To read this content please select one of the options below:

Measuring the impact of data mining on churn management

Miguel A.P.M. Lejeune (Miguel A.P.M. Lejeune is a PhD Student in the School of Management at Rutgers University, Newark, New Jersey, USA.)

Internet Research

ISSN: 1066-2243

Article publication date: 1 December 2001

4901

Abstract

Churn management is a fundamental concern for businesses and the emergence of the digital economy has made the problem even more acute. Companies’ initiatives to handle churn and customers’ profitability issues have been directed to more customer‐oriented strategies. In this paper, we present a customer relationship management framework based on the integration of the electronic channel. This framework is constituted of four tools that should provide an appropriate collection, treatment and analysis of data. From this perspective, we pay special attention to some of the latest data mining developments which, we believe, are destined to play a central role in churn management. Relying on sensitivity analysis, we propose an analysis framework able to prefigure the possible impact induced by the ongoing data mining enhancements on churn management and on the decision‐making process.

Keywords

Citation

Lejeune, M.A.P.M. (2001), "Measuring the impact of data mining on churn management", Internet Research, Vol. 11 No. 5, pp. 375-387. https://doi.org/10.1108/10662240110410183

Publisher

:

MCB UP Ltd

Copyright © 2001, MCB UP Limited

Related articles