Assessing the Impact of Regret on Customer Churn in E-Commerce: A Data-Driven Analysis

Problem Statement: Customer churn is a critical challenge for e-commerce businesses, causing revenue loss and high customer acquisition costs. Objectives: This study aims to analyse the impact of buyer's and hesitator's regret on customer churn and to identify key behavioural features that predict churn. Methods: Utilizing a public e-commerce churn dataset, features like Order Amount Regret and Complaint Rate were engineered to capture customer regret. Statistical tests, including Chi-Square and Mann-Whitney U, were used to assess the significance of these features. Visual analyses, such as boxplots and violin plots, validated the findings. Results: Regret-related behaviours, particularly high Complaint Rate and Order Frequency, emerged as strong predictors of churn. Significance of the Study: Understanding and addressing regret-related factors can enhance customer satisfaction and reduce churn.