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The impact of personalised incentives on the profitability of customer retention campaigns

Tamaddoni Jahromi, Ali, Stakhovych, S and Ewing, Michael 2017, The impact of personalised incentives on the profitability of customer retention campaigns, Journal of marketing management, vol. 33, no. 5, pp. 1-22, doi: 10.1080/0267257X.2017.1295094.

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Title The impact of personalised incentives on the profitability of customer retention campaigns
Author(s) Tamaddoni Jahromi, AliORCID iD for Tamaddoni Jahromi, Ali
Stakhovych, S
Ewing, MichaelORCID iD for Ewing, Michael
Journal name Journal of marketing management
Volume number 33
Issue number 5
Start page 1
End page 22
Total pages 22
Publisher Taylor & Francis
Place of publication Abingdon, Eng.
Publication date 2017-03-06
ISSN 0267-257X
Keyword(s) customer churn management
customer retention
incentive redemption
data mining
profitability frameworks
Summary Traditional approaches to managing customer churn have typically concentrated on those customers most likely to defect. While accurately predicting customer churn probability is important, this metric alone does not sufficiently empower managers to make optimal decisions. Hence, the current study focuses on the relationship between retention incentives and profit maximisation. Specifically, we improve existing churn management practices by: (1) allowing for customer heterogeneity in incentive redemption behaviour, (2) introducing the dependence of the probability of accepting an incentive on its monetary value, and (3) offering an improved model for developing retention campaigns. We support our conclusions with empirical data and simulations and make tangible managerial recommendations.
Language eng
DOI 10.1080/0267257X.2017.1295094
Field of Research 1505 Marketing
1504 Commercial Services
1503 Business And Management
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2017, Westburn Publishers
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Document type: Journal Article
Collection: Department of Information Systems and Business Analytics
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