How Dar.Win CEO Frank Mcdermott grew to $432K revenue and 36 customers in 2018.

hello everybody my guest today is frank mcdermott he is an entrepreneur and technologist launched hundreds of sites 50 plus apps tens of digital products launched nine businesses four for himself and delivered a line of high-end beverages to the market and consulted in the finance and tech industries a lot of experiences now building a company called darwin that's dar.win frank are you ready to take us to the top i am how the hell do you decide what to focus on yeah uh you know it's been a very interesting career and i've had a lot of exciting opportunities the kind of threat i found is just being able to bring products to market in different industries different technologies and we've gotten really good at that so when we decided to start darwin we really kind of had a core competency in e-commerce we had core competency and technology and cloud technologies and we wanted to try something really new which was bringing machine learning into a production environment uh and so that's kind of where we decided to uh start to ideate on what could we do with that so tell us what the company does sure so darwin is a suite of products and services that uh essentially provide personalization for e-commerce so you install darwin on your store and we instantly start tracking collecting information about the people who visit your site the things that they look at the things that they click on the things that they buy and put that all into our machine learning models to start to segment that audience and then allow you to start to make product recommendations and predictions and what they're going to want to be interested in what they're going to want to buy we take that information and allow the people to segment into doing e-marketing social marketing and being able to drive those specific segments to specific suites of products okay and name some of the data inputs i mean so let's let's is like h m a customer or someone like an h m a big retailer with an e-commerce site it would be someone like a big e-commerce site uh the way garland works is that you know we can scale and have as long as you have a couple of products and a single visitor on your site we can make a prediction but really the way machine learning works is the more uh information you have the more training data you have the better your predictions are going to get and what darwin does is actually retrain itself with new testing data every week to kind of accommodate new people that are coming to your store and uh different types of visitors that are going to be uh you know coming over a period of your season or your year whatever you're doing that's what i ask actually right so like when you talk about a prediction like give me a prediction that darwin made that a company listened to made changes and saw more revenue because of it well it's really at the consumer level so say the analogy that we use say you're rei for example you might have a customer that's a hiker you might have a customer that's a climber if a person starts looking at hiking stuff there's a propensity they're going to want to see more hiking gear and their recommendations and where they see different products and where you're going to be able to advertise different types of products that are associated with both the one you're looking at and ones that they viewed over time and then you take that to the next level and say maybe that sometime time there's another similar type of visitor in the future we can catch that propensity earlier and start to make more refined predictions now if where darwin really excels is that that person is both a hiker and a climber over time there's going to be a hybrid of products that we're going to be able to make recommendations on it's not the static linear model of making a recommendation based upon category or type yeah and then are you is your business model a pure play sas business uh it's a little bit right now it's both a combination of software and dedicated service i think we have a core competency in e-commerce and a lot of our customers as they experience and try to implement machine learning um you know we really need to kind of get hands-on a little bit um to both understand their business and how it works and how their data works but then also how we can best implement darwin within their organization so if you i mean if you look at revenue over the past 12 months and as a big pie what percentage of that was pure sas versus kind of you consulting and helping out professional services as far as revenue goes right now it's all sas based oh it is all sas yeah so we're providing essentially we're kind of in our our what i'll call our secondary beta alpha or kind of more like production at the same time like we still need a lot of uh road map to kind of grow so uh and as far as this data what types of customers are getting and what their interests are how their customers behave this all works with data so we really have to be open about who we're working with and the types of information that we're getting from them once we start to get to a point where we can really um dial that in and and be able to implement different services more quickly um that's where i think we're going to really start to kind of ramp things up so right now we're working you know pretty much for free for all of our customers what the people that are paying on average what are they paying per month or per year to get access to this tech sure on the low end uh you know a base price on shopify as an introductory price is 29.95 a month but we have customers paying in thousands really depending upon the types of volume that we're getting and the types of predictions that we need would you say that's more of a fair average like a thousand bucks a month something like that absolutely and really when we come to actually getting high performance out of this system and you're gonna be in tens or you know hundreds of thousands of dollars a month uh with the hopes that you know you don't have people at that scale yet do you hundreds of thousands a month no yeah yeah but that's the goal obviously absolutely yeah that's great when did you launch the company what year uh we started we wrote our first line of code in june of 2016 and uh we went uh in beta with our first customer in july of 2017. we ran them six-month beta there and then we launched in the shopify app store in november or to be september of 2017 uh and we now have an sdk where we're watching uh through other different e-commerce platforms uh as of november of this year and how many customers have you scaled to uh we're in the hundreds now okay all kind of free work or most of those are paid that's a combination okay so if we just look at people that have moved from like free kind of pilot you like hustling to actually paying for the tech plus you're helping them i mean how many are paying a couple dozen couple dozen yeah okay that's great how have you so walk me through kind of how you funded this right so did you decide to bootstrap the company or have you raised capital uh no we bootstrap it so i run a software development company and we essentially build software products for people and we've been doing that for 10 years called caravan interactive through that we have a propensity and kind of core competency and bringing software products to market and we've managed hundreds of websites hundreds of applications and we built them for startups for big brands et cetera uh time to get in the game uh the analogy i've always used is we sold shovels to miners but now we decided to get byron shovel what's the team size look like today solely dedicated to darwin uh we have four people slowly dedicated okay that's great so four people and they're all based in new york uh yes they're not here in brooklyn there's two in poughkeepsie and one in manhattan that's great and are you i imagine it's probably too early i mean you're not looking at things like cac and churn and things like that yet right i mean we have a different an understanding of what that is and we are now in the process of trying to investigate why that is uh you know on the shopify platform you can install an app and uninstall an app in under two minutes so there's no like good information awarding there but whereas in our other customers in our existing um other e-commerce platforms we have a good uh really long age so we've had the customers now for almost two years um and so it's hard to tell on darwin or something else on darwin i thought you said on darwin the first really paid people was just about a year ago sorry yeah june 2017 you know it's a year and a half i guess okay god i got it got it um no no that's helpful i just want to say like you're you're basically in the stages now where you're really you're still tinkering you're figuring some stuff out you're not like actively trying to optimize for a cac payback period or something like that correct yeah and now in terms of scale you mentioned kind of thousand bucks a month is a good kind of average and a couple dozen maybe caught 30 sixes i mean is it fair to say you're kind of in that range of revenue 30ish grand a month yeah that's good and zero a year ago right correct and what do you hope to scale to by the end of next year you know uh it's a little tough to tell um our sales cycle we're still kind of figuring out sometimes it's six months sometimes it's going to be you know quite a bit longer so i feel like what we're really trying to do now is now the customers that we want to get and we have the capacity to kind of just go go fish what of the team of fours there's one of them like solely dedicated to sales or are they all kind of developers that's good well then you're the one that asked this question you've got hundreds of people using it a couple dozen paying what's your what's the number one growth channel i mean how are you finding the customers to sell to sure so uh it's been varied uh we've done a lot of social media outreach to being able to reach into people who are trying to get into e-commerce for the first time or have an existing kind of client base uh and they're trying out shopify shopify has been kind of an area where we spent a little bit of time um in our ability to not only get normalized data out of it pretty quickly and get our installation times down but also give us access to a large base of customers do a variety of different marketing campaigns with them and essentially right now you know through their shopify partner program shopify experts we're reaching out to all of them uh through caravan as well we've had an enormous network of agencies who build e-commerce platforms for other people so we're starting to do a referral business there and a referral model and that's where we also we're really motivated to kind of bring up our pricing and uh and get that dialed in a bit more and then from there being able to kind of go and go direct to a consumer or to customers uh themselves yep sounds good man let's uh let's wrap up here frank with the famous five number one what's your favorite business book uh doing deals it was the first one on how to how to create businesses that's great actually hey related to doing deals so are you looking at raising any capital fuel growth or no uh yeah you know the belief i've always had is is the money is great to have uh when they're asking you for it um it's not something that we're in a position where we have a lot to offer a veteran capitalist say right now um and we know enough about software to run this and definitely do you know where you would spend money though to drive customer growth or no yes and no so i think we're still figuring out that piece of the puzzle i mean the product itself is good though we have a lovely road map of things we want to do for the next 100 years when it comes to marketing machine learning to consumers that's a very ambiguous thing our biggest challenge at this point is no one knows how machine learning works or even if it does work or if it works for this situation so there's a lot of experiment that we need to do and a lot of uh investment up fronts to be able to kind of uh normally get them to realize that it is an actual benefit um and also you know implement it in order to understand how it can benefit them got it would you ever consider venture debt uh you know i as an entrepreneur i like to think consider a deal as a deal uh you know sure yeah interesting all right number two here uh is there a ceo you're following are studying right now um you know i definitely have studied a lot of them over the years uh you know i read the wall street journal every day there's always mention of one or two of them in there so that's sometimes a good reference sometimes it's also referenced on what not to do why did you why do you pick the wall street journal as kind of your morning go to paper i've been reading it since i've been was 13 years old so it's just part of my routine now that's amazing and you just you feel like it just helps to get ahead it's it's the place where i've learned the most about business besides doing it myself you see a lot of deals you see a lot of mistakes you see a lot of things over time um and then not that they're reporting is necessarily great or unbiased it definitely is not to get too political but uh the mechanics of business are well represented yeah you spend most time in the business and finance section huh sorry i said you spend most your time in the business and finance section huh yeah definitely and i love all of it um you know i market stocks uh bonds insurance health care mmo and that's great number three what billing tool do you use uh we use quickbooks okay number four how many hours of sleep to get every night uh 46 okay and what's your situation married single kids single no wife no kids no mortgage that's great i love that and how old are you i'm 40 40. last question what do you wish your 20 year old self knew uh just keep trucking keep trucking guys there you have it he's a guy that has been selling again the pickaxes to the gold miners they bought one of their own pickaxes now building darwin helping e-commerce brands get smarter increase average checkout price you know increase lifetime value of checkouts you know where where should product one go if it's a hiker looking on an rei site they've scaled to about 36 customers paying a grand a month to call it 30 36 grand a month right now in revenue team of four based in new york kind of spread out throughout the state bootstrapped which i love too early to talk about economics but growing rapidly frank thanks for taking us to the top thank you very much have a great day