Caracterización del proceso de fuga de clientes utilizando información transaccional

Fecha de Publicación: 2 julio, 2009
Industria: Otras
Autores:

Customer churn detection is relevant for any company: the cost of acquiring a good new customer is far greater than the cost of retaining a good “old” one. The proposed methodology characterizes the churn process of customers using their transactional data. The dynamics of the situation are modeled with Markov chains, where each state represents a group of clients with similar Recency, Frequency and Monetary value attributes. The
methodology characterizes the “path” that a customer leads to churn, besides estimating the churn probabilities in every period. Based on information analyzed, the methodology proposed detects how customers are moving slowly towards inactivity. This knowledge is valuable to managers because it gives them a timely signal they can use to define preventive actions to retain valuable customers.