Modeling customer lifetime value, retention, and churn
Résumé
Customers represent the most important assets of a firm. Customer lifetime value (CLV) allows assessing their current and future value in a customer base. The customer relationship management strategy and marketing resource allocation are based on this metric. Managers therefore need to predict the retention but also the purchase behavior of their customers.
This chapter is a systematic review of the most common CLV, retention, and churn modeling approaches for customer-base analysis and gives practical recommendations for their applications. These comprise both the classes of deterministic and stochastic approaches and deal with both, contractual and noncontractual settings. Across those situations, the most common and most important approaches are then systematically structured, described, and evaluated. To this end, a review of the CLV, retention, as well as churn models and a taxonomy are done with their assumptions and weaknesses. Next, an empirical application of the stochastic “standard” Pareto/NBD, and the BG/NBD models, as well as an explanatory Pareto/NBD model with covariates to grocery retailing store loyalty program scanner data, is done. The models show their ability to reproduce the interindividual variations as well as forecasting validity.