Case Study: Swimply increases bookings by 20% with Statsig

How Swimply increases bookings by 20% with Statsig

Swimply, an online marketplace for renting private swimming pools and sports courts, needed a more affordable and straightforward experimentation platform that could support its data science needs without heavy setup. After evaluating legacy tools like VWO and Optimizely, the team turned to Statsig for full-stack feature flagging and A/B testing.

With Statsig’s experimentation and feature flagging platform, Swimply integrated Segment events, used offline calculations from Snowflake, and ran tests across search and ranking algorithms as well as front-end flows. This gave the team faster experimentation, easier traffic allocation changes, and unbiased training data for its predictive model, ultimately helping Swimply increase bookings by 20%.

Swimply

Michael Sheldon

Head of Data