How Shopify Merchants can Measure Retention - Shopify

This post introduces the BG/NBD (Beta Geometric / Negative Binomial Distribution) model as a probabilistic approach to customer churn and retention analysis, moving beyond arbitrary time-limit based definitions. It details the model's parameters (rate of purchasing \(\lambda\), probability of churn event \(p\)), its sufficient statistics (Age, Recency, Frequency), and how these are used to estimate customer behavior and probability of being active. The post also mentions the use of the 'lifetimes' Python package and Apache Spark for large-scale merchant data processing.