A Cross-Cohort Changepoint Model for Customer-Base Analysis

63 Pages Posted: 29 Jul 2012 Last revised: 7 Sep 2016

See all articles by Arun Gopalakrishnan

Arun Gopalakrishnan

Rice University - Jones Graduate School of Business

Eric Bradlow

University of Pennsylvania - Marketing Department

Peter Fader

University of Pennsylvania - Marketing Department

Date Written: August 1, 2016

Abstract

We introduce a new methodology that can capture and explain differences across a series of cohorts of new customers in a repeat-transaction setting. More specifically, this new framework, which we call a vector changepoint model, exploits the underlying regime structure in a sequence of acquired customer cohorts to make predictive statements about new cohorts for which the firm has little or no longitudinal transaction data. To accomplish this, we develop our model within a Hierarchical Bayesian framework to uncover evidence of (latent) regime changes for each cohort-level parameter separately, while disentangling cross-cohort changes from calendar-time changes. Calibrating the model using multi-cohort donation data from a non-profit organization, we find that holdout predictions for new cohorts using this model have greater accuracy – and greater diagnostic value – compared to a variety of strong benchmarks. Our modeling approach also highlights the perils of pooling data across cohorts without accounting for cross-cohort shifts, thus enabling managers to quantify their uncertainty about potential regime changes and avoid “old data” aggregation bias.

Keywords: Changepoint, Cross-Cohort, Hierarchical Bayesian, Forecasting, Customer-Base Analysis, Customer Lifetime Value, Reversible-Jump MCMC

JEL Classification: C11, C53, M31

Suggested Citation

Gopalakrishnan, Arun and Bradlow, Eric and Fader, Peter, A Cross-Cohort Changepoint Model for Customer-Base Analysis (August 1, 2016). Available at SSRN: https://ssrn.com/abstract=2119337 or http://dx.doi.org/10.2139/ssrn.2119337

Arun Gopalakrishnan (Contact Author)

Rice University - Jones Graduate School of Business ( email )

6100 South Main Street
P.O. Box 1892
Houston, TX 77005-1892
United States

Eric Bradlow

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States
215-898-8255 (Phone)

Peter Fader

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

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