Overcoming the Cold Start Problem of Customer Relationship Management using a Probabilistic Machine Learning Approach

Journal of Marketing Research, 58(5), 981–1006. https://doi.org/10.1177/00222437211032938

Posted: 17 Mar 2017 Last revised: 31 Dec 2021

See all articles by Nicolas Padilla

Nicolas Padilla

London Business School - Department of Marketing

Eva Ascarza

Harvard Business School

Date Written: July 7, 2021

Abstract

The success of customer relationship management programs ultimately depends on the firm's ability to identify and leverage differences across customers—a difficult task when firms attempt to manage new customers, for whom only the first purchase has been observed. The lack of repeated observations for these customers poses a structural challenge for firms to infer unobserved differences across them. This is what the authors call the “cold start” problem of customer relationship management, whereby companies have difficulties leveraging existing data when they attempt to make inferences about customers at the beginning of their relationship. The authors propose a solution to the cold start problem by developing a probabilistic machine learning modeling framework that leverages the information collected at the moment of acquisition. The main aspect of the model is that it flexibly captures latent dimensions that govern the behaviors observed at acquisition as well as future propensities to buy and to respond to marketing actions using deep exponential families. The model can be integrated with a variety of demand specifications and is flexible enough to capture a wide range of heterogeneity structures. The authors validate their approach in a retail context and empirically demonstrate the model's ability to identify high-value customers as well as those most sensitive to marketing actions right after their first purchase.

Keywords: Customer Relationship Management (CRM), Deep Exponential Families, Probabilistic Machine Learning, Cold Start Problem.

Suggested Citation

Padilla, Nicolas and Ascarza, Eva, Overcoming the Cold Start Problem of Customer Relationship Management using a Probabilistic Machine Learning Approach (July 7, 2021). Journal of Marketing Research, 58(5), 981–1006. https://doi.org/10.1177/00222437211032938, Available at SSRN: https://ssrn.com/abstract=2933291 or http://dx.doi.org/10.2139/ssrn.2933291

Nicolas Padilla (Contact Author)

London Business School - Department of Marketing ( email )

Sussex Place
Regent's Park
London, NW1 4SA
United Kingdom

HOME PAGE: http://www.nicolaspadilla.com

Eva Ascarza

Harvard Business School ( email )

Soldiers Field
Boston, MA 02163
United States

HOME PAGE: http://evaascarza.com

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