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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.

Keywords

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