Targeting Customers with Statistical and Data-Mining Techniques

Author:

Drew James H.,Mani D. R.,Betz Andrew L.,Datta Piew1

Affiliation:

1. Verizon Laboratories Incorporated

Abstract

Operationalizing a relationship management program requires a retention strategy that is sensitive to an individual customer’s position in the service life cycle, while being financially sound for the provider. To this end, estimating a customer’s hazard function and remaining tenure with the company can lead to important insights into marketing tactics and constitute fundamental building blocks for methods of targeting important customers. The authors describe a way of estimating these quantities using a combination of statistical and data-mining techniques. The resulting customer hazard information leads to a generalization of lifetime value (GLTV) that explicitly accounts for company actions and their success in relationship management.

Publisher

SAGE Publications

Subject

Organizational Behavior and Human Resource Management,Sociology and Political Science,Information Systems

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