Optimal threshold analysis of segmentation methods for identifying target customers

Makoto Mizuno, Akira Saji, Ushio Sumita, Hideo Suzuki

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


In CRM (Customer Relationship Management), the importance of a segmentation method for identifying good customers has been increasing. For evaluation of different segmentation methods, Accuracy often plays a key role. This indicator, however, cannot distinguish two types of errors. The purpose of this paper is to overcome this pitfall by introducing two different indicators: Recall and Precision. Assuming that a promotion is addressed exclusively to the selected target customers, the financial effectiveness of the underlying segmentation method is expressed as a function of Recall and Precision. An optimization problem is then formulated so as to maximize the financial measure by finding the optimal threshold level in terms of the severeness for estimating the target set. By introducing a functional form which represents correctness and mistakes about the target set, the unique optimal solution is derived explicitly. The proposed approach is validated by using real customer purchase data.

Original languageEnglish
Pages (from-to)358-379
Number of pages22
JournalEuropean Journal of Operational Research
Issue number1
Publication statusPublished - 2008 Apr 1
Externally publishedYes


  • Cost benefit analysis
  • Identifying target customers
  • Marketing
  • Optimal threshold level
  • Segmentation method

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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