Winning your customers’ minds and hearts: Disentangling the effects of lock-in and affective customer experience on retention

Lily (Xuehui) Gao (), Evert Haan (), Iguácel Melero-Polo () and F. Javier Sese ()
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Lily (Xuehui) Gao: University of Zaragoza
Evert Haan: University of Groningen
Iguácel Melero-Polo: University of Zaragoza
F. Javier Sese: University of Zaragoza

Journal of the Academy of Marketing Science, 2023, vol. 51, issue 2, No 5, 334-371

Abstract: Abstract Building barriers to lock in customers and improving the affective customer experience are two key strategies employed by firms to enhance customer retention. Although pursuing the same goal, these strategies work differently: the former relies more on a calculative, cost–benefit approach to the exchange, while the latter promotes affective aspects of the relationship. Integrating experiential learning theory with social exchange theory, we provide a conceptual framework to understand the impact of lock-in and affective customer experience on customer retention, and the moderating role of relationship depth. Using a comprehensive data set for a sample of 13,761 customers covering all firms in one telecom market for two different services, we empirically test the framework via multinomial logit modeling. The results offer novel insights into the interplay between the two strategies. For poor affective customer experience (i.e., a score below five on a 0–10 scale), lock-in helps firms reduce customer churn (between 49.03% and 47.86%). However, the impact of lock-in decreases when affective customer experience improves and turns to be insignificant once the experience reaches the “acceptable level” (i.e., a score above seven on a 0–10 scale). Importantly, the separate and joint effects of the two strategies are stronger when there is a low relationship depth, and weaker when heavy relationships are established. The findings offer useful practical advice to manage these strategies in an efficient and optimal way.

Keywords: Customer retention; Lock-in; Affective customer experience; Spillover effect; Multinomial logit models; Telecom industry (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11747-022-00898-z

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