A case study of applying spectral clustering technique in the value analysis of an outfitter's customer database

En Chi Chang, Shian-Chang Huang, Hsin-Hung Wu, Chiao Fang Lo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This case study applies the spectral clustering technique in the value analysis of the customer database of an outfitter in Taipei, Taiwan. By considering gender, birth date, zip code, shopping frequency, and the total spending, the spectral clustering analysis found six clusters among 551 member customers from the company's database. In addition to the clustering analysis, different promotion strategies based on two recency-frequency-monetary based loyalty strategies matrices for the members of different clusters are provided. The analysis shows that Clusters 5 and 3 are the two most important groups and one group of customers may have to be abandoned to save the company's marketing resources.

Original languageEnglish
Title of host publicationIEEM 2007
Subtitle of host publication2007 IEEE International Conference on Industrial Engineering and Engineering Management
Pages1743-1746
Number of pages4
DOIs
Publication statusPublished - 2007 Dec 1
Event2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007 - , Singapore
Duration: 2007 Dec 22007 Dec 4

Publication series

NameIEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management

Other

Other2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007
CountrySingapore
Period07-12-0207-12-04

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All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Industrial and Manufacturing Engineering

Cite this

Chang, E. C., Huang, S-C., Wu, H-H., & Lo, C. F. (2007). A case study of applying spectral clustering technique in the value analysis of an outfitter's customer database. In IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1743-1746). [4419491] (IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management). https://doi.org/10.1109/IEEM.2007.4419491