Abstract :
Preventing customer churn is an important task in customer relationship management (CRM), in which the identification of customers with an intention to terminate one or more contracts plays a pivotal role. Today, typically survival analysis is used for this purpose. These approaches, in their standard configuration, assume a proportional, time-invariant influence of covariates. In telecommunications, for instance, these assumptions are questionable because of existing fixed-term contracts and term of notice clauses. These can be expected to result in non-monotonous cancellation probabilities over time, with increased frequencies of cancellation in time periods before minimum subscription periods end. In this paper, we consider customer-specific contract duration dates within established methods of survival analysis. We introduce a novel, non-standard feature generation procedure for this purpose. In addition, we study the impact of product variety in a customer´s portfolio on his churn probability, as there is evidence both from theory and practical experiences in other industries that product variety can be related to loyalty. In the empirical part of the paper, we evaluate the proposed extended model using data provided by one of the largest telecommunication companies in Europe. Results show that both model extensions significantly increase churn prediction performance in out-of-sample tests.
