A Cross-Cohort Changepoint Model for Customer-Base Analysis

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 cu...

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Bibliographic Details
Published in:Marketing science (Providence, R.I.) R.I.), 2017-03, Vol.36 (2), p.195-213
Main Authors: Gopalakrishnan, Arun, Bradlow, Eric T., Fader, Peter S.
Format: Article
Language:English
Subjects:
Bayesian analysis
Bias
changepoint
Cohort analysis
cross-cohort
customer lifetime value
customer-base analysis
Customers
Donations
forecasting
hierarchical Bayesian
Marketing
Nonprofit organizations
reversible-jump MCMC
Studies
Uncertainty
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Summary: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 multicohort donation data from a nonprofit 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.
ISSN:0732-2399
1526-548X
DOI:10.1287/mksc.2016.1007