How Voicea CEO Omar Tawakol grew Voicea to $1.1M revenue and 1K customers in 2019.

hello everyone my guest today is omar tawakal he is the chief executive officer of voicia prior to the company he was the founder and ceo of blue kai which was the world's largest consumer data marketplace in dmp oracle acquired the company in 2014 and he served as the svp and gm of the oracle data cloud omar earned an ms and cs from stanford where he's researched and published work on ai agents all right um are you ready to take us to the top yes why didn't you drive me why did you stay at oracle you didn't like the data cloud no i had a good time there i stayed there for two and a half years and sometimes you just get the entrepreneurial itch and uh here we are two and a half years in mountain view is like eternity right that's how it works you're supposed to stay for 13 13 months past the cliff then move on and then get your equity in a new startup right you know uh it was a fun ride there because i was reporting to thomas curien who was uh just a great guy to work for yeah well i was reporting to steve miranda also who was amazing all right let's talk about voicia so what's company doing what's your revenue model is you peer play sas yes it is uh basically our it's a pure place sas we emulate uh things like dropbox zoom where uh i call it consumerized b2b anybody can use us there's a free model you can upgrade to paid and then when we see multiple people in an organization using us then the team tries to engage and sell enterprise solutions okay great so bottoms up and then i mean give me a sample of a customer and how they're using you yeah so we have some financial institutions where whenever they speak to customers they'll have either their on the call capturing uh items updating salesforce updating trello after the call so they know what the follow-ups are okay interesting and is that your main target financial institutions you know it's um it's a bit broader than that anybody who uses webex or zoom or google meet is a target for us essentially those systems are are the plumbing they get you into the call they make the call smooth our job is to be the intelligence so that you can just focus on the conversation we capture everything we transcribe it we help you identify moments that look like actions and then we can help you automatically update workflow so instead of going back to your desk after five hours of meetings trying to remember five hours of actions uh we we try to nudge nudge you along and do some of that for you and give me a general sense here of what your sweet spot is so on average what's the company gonna pay you per year to use your technology yeah it's uh it ranges from nine dollars a month to thirty dollars a month per individual user and um we have seen a lot of viral growth so we'll get in with it to you know one or two people and then it grows to five twenty five hundred 100 500 and you know we've only been uh charging for about 12 months oh great and just to avoid going i mean i i'm sure you have like hundreds of different customer profiles based off team sizes but if you take your total kind of you know paid companies using you today divided by how many kind of seats across all of them what would you say the average team size is using are we talking like 10 or like a thousand i'd say average would be 10. we do have some people who are like you know between 500 and a thousand yeah but uh right now let me give you a sense why we only introduced the enterprise option really in january so um that's where we've seen the growth if you look uh a year ago it was dominated by individuals and now we're dominated by uh by groups and teams in terms of the the number of licenses so it's changing quickly yep no that makes for sense basically that's code for that average is going up five months ago is maybe five per account now it's ten and maybe by the end of the year it's you know fifty or sixty yep that's the goal but at ten bucks on average i started ten seats on average per account with yeah nine bucks a seat minimum you're talking kind of price points somewhere around 100 bucks a month in terms of uh in terms of your historical base and what they pay you and that's obviously increasing with new customers today yeah yeah i'd have to check the exact number but you're in the right ballpark yeah okay interesting um i want to get this kind of on a timeline when did you launch the company 2017 uh january so we started full time uh we went into uh alpha in the summer uh beta by the end of the year and we started charging in the summer of 2018. okay i always like to ask especially like a guy like you who's been through the the wheel before would you spend on the mvp before your first dollar revenue how much did i spend to get to the first dollar revenue yeah like you know some people will pre-sell an idea before they spend a dollar some will spend five million dollars before they go out and make one dollar of sale i'm just curious where you fall on the spectrum what'd you guys put into the tool before you sold your first dollar yeah good good question so really the first thing the most thing i was focused on before even charging a dollar was really usability and usage and growth so um i'd say we we worked for about five months actually our cto came in february and we launched at the uh june so you know it was like i'd say about uh five months and we were ramping up people so it was a fairly small spend initially yeah and then we said alpha and beta we started hiring a bunch of people so we started ramping up spend and we stayed in that mode for a year so you know it you could argue somewhere um under you know somewhere between four or five million before we started charging but um but we started seeing signal in usage way before we started charging so for example in 2018 all our usage parameters went up about 100 x what are they what are your key usage parameters um so in the beginning before we started charging we started really looking at how many people come in the door and start inviting eva to four meetings in the first month and that was really a signal that they trusted eva enough to have it in their meetings participating and that was our bread and butter like how how much could we do that and that one grew like i said about 100 x uh in that year well what percent was that right so if you had 100 people come in today how many of them invited four people in the first month yeah so we've moved on to a different metric and we're no longer tracking that now that we have conversion to pay that's where we start looking at different metrics so if you look at conversion to pay um you know i think we're somewhere between three and five percent of the people who will come in we'll use it and we'll convert to pay but the problem with that number is it also includes um we acquire users in two basic ways the first one is through advertising the other ones through virality our virality coefficient now is it about point eight uh oh you're so you're so get it above one and you're showing a rocket ship man that's exactly what i do we were at point two when we started so we're just getting better and better and better pretty good so um so that's one way to require users and the other way is of course just through advertising and the the problem with advertising is it brings in some consumers and some business people and we're getting better better really just focusing on business people yeah uh because it's just cheaper to advertise and mechanisms that get you both but uh as we get better at the way we construct the ads and the landing pages we've seen the percentage of people come in with work emails and word calendar much much much higher and they convert better i want to come back to the viral coefficient but i want to compare the two real quick so on the paid side what's fully weighted cac uh you know i'm not sure i would disclose that um or maybe maybe what i'm actually asking is how maybe how aggressive are you being in terms of payback period are you comfortable with six months or you go for 12 months or more um good question uh i don't remember the answer to that i do have a sas dashboard and i don't remember the payback period but here's i think i'll give you a sense of it this way so um we acquire a user they convert to paid um and they generally uh are just if you look at their lifetime value in terms of how long they stay with us we we make money but not a ton why do we do it because many of those people convert to teams and then we make a lot of money because what happens is you you paid several hundred dollars for a user and if you're coming in and you know more than half our users are in our higher tier of um of offerings so the 30 bucks or nine or 30 months exactly and half of all people do a yearly commit so we look at it that way when we pay to acquire someone we we basically just get our money back but then a percentage of those people convert to teams and those teams are getting better bigger and bigger and so that's how we're making our money back yeah let me try and submit the real numbers and you correct me if i'm wrong when you pay on ads to get a 30...