A matheuristic for a customer assignment problem in direct marketing

Abstract

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.