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

Tamaddoni, Ali, Stakhovych, Stanislav and Ewing, Michael 2017, The impact of personalised incentives on the profitability of customer retention campaigns, Journal of marketing management, pp. 1-21, 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, Ali
Stakhovych, Stanislav
Ewing, Michael
Journal name Journal of marketing management
Start page 1
End page 21
Total pages 21
Publisher Taylor & Francis
Place of publication Abingdon, Eng.
Publication date 2017-03-06
ISSN 0267-257X
1472-1376
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.
Notes In Press
Language eng
DOI 10.1080/0267257X.2017.1295094
Field of Research 1505 Marketing
1504 Commercial Services
1503 Business And Management
Socio Economic Objective 0 Not Applicable
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2017, Westburn Publishers
Persistent URL http://hdl.handle.net/10536/DRO/DU:30091994

Document type: Journal Article
Collection: Department of Information Systems and Business Analytics
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