Conner DiPaolo, Applied Scientist
- Feb 20, 2020
Summary Here at Yelp, we generate business wins and a better platform by running A/B tests to measure the revenue impact of different user and business experience interventions. Accurately estimating key revenue indicators, such as the probability a customer retains at least \(n\)-days (\(n\)-day retention) or the expected dollar amount a customer spends over their first \(n\) days (\(n\)-day spend) is core to this experimentation process. Historically at Yelp, \(n\)-day customer or user retention was typically estimated as the proportion of customers/users we observed for more than \(n\) days who retained more than \(n\) days. Similarly, \(n\)-day spend was estimated...