Finding PMF with a contrarian approach
How we broke through several retention and DAU plateaus on Wizz with radical data-driven iterations, achieving product-market-fit and profitability in less than 1 year.
At Voodoo Apps Lab, I joined two others product engineers and one manager to work on social apps. Expectations were quite high as our DAU objective was in the millions. We needed to iterate fast, and radically.
- A new app or major iteration every 2 weeks
- Focus on engagement (retention)
- iOS & US only
We iterated radically breaking our app’s core-loop “make new friends” several times. Consequently, each time we made a major update, our App Store rating dropped drastically and users complained via support. It was quite counter-intuitive at first because it happened especially when our metrics improved significantly.
Fortunately we were backed-up by data and one north-star KPI so we were very confident despite all the noise. We were just bad at communicating updates. While we are all user-centric in this space, it’s important to not listen blindly to our users though, since in general they don’t always appreciate change.
We rounded-up the first year reaching 70% D1 and 200k DAU and being first on the App Store several times in the US. After this, we created a subsidiary inside Voodoo with my associates Gautier & Aymeric to start scaling the team and the product.
Check this another post for more recent work on the project ✌️