
Statistics Papers
Document Type
Journal Article
Date of this Version
2008
Publication Source
Marekting Science
Volume
27
Issue
5
Start Page
829
Last Page
843
DOI
10.1287/mksc.1070.0328
Abstract
Two widely recognized components, central to the calculation of customer value, are acquisition and retention propensities. However, while extant research has incorporated such components into different types of models, limited work has investigated the kinds of associations that may exist between them. In this research, we focus on the relationship between a prospective customer's time until acquisition of a particular service and the subsequent duration for which he retains it, and examine the implications of this relationship on the value of prospects and customers.
To accomplish these tasks, we use a bivariate timing model to capture the relationship between acquisition and retention. Using a split-hazard model, we link the acquisition and retention processes in two distinct yet complementary ways. First, we use the Sarmonov family of bivariate distributions to allow for correlations in the observed acquisition and retention times within a customer; next, we allow for differences across customers using latent classes for the parameters that govern the two processes. We then demonstrate how the proposed methodology can be used to calculate the discounted expected value of a subscription based on the time of acquisition, and discuss possible applications of the modeling framework to problems such as customer targeting and resource allocation.
Copyright/Permission Statement
Originally published in Marketing Science © 2008 INFORMS
This is a pre-publication version. The final version is available at http://dx.doi.org/10.1287/mksc.1070.0328
Keywords
customer acquisition, customer retention, customer retention management, stochastic models
Recommended Citation
Schweidel, D. A., Fader, P. S., & Bradlow, E. T. (2008). A Bivariate Timing Model of Customer Acquisition and Retention. Marekting Science, 27 (5), 829-843. http://dx.doi.org/10.1287/mksc.1070.0328
Included in
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Date Posted: 25 October 2018
This document has been peer reviewed.