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Customer comeback: Empirical insights into the drivers and value of returning customers

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  • Meire, Matthijs

Abstract

Customer comeback, or the return of previous customers to the company without receiving a win-back offer, has received little academic attention. By tapping into a rich transactional database enhanced with social media data, we argue that a multitude of touch points after defection (such as social media) can accurately inform managers about customers for whom win-back offers may not be relevant. Econometric analysis reveals positive links of Facebook likes and event attendances after defection with customer comeback, next to a significant concave relationship of first-lifetime behavior. From a predictive point of view, touch points after defection are more informative than first-lifetime behavior. Finally, comeback customers spend, on average, more than newly acquired customers, and lower-profile comeback customers reduce their spending with the firm upon return. Based on our multimethod analysis, we demonstrate the value of comeback analyses and derive several actionable insights and recommendations for both theory and practice.

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  • Meire, Matthijs, 2021. "Customer comeback: Empirical insights into the drivers and value of returning customers," Journal of Business Research, Elsevier, vol. 127(C), pages 193-205.
    • Handle: RePEc:eee:jbrese:v:127:y:2021:i:c:p:193-205
    DOI: 10.1016/j.jbusres.2021.01.017
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    1. Chee Sun Lee & Peck Yeng Sharon Cheang & Massoud Moslehpour, 2022. "Predictive Analytics in Business Analytics: Decision Tree," Advances in Decision Sciences, Asia University, Taiwan, vol. 26(1), pages 1-30, March.

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