A decision‐making support system module for customer segmentation and ranking. Issue 2 (19th October 2022)

• Record Type: Journal Article
• Authors: Hadad, Yossi; Keren, Baruch
• Other Names: Yu Hui guestEditor.
• Is Part Of: Expert systems. Volume 40:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-10-19
• Subjects: customer portfolio management -- customer segmentation -- data envelopment analysis -- decision‐making support system -- expert system -- ranking methods; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.13169
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: Many businesses have their own method of segmentation and of customer evaluation to help them give the appropriate managerial attention to each segment and each customer. This paper proposes a more refined and objective decision‐making support system module that allows segmentation and full ranking of customers. It offers several improvements and advantages over the state‐of‐the‐art methods. The module is based on customer criteria with quantitative values that can be extracted from the organizational information system. Customer scores are calculated objectively on the basis of measurable criteria without the need for human evaluation. The module determines the relative location of each customer within that customer's segment (for example, Platinum, Gold, Silver, and Bronze), tracks changes that occur over time, and enables a full and precise ranking of the customers according to company‐defined criteria. The module can be computerized and results can be generated quickly at any time, using up‐to‐date data. The module's design was based on feedback from a survey conducted among 39 managers and its applicability was successfully demonstrated in a real‐world case study. The decision‐makers in the organization where the case study was conducted stated that they would apply the proposed method quarterly (four times a year) instead of once a year. It was also found that the proposed method saves about 90% of the time and resources required to prepare a customer portfolio management and customer ranking compared to the subjective method that was used.