Maximizing customers' lifetime value using limited marketing resources

Mage Marmol*, Anita Goyal, Pedro Jesus Copado-Mendez, Javier Panadero, Angel A. Juan

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

Purpose: For any given customer, his/her profitability for a business enterprise can be estimated by the so-called customer lifetime value (CLV). One specific goal for many enterprises consists in maximizing the aggregated CLV associated with its set of customers. To achieve this goal, a company uses marketing resources (e.g. marketing campaigns), which are usually expensive. Design/methodology/approach: This paper proposes a formal model of the Customer Life Value problem inspired by the uncapacitated facility location problem. Findings: The computational experiments conducted by the authors illustrate the potential of the approach when compared with a standard (non-algorithm-supported) one. Originality/value: The approach leads up to the economic trade-off between the volume of the employed resources and the aggregated CLV, i.e. the higher the number of resources utilized, but also the higher the cost of achieving this level of lifetime value. Hence, the number of resources to be “activated” has to be decided, and the effect of each of these resources on each CLV will depend upon how “close” the resource is from the corresponding customer (i.e. how large will the impact of the active resource on the customer).

Original languageEnglish
Pages (from-to)1058-1072
Number of pages15
JournalMarketing Intelligence and Planning
Volume39
Issue number8
DOIs
Publication statusPublished - 25 Oct 2021

Keywords

  • Artificial intelligence
  • Biased-randomized algorithms
  • Customer lifetime
  • Customer loyalty
  • Marketing intelligence

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