300 and 500 there and say call it 400. that's helpful to understand let me ask you when a value-add investor does something like this i mean i assume these renovations are maybe like one time i mean what makes them keep paying you when they're not doing a renovation yeah so we actually help people source deals so people are constantly trying to figure out if a deal is going to be a good undervalued play or not and what our platform allows you to do is very quickly load a rent roll into the platform it'll parse it and analyze and see if your rents are at market or if there's upside load your t12 your uh trailing operating expenses it will load it into the platform very quickly and then compare to market benchmarks and tell you if your expenses are above or below market and then ultimately in just a few minutes you've actually got a full underwriting model of the plat of the deal and you can see if it's you know a good deal or not it's that whole adage that you got to look at a hundred properties make offers on 10 and then ultimately close on one we help you do that hundred properties part in about a tenth of the time it would typically take any tool that boasts machine learning or ai generally is only as good as the inputs that the founder has you've been clever enough to put into the system so how clever have you been so we get data directly from the source that's the best data that we can get is you're incentivized when you use the platform to upload your property management from your property management software your data so you can model and analyze your portfolio uh so users do that they upload rent roles in t12s which we get direct from the source we have partnerships with major national lending groups our lenders that uh that feed data in bulk into the platform and then we get it from anything publicly available and there's about 30 different sources we go to nationwide to get listing data to get demographic and economic data demand driver data all this feeds into the platform and helps make a better and more informed model these could be like mls listings that list like the current rent roll on properties things like that oh yeah so we'll use what's publicly available um is harder you got to clean it a lot but the best data we get is straight from the source yeah when did you launch the company what year 2016 was when we announced we were going to do something 2016. i got in front of a op tech audience and i was like we're going to quantify amenity values we're going to predict rents we're going to do all this and like have you done it yet no that was a it was kind of a uh the opposite of a stealth launch i would say and then we slowly built it over the next year and a half and then we actually released for for subscriptions in 2018 so january uh and we've been growing like crazy since then that's that's great so how many customers have they scaled to today we've got like five or six hundred between five and six hundred okay that's a little bit because we had columbia university's whole class sign up and there's 155 there so they're all paying five 400 bucks a month no i wish yeah that would be great we'll give you a nice dis for that class the the user base is a little bit lower than that of like standard users i would say can we just take 100 100 100 so maybe 400 actually paying full price right yeah yeah can i do that math mark can i take 400 times a 400 a month price point you're doing about 160 grand a month right now uh not quite because we got a lot more pilot programs too uh i i wish it was that high um we're closer to a million arr right now okay that's great so would you so let me just repeat that back to you what you would say is your your average price point that you already gave me is accurate at 400 bucks a month however the 400 or 500 customer count is not accurate because they haven't all closed yet it's a it's a little bit skewed because some of them are in pilots where it's like a fixed price and then you get more licenses and some of them are university well one is a university contract that is pretty big at 155 at a steep discount sure that's for my alma mater so i give them a good deal that's that's very nice of you do they give you a deal on on tuition no that's they're slowly come on you left some money on the table there yeah right all right very good so walk me through you're currently currently at a million bucks about in kind of arr you were at nothing about a year ago because you just started selling in january how did you get the first customer tell us that story uh so we uh we had been talking with people that were interested we put a beta list out and people could sign up for beta about a year before we actually launched the product for subscription so we had a good database we had 300 people that had inquired and said they were interested it was easy to go to that list afterward and then you know we we started cold outreach and we had at the same time people uh new people coming in and uh you know some of our first big players uh were just people that had been following it since i made that initial announcement and it was pretty easy because they kind of knew what we were doing than you that's the benefit of a non-stealth launch i guess is that we had already proven ourselves by doing different studies different industry publications i've been in the news all all over the place presented at harvard mit we did a study with the national apartment association on amenity price so you basically became a thought leader in this first and then you slowly built like tech to help you put out reports and then you made the tech basically available for sale yeah smart i like it very good um talk to me about kind of how you've done this right so have you bootstrapped the company or raised no we raised uh 2.2 million uh in two it's it's one round technically but it's um it was over the course of two years so we raised the first we started in like november 2016 and we got like our first deposit of like 25k over the course of the next year we raised the first 1.2 million and it was gradual it was mostly friends and family and then you'd be shocked how easy it is after you actually have a product we were able to raise the second million like in no time at all or those those investors that came in later though obviously they were investing in a company that had less risk because you had sales did they get the same terms though as the early investors uh i wish we would have done it differently uh at times but yes they did yeah the same because it was one round by the way this is very typical no one ever talks about this but it's very typical for this to happen it's essentially called letting the round roll right and you let it roll and you hit your cap did you cap it at 2.2 yeah we capped it yeah and then 20 discount and 5 million value cap on that yeah okay so it's a note yeah that's great what are you at today in terms of team uh we got 11 on the team right now all in chicago yeah we're all in chicago um so we're right west of the river um right by communion station actually that's good mostly developers we got eight developers and the business people are doing what we do that's great you know it turns critical on any sas company right so what's your turn today and how do you keep it low we're a little under five percent and uh at five percent per month uh five yes five percent uh so it's mostly its annual contracts for the most part um on our annuals obviously is it's the first year so we haven't had a ton of churn there um well what's the five percent is that monthly or annual five percent on on the monthly contract okay got it so five percent revenue turn monthly right now yeah and and so the reason they're churning is what um we've got so it's it's you know people didn't use it as much as they thought uh people they like in a few instances we had to leave the company who was like the the champion of it because it's a very new product right so there we tend to get we're not over that that gap we're we're in the first part of uh of building the business right so we got people that are kind of champions of the product and if that champion goes to a different department or leaves the company or something the others don't understand what it is and then they're like oh i see a chart i'm gonna cancel it that actually happened like three times we we had someone like either leave or go to a different department and it turned that way but in other instances they either didn't use it as much as they thought or they just can't like if they're lower market they really can't afford the expense and they did it monthly to buy it out and they never wanted to do you know like a full year they just want to do a few reports on it when you look at your fully weighted cash so the cost to get a new 400 a month customer what are you paying to get these guys um at the end of the day uh our payback period is six months on these guys okay so fairly good that's about 2400 bucks in terms of spend [Music] and where are you spending that typically uh it's so we've got commission we pay to our sales people uh 15 which is a pretty nice commission uh because we built it as a thought leader we don't have a huge advertising cost and we've actually we ramped it up and then we reduced it because we found that it didn't improve a whole lot to spend you know ten grand versus five grand it didn't make a huge difference so we're we're at about a five grand marketing budget spent right now and we track them from the the time they get to our site and all the sales interactions to the time when they actually close uh and all in takes us about six months to pay it off uh fortunately our first round of customers that the people we signed up that were were kind of in our soft launch which was like end of october last year these were investors and and people that were like evangelists of the product all of them renewed so we're in pretty good shape so far as far as those annual renewals uh now we're going to see in january when we started really picking up those annual contracts uh how many of those were new but i think we'll be doing pretty good market how did you mention a part of the value of this is you're getting data from first party source which is essentially your customers which would i you could argue then the first customer got the least value because they weren't getting anyone else's data they were just essentially uploading their own what did that first customer see when they logged on if there was no other data except their own to see oh we use public data we used publicly available data so they had just more was publicly available more was from property websites or listing sites or you know open data portals now as time goes on we're getting more and more of that coming from the users themselves uh so the predictions get better that's the big thing you see is the predictions get better over time so before there was a wider margin of error on amenity predictions so you'd see you know amenity is twenty dollars plus twenty dollars but plus or minus ten dollars right so oh that's you know it's a prediction but it's not as reliable now it's plus or minus three dollars so yeah because you have more customers uploading their data exactly interesting how do you measure how much data you've like they've uploaded is it like a number of properties number of api calls per day i mean what do you measure a number of rules uploaded number of t12s and number of units on the platform so how many units on the platform so uploaded to the platform we've got somewhere around 200k okay and how many rolls um and then rent rolls would get like 300 to 500 a month depending on the month so that's that number what's that that's new new yes yeah because people are doing deals we've got our customers we aim for you know a deal a week to be run through the platform by any user so you know we're trying to to continually get people to come into the platform and run like a t12 a rent roll and you know toggle some things and analyze yeah are you burning capital today yeah yeah how do you think about that i mean are you burning like 10 grand 20 grand how do you make sure you you only burn enough for you doesn't make you turn nervous uh we're we've got kind of a backstop so we've got um tom delaney is one of our investors he's our our ceo and he's got if we ever got to you know a point where we were too low i mean obviously we'd raise but you know we've got a backstop too so we're we don't have like the the the brink of destruction feeling that you typically how aggressive are you being though right now like are you talking burning 20 grand a month 40 grand more or less uh about 50. okay and when did you finish the 2.2 million um we're still finishing it we're not quite oh got it okay got it got it got it but you've raised that okay you've already used some of that though because from the money you captured earlier yeah we're in the process of closing around right now um the 2.2 or a new round a new round one point how much uh we're raising 1.5 priced at 10 million okay 1.5 price and why 1.5 why not more why not less that's how much we need to to achieve profitability and then to i mean we don't need a huge team right so we're not like a company that needs a call center we don't need to keep ramping up sales people the sales happen through the site then itself we need maybe a few more sales people a little bit more development capacity but not you know a ton uh right now and our main objective first is to achieve profitability yeah so you think that's why you raise the 1.5 that's the runway you need to get profitable yeah very good all right we're out of time let's wrap up quickly with the famous five number one what's your favorite business book uh i'd say the the challenger sale is my uh recent favorite uh but the lean startup is my all-time favorite number two is there a ceo you're following or studying right now uh right now um shoot there's uh a lot not not in particular i've been reading a lot of business books lately so i haven't been following anyone in particular i guess this kalanick is kind of interesting right now because the whole thing he's doing with cloud kitchens that that startup that's investing in like stagnant uh retail space i think that's kind of interesting but i wouldn't say i'm following him necessarily got it number three what's your favorite online tool for building the company uh i'd say slack uh incredible and hubspot is more incredible though i'd have to give uh i have to give you number four how many hours of sleep to get every night i i try for six what do you get i have a daughter at home so i probably get five to six okay five and daughter are married or single married and she's she's turning two soon married and one kiddo that's great and how old are you i'm thirty thirty last question what do you wish your 20 year old self knew uh i wish i would have started doing this sort of thing earlier i wish i would have known how easy it is if you well not easy but how fulfilling it is i should say uh if you actually take the leap and start being entrepreneurial sooner i tried to go the whole traditional career route it did not work so well for me uh it just was not fulfilling it was not engaging so i wish i would have done this sooner guys start your company sooner launched uh launched the company back in 2016 16 again enoto inc again helping people understand if you've replaced the granite countertop how much more can you charge in terms of rent per month he's got about uh 220 customers actually more than that caught 400 500 just at different price points but just past a million bucks in terms of run rate uh they're looking to continue to scale currently burning about 50 grand a month 2.2 million raised about to raise another 1.2 million on a 10 million pre-priced round 11 folks on the team again hoping to drive for its profitability now all based in chicago five percent revenue churn per month uh so about 95 net retention spending 2400 bucks to get a new customer so about a six-month payback period again as they look to increase the amount of rent rolls ttis and uh and additional property data uploaded to their platform every single month and day mark thanks for taking us to the top thanks