Forecasting Customer Lifetime Value: A Statistical Approach

We propose a method of forecasting customer lifetime value using the customer usage database, sampling strategy, segmentation, modeling, and validation techniques in data mining.  The highly heterogeneous customer database being mined will allow the inclusion of uncertainty components in the estimation of customer lifetime value.  A hazard function model based on a truncated lifetime data of customers can provide adequate information to compute the value of the incentive to be offered and the length of the lock up period for the customer.

[1]  A. Zellner An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias , 1962 .

[2]  F. Dwyer Customer lifetime valuation to support marketing decision making , 1997 .

[3]  Rajkumar Venkatesan,et al.  A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy , 2004 .

[4]  Dirk Van den Poel,et al.  Benefits of quantile regression for the analysis of customer lifetime value in a contractual setting: An application in financial services , 2009, Expert Syst. Appl..

[5]  Dominique M. Hanssens,et al.  Modeling Customer Lifetime Value , 2006 .

[6]  Saharon Rosset,et al.  Customer Lifetime Value Models for Decision Support , 2003, Data Mining and Knowledge Discovery.

[7]  Bart Baesens,et al.  A modified Pareto/NBD approach for predicting customer lifetime value , 2007, Expert Syst. Appl..

[8]  Hans H. Bauer,et al.  THE CUSTOMER LIFETIME VALUE CONCEPT AND ITS CONTRIBUTION TO CORPORATE VALUATION , 2004 .

[9]  Ming Ma,et al.  Phase-type distribution of customer relationship with Markovian response and marketing expenditure decision on the customer lifetime value , 2008, Eur. J. Oper. Res..

[10]  Xi Chen,et al.  Exploring business opportunities from mobile services data of customers: An inter-cluster analysis approach , 2010, Electron. Commer. Res. Appl..

[11]  Andrew W. H. Ip,et al.  A dynamic decision support system to predict the value of customer for new product development , 2011, Decis. Support Syst..

[12]  Stephen C. H. Leung,et al.  Segmentation of telecom customers based on customer value by decision tree model , 2012, Expert Syst. Appl..

[13]  David J. Hand,et al.  On optimal intervention for customer lifetime value , 2007, Eur. J. Oper. Res..

[14]  P. Berger,et al.  Customer lifetime value: Marketing models and applications , 1998 .

[15]  Kiyana Zolfaghar,et al.  Estimating customer lifetime value based on RFM analysis of customer purchase behavior: Case study , 2011, WCIT.

[16]  L. Ryals,et al.  Measuring risk‐adjusted customer lifetime value and its impact on relationship marketing strategies and shareholder value , 2005 .

[17]  Karri Mikkonen,et al.  Exploring the creation of systemic value for the customer in Advanced Multi-Play , 2011 .

[18]  W. Reinartz,et al.  The Impact of Customer Relationship Characteristics on Profitable Lifetime Duration , 2003 .

[19]  Sunil Gupta,et al.  Customers as assets , 2003 .

[20]  So Young Sohn,et al.  Conjoint analysis for luxury brand outlet malls in Korea with consideration of customer lifetime value , 2009, Expert Syst. Appl..

[21]  A. Zellner Estimators for Seemingly Unrelated Regression Equations: Some Exact Finite Sample Results , 1963 .

[22]  Donald R. Lehmann,et al.  From Customer Lifetime Value to Shareholder Value , 2006 .

[23]  Lawrence Feick,et al.  Incorporating word-of-mouth effects in estimating customer lifetime value , 2006 .

[24]  Robert C. Blattberg,et al.  Can We Predict Customer Lifetime Value? Can We Predict Customer Lifetime Value , 2004 .