How Rocketreach CEO Amit Shanbhag grew Rocketreach to $221M revenue and 75K customers in 2024.

this is the top where I interview entrepreneurs who are number one or number two in their industry in terms of Revenue or customer base you'll learn how much revenue they're making what their marketing funnel looks like and how many customers they have I'm now at $20,000 per to 5 and6 million he is hent on global domination we just broke our 100,000 unit soul Mark and I'm your host Nathan Latka I just finished traveling south East Asia for 41 days and I usually always get sick when I travel and quite frankly eating is difficult for me it's hard to find a restaurant and I'm spoiled in Austin with my personal chef well I took these little packets with me this time 30 of them in my carryon suitcase they kept me totally healthy with 11 different secret ingredients you can see them at Nathan la.com juu I'll tell you more later on in the show that's Nathan la.com slj top tribe you know I don't have a lot of time to waste that's why I use fresh books to send out invoices and make sure I'm collecting my money to get your free month go to Nathan l.com fresh books and enter the top in the how did You Hear About Us section this is episode 635 and coming up tomorrow morning you'll learn from Amar PRI cowcat his Bangalore startup just hit $40,000 a monthly occurring Revenue helping 18 customers get consumer data using social intelligence with his company thr good morning everybody Nathan ladka here my guest this morning is am shanag he bootstrapped rocket reach from zero to over 300,000 registered users in its first year rocket reach and the rocket reach API are trusted by some of the largest companies on the planet like apple Google Chase Morgan Stanley just to name a few he has more than a dozen patents and started his professional life writing code for geostationary satellites he's also a judge for the MIT 100,000k competition and hopes to invest more time and money back into the startup ecosystem Amit are you ready to take us to the top sounds good I'm here all right so last time we had you on it was actually a very good episode many many people really enjoyed it that was episode 465 in November of last year and at that point You' passed 120,000 paying customers uh your goal for uh or you pass $200,000 in month your curring Revenue your goal for 2017 AR is to hit uh you said $10 million are all those on track you're beating those goals yeah so yeah I don't know I don't remember exactly how many users we had back then but we have almost 300,000 users now um our growth has continued to accelerate so all the all the signs definitely look positive and uh we're also investing in a couple of features in the uh product that uh we hope we really accelerate the revenue when you say be specific with 300,000 users people don't know what that means are those paying customers or free users no those are so we have three tiers of users there are there are Anonymous users who just use a site a little bit and go away there's signed up users so there are 300,000 signed up users and there are paid users who are less than 300,000 obviously okay and last time you told me you had about 120,000 paid customers are you still at about that same area or have you gone up to 130 140,000 yeah they're not exactly exposing that number but it's somewhere you know it's definitely lower than 300,000 okay well but am me you you already told me that number on the last episode that it was 120,000 I mean all I'm asking is have you grown above that over the last four or five months we've continued to grow we've uh you know ever since March of 2015 we've had you know double- digit growth um High double digit growth and that's continued to continue to occur okay great and you so you mentioned one of your focuses here in q1 is to get more teams signing up so so how do you do that pragmatically how are you approaching that yeah so a little bit of a journey right so what what what have we been up to so we've um we we tried to do a few things to figure out how to accelerate a revenue growth one of the um approaches that we tried is we tried to go more into the lead generation space which is um rather than just providing contact information and just doing contact Discovery let's give customers a list of leads based on uh users who signed up for their service every day or something we call it lookalike uh lead generation the key learnings from trying to do a lead generation product were one that uh the end customers Hold Us responsible for much higher um you know a much higher value of you know a much higher quality of data and for things that are out of our control if we provide a list of leads to our customers then they have to actually you know reach out to them and follow up on those leads um and how well they do that will affect how they gauge our data which which is sort of unfair so this is like the same spaces like Inspire beats or Leo or lead genius prospec toy Pro leads these kind of come toer these kind of companies right absolutely twer probably does uh contact Discovery but lead genius is a good is a good example of somebody that does lead generation okay so if you think about lead lead genius right um they charge you much more per row of data because they are giving you what they would consider a qualified lead yeah they've got about 200 customers and their monthly RP is about 3.3 Grand 3 3,300 bucks exactly um so uh you know so so the problem with that the problem with that space is one um the the uh the bar is very high like the quality of the data has to be very very good otherwise people will um people will churn out very quickly so how I mean could you not get to the quality of data that like a lead genius has what was the challenge there so we did not so Le genius uses a combination of people and software okay uh we wanted to do it completely with uh completely with software not rely on human intervention so one of the things that we noticed is that we started hitting an upper bar of how good our quality was which was what if if you give me 100 emails how many of them are going to bounce um it's not the bounce it's let's say we give you a 100 uh emails the question is how many of those are good leads for you and that's a subjective evaluation um we found that we were topping out out at about 40 to 50% good leads were good leads the rest of them programmatically generated were not great leads okay the other part of the problem is you've given this data set to your customer they have to now follow up on them right so they could do direct emails they could do Facebook ads Twitter ads um they they have to call those people up if they have phone numbers right they have to follow up on that now the the way that they do that their sales pipeline if that's not good they will eventually pass the blame on to us and then say you know this did not work because the leads were not good enough how does lead genius solve that problem to be honest I don't know I I don't know whether they are able to solve that problem this is you know as long as you're providing leads and you're not in control of pipeline you are you know you're inadvertently going to be held responsible for things that are out of your control well there yeah I mean I look that was episode 265 for anyone that wants to go listen to it but I mean they've got less than 2.8% gross customer turn per month and their Mr is above $700,000 per month so I mean look their ARP is way higher than you maybe they're putting humans on every account they only have 200 accounts right um you know if they're if they're able to do it with very low churn that's awesome but what we found when we were doing it ESP especially because we were not you know we were not doing the human intervention part of it um is that first of all the cost of getting each customer was very high because we had a you know the sales cycle was long lot of handholding How High what was the cost um I mean we're talking about like almost $1,000 to acquire a customer okay and what's your arpo that you have on average so we never really we never really release this product to a point where you know we have good metrics on these things we have 120,000 customers though you must you must know what an average is that's a huge sample size right for lead generation though the lead generation product is not wasn't that we basically piloted it we never really took got it got it so the the amount of money that we were getting per um per delivery of data set was somewhere between $3,000 to $7,000 right and and the thing is that they wouldn't last for more than two to three months because eventually they they would um eventually they would find that the the quality of the lead but that math Works doesn't it if you spend a grand to get a user that pays you three grand per month that's a grand for every nine grand I mean why that math seems to work to me it does work but the margins are not as high as a selfs serve uh model okay I think this the scaling of that is much much more difficult okay and were you powering I mean a lot of your data you want to do it with software were you kind of using a combination of what clear bit and full contact I mean what other data sources were you using um um we're using a bunch of open apis right so...