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Profit-based model selection for customer retention using individual customer lifetime values

Profit-based model selection for customer retention using individual customer lifetime values
Profit-based model selection for customer retention using individual customer lifetime values

The goal of customer retention campaigns, by design, is to add value and enhance the operational efficiency of businesses. For organizations that strive to retain their customers in saturated, and sometimes fast moving, markets such as the telecommunication and banking industries, implementing customer churn prediction models that perform well and in accordance with the business goals is vital. The expected maximum profit (EMP) measure is tailored toward this problem by taking into account the costs and benefits of a retention campaign and estimating its worth for the organization. Unfortunately, the measure assumes fixed and equal customer lifetime value (CLV) for all customers, which has been shown to not correspond well with reality. In this article, we extend the EMP measure to take into account the variability in the lifetime values of customers, thereby basing it on individual characteristics. We demonstrate how to incorporate the heterogeneity of CLVs when CLVs are known, when their prior distribution is known, and when neither is known. By taking into account individual CLVs, our proposed approach of measuring model performance gives novel insights when deciding on a customer retention campaign. The method is dependent on the characteristics of the customer base as is compliant with modern business analytics and accommodates the data-driven culture that has manifested itself within organizations.

churn prediction, customer lifetime value, maximum profit measure, model evaluation
2167-6461
53-65
Óskarsdóttir, María
1622b6dd-5d25-4228-9418-a1729e9577e0
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d
Óskarsdóttir, María
1622b6dd-5d25-4228-9418-a1729e9577e0
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d

Óskarsdóttir, María, Baesens, Bart and Vanthienen, Jan (2018) Profit-based model selection for customer retention using individual customer lifetime values. Big Data, 6 (1), 53-65. (doi:10.1089/big.2018.0015).

Record type: Article

Abstract

The goal of customer retention campaigns, by design, is to add value and enhance the operational efficiency of businesses. For organizations that strive to retain their customers in saturated, and sometimes fast moving, markets such as the telecommunication and banking industries, implementing customer churn prediction models that perform well and in accordance with the business goals is vital. The expected maximum profit (EMP) measure is tailored toward this problem by taking into account the costs and benefits of a retention campaign and estimating its worth for the organization. Unfortunately, the measure assumes fixed and equal customer lifetime value (CLV) for all customers, which has been shown to not correspond well with reality. In this article, we extend the EMP measure to take into account the variability in the lifetime values of customers, thereby basing it on individual characteristics. We demonstrate how to incorporate the heterogeneity of CLVs when CLVs are known, when their prior distribution is known, and when neither is known. By taking into account individual CLVs, our proposed approach of measuring model performance gives novel insights when deciding on a customer retention campaign. The method is dependent on the characteristics of the customer base as is compliant with modern business analytics and accommodates the data-driven culture that has manifested itself within organizations.

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Profit based model selection for customer retention using individual customer lifetime values - Accepted Manuscript
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Accepted/In Press date: 1 March 2018
e-pub ahead of print date: 1 March 2018
Keywords: churn prediction, customer lifetime value, maximum profit measure, model evaluation

Identifiers

Local EPrints ID: 421340
URI: http://eprints.soton.ac.uk/id/eprint/421340
ISSN: 2167-6461
PURE UUID: d8cbc11a-9551-4026-8265-fa8df3438743
ORCID for Bart Baesens: ORCID iD orcid.org/0000-0002-5831-5668

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Date deposited: 01 Jun 2018 16:31
Last modified: 07 Oct 2020 06:37

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