Ascarza’s “Retention Futility: Targeting High-Risk Customers Might be Ineffective,” Wins 2018 Award

Eva Ascarza has been selected as the recipient of the 2018 Paul E. Green Award for her article “Retention Futility: Targeting High-Risk Customers Might be Ineffective,” which appeared in the February 2018 issue of the Journal of Marketing Research. This award recognizes the article published in the Journal of Marketing Research during 2018 that demonstrates the greatest potential contribution to the practice of marketing research and research in marketing. The Green Award committee this year includes Tulin Erdem (New York University), Rebecca Hamilton (Georgetown University) and Joel Huber (Duke University). The committee provided the following statement about their choice of Ascarza’s paper for the Green Award:

In her paper, “Retention Futility: Targeting High-Risk Customers Might be Ineffective,” Ascarza questions the assumption made by researchers and practitioners that targeting current customers with the highest risk of defection with retention interventions provides the most effective way to reduce customer churn. Ascarza argues that the degree to which customers will respond favorably to retention efforts (known as “lift”) is a better metric to identify customers to target with retention campaigns.

Ascarza models the effects of targeting customers based on both “lift,” the probability that retention efforts will be successful, and “risk,” the probability that a customer will defect. Based on field data from a wireless services provider and a membership organization, she compares the effects of targeting based on lift and targeting based on risk of defection. Simulations using both datasets show that targeting customers for retention interventions based on lift more effectively reduces churn than targeting them based on risk of defection.

In addition to integrating literature on customer retention with literature on customer heterogeneity in response to targeting, this paper demonstrates a new approach for leveraging A/B tests to improve targeting. Not only has the paper gained traction among an academic audience, it has also become part of the teaching curriculum in several business schools and has been presented in practitioner workshops at Google and MSI.

Four finalists were considered by the Green Award committee. The committee was particularly impressed by the innovation and methodological rigor each of the finalists used to address important market problems. These are summarized below.

• Kusum L. Ailawadi, Yu Ma, and Dhruv Grewal for their paper, “The Club Store Effect: Impact of Shopping in Warehouse Club Stores on Consumers’ Packaged Food Purchases,” published in the April 2018 issue of the Journal of Marketing Research. The committee appreciated this paper’s rich analysis of purchases by households who shop vs. those who do not shop at club stores. The analysis is motivated by theoretical predictors of both store selection and product selection decisions, and its results provide important insights for policy makers, consumers and managers.
• Daniel M. McCarthy and Peter S. Fader for their paper, “Customer-Based Corporate Valuation for Publicly Traded Noncontractual Firms,” published in the October 2018 issue of the Journal of Marketing Research. The committee appreciated this paper’s guidance for computing customer-based firm valuation for firms that do not have formal contracts with their customers, making it difficult to detect when a customer relationship has ended. They were also impressed that the model can be estimated using publicly available data, increasing the usefulness of this approach for decision makers outside of these firms.  
• Courtney Paulson, Lan Luo, and Gareth M. James for their paper, “Efficient Large-Scale Internet Media Selection Optimization for Online Display Advertising,” published in the August 2018 issue of the Journal of Marketing Research. The committee appreciated this paper’s very timely development of a non-proprietary algorithm to allocate a firm’s advertising budget across multiple websites. Notably, their algorithm controls for overlap in viewership across websites, which increases efficiency by helping firms avoid overpaying to reach the same customers via multiple websites.

Learn more about the Green Award, previous recipients, and how to support the award via the AMA Foundation.