How Motiva CEO David Gutelius grew to $1.8M revenue and 36 customers in 2018.

hello everyone my guest today is david gutellius he is the ceo and founder of a company called motiva ai partner at venture studio the data guild uh david is a serial entrepreneur previously founded social kinetics which was sold to red brick health and proximal labs which was sold to jive software he served as chief social scientist at jive and part of the team that took jive to an ipo in 2011. he began his career as a program manager for darpa's callow the largest machine learning project funded by the us government today he's an active early stage investor and advisor david are you ready to take us to the top absolutely all right uh let's talk about the company what do you guys do and what's your revenue model motiva is all about using machine learning at scale to help our customers both on the b2b side and b2c side develop deeper relationships with customers at the end of the day what we're trying to do is use ai to create trust between humans that's really what we're up to any sector focus or anyone really anyone what we're finding is we're having some really great success in healthcare and life sciences around patient engagement but it really uh goes across all sectors and verticals give me an example of healthcare so let's dive deep onto that use case for a second how would a healthcare provider use you yeah absolutely so you could use this in a number of different ways but one way would be on the kind of acquisition patient acquisition side so provider system looking to get the right patients in the door we can help them identify who those folks are and develop messaging strategies that really appeal to those people in a deeper more personal way and that's really kind of the secret sauce is to use learning to personalize and engage folks in a much more uh meaningful way but this is all happening pre-sale not post sale correct yeah that's so that use case is pre-sale but you can think of kind of you know staying with health care more of a patient engagement use case so they've seen the doc already and now it's time for a follow-up and we can be in the middle of that exchange not necessarily with humans in the mix but with machines kind of driving the communication between the back and forth between the patient and provider and again using the learning to optimize how we engage that patient so the whole point is to kind of deepen that relationship over time keep those patients or customers depending on the vertical engaged and growing that relationship in terms of the not just sort of personal human depth but also the the revenue as well so i imagine my audience when they're hearing this they're going okay wait like it's kind of a marketing engagement to drive a sale on an engagement post sale to drive activation and maybe expansion revenue and they might think well like we use outreach for this or something like that how would you be different than like what manny's building at outreach yeah absolutely so the the way to think about us is kind of a brain for those outreach type platforms we hook into the major marketing automation engines like eloqua like responses all those sorts of traditional modes of actually you know reaching out and engaging folks at at some level the difference with motiva though is really that we're using some new generation machine learning to understand what strategies work understand what strategies don't do more of the stuff that works automatically for you so it's really about trying to scale kind of human team's ability to connect with their end audiences that's kind of the bottom line and it sounds like you have a lot of different cohorts you're working with here but what would you say on average right a brand or a customer is paying you to use this technology uh sorry can you rephrase that yeah sure i'm simply asking average acv right i'm sure you have a lot of different cohorts but on average what's the company pay to use this oh right so it's anywhere from on the low side about 20 000 a year all the way up to a couple of million okay and i assume you probably have power laws the biggest customers make up call at 40 50 of the revenue in some cases but would you say i mean the average is closer to 30 40k per year average i would say it's about about 50. about 50. okay fairly healthy so that's a that's enough of a price point where you can kind of afford to put touch on the sale and kind of have an inside sales machine do you have an inside sales machine what's your acquisition look like yeah so the acquisition model is very savvy using some of our own technology to identify the right kinds of customers and kind of nurture them through on an account basis so it is a you know in that sense a traditional sales enterprise sales model it's a b2b the inside inside sales team is me because we're scrappy and tiny how many how many people total right now so we've got nine total i love that small and scrappy that's great and put this on a timeline for us when did you launch uh so we launched in 16 but we stayed stealth for about 18 months and came out in 17. so we've all been out for you know more or less a year or so and ever the whole team's in reno no we're split all over the place we've got a couple of folks in japan we've got folks in toronto canada and the bay area and i'm the the sole uh operator okay so nine nine remote that's good total freedom and uh what if you guys so over the past call it year what have you scaled to in terms of total customers using the platform uh we don't really talk about that we're a little bit uh still under the covers there um but uh it's uh it's a couple dozen okay couple dozen yeah is that what you said okay very good and um and walk me through the getting these first customers you mentioned obviously you're kind of the inside sales machine how are you training kind of your you know motiva brain to figure out what kind of accounts to go after yeah so it's a lot about identifying characteristics that we think are good fits especially where we are as a company early on so as a founder kind of serial founder what i've found is that you know personally reaching out once we've identified kind of a cohort to go after really personally reaching out as a founder ceo and establishing a trusting relationship and then building on that sort of basis of early more progressive customers to both understand what is working in our product and maybe what still needs some work and then also where to go next in terms of uh outreach into to new customers so it's it's a very kind of hands-on model have you bootstrapped this or have you decided to raise capital we bootstrapped it uh for about a year and then decided that we needed some growth capital injected so we did a very small round uh in 16 just essentially with you know folks that that i knew uh and we've been growing organically ever since okay so how much total in the company to date uh we don't talk about that either okay why not out of curiosity uh you know the the venture capital market loves to gossip about these things and we like to just uh keep it quiet and keep it modest until we're ready to publicize that sort of information yeah by the way i i actually i actually if you listen to my interviews we've integrated out 3 000 b2b ceos i actually much more appreciate a bootstrap story versus a funded one so i'm not it sounds like you feel like i'm judging you because you might not have a sexy headline that you've raised 20 million bucks at a billion dollar valuation i'm generally just curious to get to a couple dozen customers and the stage you're at today how much you've raised to do that i mean are we talking a couple you know less than a million bucks or less than 10 giving me a range oh yeah it was around a million dollars for our seed round yeah that's great and and and um yeah thanks for sharing that i appreciate it um talk to me too i mean you're only you know caught a year a year and a half in but churn's critical in any sas company how do you think about your churn very good question so what we like to do just in terms of the product itself and the way that it's designed is create experiences on the customer side where it is really well aligned with the users careers themselves that makes sense so really the way that we think about the product is almost an extension of the human marketer for us an augmentation of kind of what they're able to do so we love making them heroes and the way that we've designed the product is all about giving them confidence sort of in what we do in terms of the marketing optimization but also in the sense of allowing them to demonstrate impact in their organization to pay a lot of attention to metrics a lot of attention to very easy to understand reporting that they can kind of review internally with their stakeholders whether it's their boss or their large organization or peers so it's really for us we think about churn as how do we build relationships for our main stakeholders on the other end of that table um and really think about that as a a relationship that we you know nurture in a very personal way oh and david just to push harder i mean your ability to deliver on all those goals you just so articulately delivered is measured by churn so what is your churn today and how do you continue to drive that down oh so the actual churn is uh zero we haven't lost a single customer any downgrades no okay yeah the way that we price uh would make it difficult to kind of downgrade you're either kind of on the platform or or you're off okay so it's based on the number essentially the size of the audience that you're dealing with in terms of marketing and outreach literally number of contacts is the pricing access exactly that's right what other pricing axes do you use uh that's it uh we you know it's full i o whatever data you need to support that level of uh outreach it's all about the unique number of people you're trying to reach out to in your in your audience so because you've had no gross revenue churn obviously your net revenue retention if you have any expansion is going to be above 100 how far above 100 are you today are we talking like 110 or 150 or higher uh we're probably yeah we're probably 140 off the top of my head yeah 130 140. and what does that mean to you in terms of a signal that you have no churn you know the obvious one is oh that's great it's a healthy company but you could argue the other side very easily and say well you're priced too cheaply yeah i think that's right and as an entrepreneur i always worry about that is kind of where are we really hitting our sweet spot the the thing that i guess i've come to realize it's just it's early enough where we want to get points on the board we want to make sure we can tell those really compelling stories to to new customers down the road so i don't want you know the case if it's in early days um you know we're mispriced a little bit we'll figure that out as we go it's really about those relationships and the stories we tell out of these you know first days yep and help me understand you've been through this a few times so you understand trends and cycles and aggressive versus pullback how aggressive are you being right now in terms of acquiring new customers and that's for the sake of the example use your average of a 50 000 acv what would you spend to acquire that customer oh not much uh it's really about very personal outreach um i would say it's probably total fully weighted if 400 500 bucks okay for that customer no i don't have a sales force that's a big well you i mean you look at you and your salary right if you're doing inside sales you're taking demos calls flying around you're including your you know your salary into that as well yeah that's that's about right yeah yeah i mean that's really i mean it's really healthy so i mean why not spend more to drive growth that's a really healthy payback period yeah because we want to get the product right this is what's a little bit but you have no churn david no no but that's not the question it's really about the machine learning product itself and in my experience this has been one of the biggest challenges in creating kind of machine learning products that scale massively so we're still in the early days of trying to figure out what's going to work both from a kind of pure deep technology perspective and sort of the problems that we're solving and we really need to get that mix right in order to make sure that we can support the level of growth that you know we would like to get to so it's it's really about just making sure that that mix is right before we expand and you know really put it into the top of the funnel really drive that that you know shape of that funnel in a different way but david something though about the feedback here loop isn't matching up because what you just told me is you feel like you're not totally efficient yet there are still things you can work on however you're not churning any customers so what signals are you using to figure out if you're doing right or doing wrong uh so the main signal that i'm using right now is just um how long it takes to land a customer so this is the length of the sales cycle which is what um it's generally about eight months to get to from beginning to end and then i think that the onboarding process of helping customers really get used to everything that they can do with motiva so that's a design question it's an onboarding question and this is a again something i've faced over and over again with machine learning products before is is making sure that design is right so that customers can really be as independent as possible and i would say we still got stuff to lock down on that side to make sure that onboarding is right make sure that those teams really can use the product and the way it was intended so there's still some learning that we need to do i think there david my audience is not going to understand an eight-month sales cycle at a 500 cac if usually if you have an eight-month sales cycle you're talking thousands in cac help me understand that yeah well it's it's to do with i think the decision that i've made to not go kind of mass market and really tailor the early customers to kind of the best value customers that we can have as a company right now you know which is uh you know particular kinds of customers that have a mix of um in our in our case kind of marketing ops professionals who can really use the product and really exercise its power so what we've done is kind of throttle that back not spent a lot on kind of acquiring the the revenue and really trying to get the the product to a state where we can scale it yeah but you're the only just to be clear though you're the only one doing sales internally correct david you're the i just want to make sure i understand this you're the only one doing sales internally correct yes correct yes i mean there if you're including if you've added 30 a couple you said a couple dozen let's assume it's 36 right so it'll be aggressive 36 customers i mean there's no way you're including whatever you're paying yourself in that fully weighted cost you're basically looking at that and either you're not paying yourself and you look at it as sweat equity because you've had exits in the past and that's why your cack is so low i mean is that fair yeah i have a low salary that's for sure yeah but even if it's the lowest even if it's as low as 50 000 bucks right and you've got and you've spent your time adding 36 customers 36 into 50 000 that's 1500 bucks in cac right there yeah that's right that's right so i don't have time to go after that level of customer right now and i've got you know other duties as ceo uh including like you know running product and what do you mean what do you mean that level of customer the that number of customers at once why we've kind of throttled back uh and not gone off after you know the more than basically the customer pipeline that we've got right now well you're talking very slowly very carefully your cac would be higher if you're going after less customers and 36 on the same salary let's say you're only going after three customers i'm saying that i can't handle that many so i wouldn't i know that that's feeding my point though so let's assume that you were paying yourself a very low salary of 50 000 bucks per year and an average year you don't handle 36 you can't handle that many let's see you only handle 10. that's a 5k that's actually a higher cap i'm just trying to understand you're not including your personal salary or whatever you pay yourself in that fully weighted cache number yeah i am i am we pay virtually nothing besides my time we do a little bit of advertising a little bit of of outreach on uh get kind of sponsored blog posts but that's that's the extent of it yeah but david sorry the math isn't adding up 500 cac and you're let's say you're handling less than 30 cust new customers a year if i take 30 customers times a 500 cac and assuming that cac is only your salary that's 15 000 per year in salary that's true yeah that's the math doesn't work so where am i going wrong yeah i'm not sure maybe we're spending yeah a different amount than that i have off the top of my head it's it's not much and it is only me so yeah the reason i'm pushing so hard on this by the way is people build models around sales rep productivity and usually the first sales rep is the founder and i just want to make sure that i'm not giving them unrealistic expectations you there is no way based on these numbers that you're including whatever you're paying yourself in that cache number unless you're paying yourself 15 000 bucks a year or lower yeah right no it's it's around 40k yeah okay i mean so again let's say you're only handling 30 customers on that i mean that that would be a cac that's much higher than 500 bucks so you see what i'm saying right yeah yeah okay okay got it got it cool you're right i just want to make sure i just thank you for cleaning that up i wanna make sure i didn't miss that um uh okay so nine people remote you're perfecting the system before you double down on kind of scaling uh less than a million bucks raised at this point couple dozen customers caught maybe 36 and you said earlier 50 000 kind of acv average that would put you at about 150 grand per month right now on revenue is that about right that's all right and and what's growth look like so go take me back a year what were you doing per month growth is probably between again kind of throttling it back it's sort of engineered this way but between 10 to 20 just given given the month okay so trying not to add too many on per month um and just you know grow sustainably what's a year over year though so 150k today go back to october november 2017 what were we doing that month uh so october 2017 it was i was probably that was when we first that was when we first came out so it's more like 70k okay good so about maybe doubling your every year yeah yeah yeah that's great fair enough good all right let's wrap up here uh with easier questions number one what's your favorite business book my favorite business butch book is nudge by richard thaler it's a good one number two is there a ceo you're following or studying right now um you know in terms of ceo roy bahat he's not a typical ceo but roy bahat at bloomberg beta yep uh number three what's your favorite online tool for building your company oh gosh google apps yup number four how many hours i sleep to get every night i get eight and a half to nine okay and what's your situation married single kiddos married no kiddos no kids and how old are you uh i am 47. 47 years young last question david what do you wish your 20 year old self knew uh to take it easy not sweat so much not stressed so much there you have it take it easy motiva again adding a brain behind your you know well-known outreach platforms like outreach sales off these kinds of things using artificial intelligence to help drive that founded in 2016 now nine people remote uh about you know caught couple dozen customers doing about 150 grand per month right now in revenue that's up doubled year over year they're doing about 70 grand per month just a year ago average acv especially first year is about 50 grand but they're expanding that contract value quickly net revenue retention annually about 140 percent as people add more contacts into the platform david thank you so much for taking us to the top hey thanks nathan have a good one