Predictive Analysis of Customer Churn in Community-Supported Agriculture Based on RFM Modeling

Urban Farm DB summary

High customer turnover is a significant challenge in China's Community-Supported Agriculture (CSA) industry. This study utilized RFM models (Recency, Frequency, and Monetary) and algorithms to regularly rank and classify the consumption ability of CSA customers. This was achieved by analyzing their recent purchase time, number of times of consumption, and consumption data.