Evolutionary computing applied to customer relationship management: A survey

Abstract

Customer relationship management (CRM) is a customer-centric business strategy which a company employs to improve customer experience and satisfaction by customizing products and services to customers' needs. This strategy, when implemented in totality eventually increases the revenue of the company. Traditionally, data mining (DM) techniques have been applied to solve various analytical CRM tasks. In turn, optimization techniques have long been used for training some of the DM techniques. However, during the past few years, evolutionary techniques have become so powerful and versatile that they can be deployed as a substitute for some DM techniques. This trend caught the attention of the researchers working in the analytical CRM area as they too started solving the CRM tasks using evolutionary techniques alone. In this context, we present a survey of evolutionary computing techniques applied to CRM tasks. In this paper, we surveyed 78 papers that were published during 1998 and 2015, where the application of evolutionary computing (EC) techniques to analytical CRM tasks is the main focus. The survey includes papers involving evolutionary computing techniques applied to the analytical CRM tasks under single- as well as multi-objective optimization framework. The purpose of the survey is to let the reader realize the versatility and power of EC techniques in solving analytical CRM tasks in the service industry and suggesting future directions.