Managing Churn to Maximize Profits

Marketing Science, Forthcoming

56 Pages Posted: 9 May 2017 Last revised: 7 Jan 2020

See all articles by Aurelie Lemmens

Aurelie Lemmens

Rotterdam School of Management, Erasmus University Rotterdam

Sunil Gupta

Harvard University - Business School (HBS)

Date Written: January 1, 2020

Abstract

Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability, or their responsiveness to a retention offer. However, both approaches ignore that some customers contribute more to the profitability of retention campaigns than others. This study addresses this problem by defining a profit-based loss function to predict, for each customer, the financial impact of a retention intervention. This profit-based loss function aligns the objective of the estimation algorithm with the managerial goal of maximizing the campaign profit. It ensures (1) that customers are ranked based on the incremental impact of the intervention on churn and post-campaign cash flows, after accounting for the cost of the intervention and (2) that the model minimizes the cost of prediction errors by penalizing customers based on their expected profit lift. Finally, it provides a method to optimize the size of the retention campaign. Two field experiments affirm that our approach leads to significantly more profitable campaigns than competing models.

Keywords: Defection, Field Experiments, Loss Function, Machine Learning, Proactive Churn Management, Profit Lift, Stochastic Gradient Boosting

Suggested Citation

Lemmens, Aurélie and Gupta, Sunil, Managing Churn to Maximize Profits (January 1, 2020). Marketing Science, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2964906 or http://dx.doi.org/10.2139/ssrn.2964906

Aurélie Lemmens (Contact Author)

Rotterdam School of Management, Erasmus University Rotterdam ( email )

3000 DR Rotterdam
Netherlands

Sunil Gupta

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Morgan 270C
Boston, MA 02163
United States

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