A neural network extension for solving the Pareto/Negative Binomial Distribution Model

This research proposes a new estimation scheme to solve the estimation burden of the Pareto/NBD model and to release its power in out-of-sample prediction and then builds a neural network-based model (NNA-based model) for parameter estimation of the Pareto/NBD model, by designing a loss function to include the likelihood of the Pareto/NBD model and the mean absolute error.

Introduction

In customer relationship management (CRM), market practitioners and academic researchers are concerned about how a company maintains long-term and sustainable customer relationships (Bolton & Tarasi, 2017; Payne & Frow, 2005). A long-run...