A matheuristic for a customer assignment problem in direct marketing

Bigler, T; Kammermann, M; Baumann, P (2023). A matheuristic for a customer assignment problem in direct marketing. European journal of operational research, 304(2), pp. 689-708. Elsevier 10.1016/j.ejor.2022.04.009

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In direct marketing, companies use sales campaigns to target their customers with personalized product offers. The effectiveness of direct marketing greatly depends on the assignment of customers to campaigns. In this paper, we consider a real-world planning problem of a major telecommunications company that assigns its customers to individual activities of its direct marketing campaigns. Various side constraints, such as budgets and sales targets, must be met. Conflict constraints ensure that individual customers are not assigned too frequently to similar activities. Related problems have been addressed in the literature; however, none of the existing approaches cover all the side constraints considered here. To close this gap, we develop a matheuristic that employs a new decomposition strategy to cope with the large number of conflict constraints in typical problem instances. In a computational experiment, we compare the performance of the proposed matheuristic to the performance of two mixed-binary linear programs on a test set that includes large-scale real-world instances. The matheuristic derives near-optimal solutions in short running times for small- to medium-sized instances and scales to instances of practical size comprising millions of customers and hundreds of activities. The deployment of the matheuristic at the company has considerably increased the overall effectiveness of its direct marketing campaigns.

Item Type:

Journal Article (Original Article)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Financial Management
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Financial Management > Professorship for Quantitative Methods in Business Administration

UniBE Contributor:

Bigler, Tamara, Kammermann, Manuel Stanley, Baumann, Philipp

Subjects:

600 Technology > 650 Management & public relations

ISSN:

0377-2217

Publisher:

Elsevier

Language:

English

Submitter:

Philipp Baumann

Date Deposited:

06 Sep 2022 10:23

Last Modified:

05 Dec 2022 16:23

Publisher DOI:

10.1016/j.ejor.2022.04.009

BORIS DOI:

10.48350/172497

URI:

https://boris.unibe.ch/id/eprint/172497

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