$0 to $70k MRR in 120 days
An Analytics Case Study for Apptopia
How we turned download and revenue data from apps in the App Store and Google Play into an indispensable market intelligence platform that was generating $70k MRR within 4 months.
In early 2015, Apptopia.com–a marketplace for mobile companies to buy and sell their apps–was looking for a second business opportunity to monetize the mounds of mobile app data they had collected: the actual download and revenue data from thousands of real apps across Google Play and iTunes. Apptopia knew that this data could be turned into a useful competitive intelligence analytics product for app publishers, advertisers, SDK companies, and investors that would provide a less expensive and better offering than the leading competitor, App Annie. However, they needed help turning all this data into a useful, usable, well-designed analytics product capable of becoming a successful subscription-based SAAS platform.
Instead of just showing users random tables and charts of time series data and “data visualizations” that don’t actually solve customer problems, Apptopia hired me to help them design a service that would allow app publishers and investors to answer real business questions prevalent in the app publishing world. Using my discovery process and a lot of dry-erase markers, we sketched out a product roadmap, including an MVP, and several follow-on features that would best satisfy the set of user goals, tasks, and business problems that we had uncovered.
And then I designed and helped them launch the MVP reflecting their new pivot to app intelligence.
When the new product launched in June 2015, it had no revenue. However, according to Apptopia CEO Eliran Sapir in a recent TechCrunch article, “within 60 days [of launch], we were at $30,000 MRR. Within 120 days, we were at $70,000 MRR.” By 2018, they made the Inc. 5000 with three-year growth of 363% and 2017 revenue of $2.8M.
Apptopia's customers include Facebook, Localytics, Verizon, Google, Pinterest, NBC Universal, Philips, Deloitte, Chartboost, and SendGrid and its data has been featured in The Wall Street Journal, Forbes, CNN and Barrons.
Brian brings a very high floor in terms of end results. The worst possible end result they will get from him is so much higher than what most designers can provide at their best.
When you’re bringing on a consultant, there is always a level of uncertainty about results, and there’s nothing worse than ending up with solutions that aren’t feasible, workable, or usable at the end of the process. While Brian’s processes differed from what I was used to, and I didn’t always want to get into the level of requirements detail that he felt was necessary, the bottom line is that Brian brings a very high floor in terms of end results. Given how many different responsibilities I am juggling at any given time, it was extremely comforting to know that my goals for the [new Apptopia analytics] product would always be met, and that my bottom line was so high. I’ve recommended Brian to my peers because the worst possible end result they will get from him is so much higher than what most designers can provide at their best.