A Simplified and Numerically Stable Approach to the BG/NBD Churn Prediction model
Other Statistics
2025-02-19 v1 Machine Learning
Statistics Theory
Statistics Theory
Abstract
This study extends the BG/NBD churn probability model, addressing its limitations in industries where customer behaviour is often influenced by seasonal events and possibly high purchase counts. We propose a modified definition of churn, considering a customer to have churned if they make no purchases within M days. Our contribution is twofold: First, we simplify the general equation for the specific case of zero purchases within M days. Second, we derive an alternative expression using numerical techniques to mitigate numerical overflow or underflow issues. This approach provides a more practical and robust method for predicting customer churn in industries with irregular purchase patterns.
Cite
@article{arxiv.2502.12912,
title = {A Simplified and Numerically Stable Approach to the BG/NBD Churn Prediction model},
author = {Dylan Zammit and Christopher Zerafa},
journal= {arXiv preprint arXiv:2502.12912},
year = {2025}
}
Comments
4 pages, numerically stable BG/NBD