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An approach to optimised customer segmentation and profiling using RFM, LTV, and demographic features

Version 2 2024-06-02, 13:39
Version 1 2017-07-07, 10:01
journal contribution
posted on 2024-06-02, 13:39 authored by MM Namvar, SK Khakabimamaghani, MRG Gholamian
Customer segmentation and profiling are increasingly significant issues in today's competitive commercial area. Many studies have reviewed the application of data mining technology in customer segmentation, and achieved sound effectives. But in the most cases, it is performed using customer data from especial point of view, rather than from systematical method considering all stages of CRM. This paper constructs a new customer segmentation method based on RFM, LTV, and demographic parameters with the aid of data mining tools. In this method, first different combinations of RFM and demographic variables are used for clustering. Second, using LTV, the best clustering is chosen. Finally, to build customer profiles each segment is compared to other segments regarding different features. The method has been applied to a dataset from a food chain stores and resulted in some useful management measures and suggestions.

History

Journal

International Journal of Electronic Customer Relationship Management

Volume

5

Pagination

220-235

Location

Olney, Eng.

ISSN

1750-0664

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal, C Journal article

Copyright notice

2011, Inderscience Enterprises

Issue

3/4

Publisher

Inderscience Publishers