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

doi:10.1109/IEEM.2007.4419491

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

MSM Marketing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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. © 2007 IEEE.

Original language	English
Title of host publication	IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management\|IEEM IEEE Int. Conf. Ind. Eng. Eng. Manage.
Place of Publication	Singapore
Pages	1743-1746
Number of pages	3
DOIs	https://doi.org/10.1109/IEEM.2007.4419491
Publication status	Published - 2007
Event	2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007 - Duration: 1 Jul 2007 → …

Conference

Conference	2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007
Period	1/07/07 → …

Keywords

Customer value analysis
Promotion strategy
Spectral clustering technique

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10.1109/IEEM.2007.4419491

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|IEEM IEEE Int. Conf. Ind. Eng. Eng. Manage. (pp. 1743-1746). https://doi.org/10.1109/IEEM.2007.4419491

@inproceedings{38b08adb8c52419baa1289290056f2fa,

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

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. {\textcopyright} 2007 IEEE.",

keywords = "Customer value analysis, Promotion strategy, Spectral clustering technique",

author = "Chang, {En Chi} and Huang, {Shian Chang} and Wu, {Hsin Hung} and Lo, {Chiao Fang}",

year = "2007",

doi = "10.1109/IEEM.2007.4419491",

language = "English",

isbn = "1424415292",

pages = "1743--1746",

booktitle = "IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management|IEEM IEEE Int. Conf. Ind. Eng. Eng. Manage.",

note = "2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007 ; Conference date: 01-07-2007",

}

Chang, EC, Huang, SC, Wu, HH & Lo, CF 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|IEEM IEEE Int. Conf. Ind. Eng. Eng. Manage.. Singapore, pp. 1743-1746, 2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007, 1/07/07. https://doi.org/10.1109/IEEM.2007.4419491

A case study of applying spectral clustering technique in the value analysis of an outfitter's customer database. / Chang, En Chi; Huang, Shian Chang; Wu, Hsin Hung et al.
IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management|IEEM IEEE Int. Conf. Ind. Eng. Eng. Manage.. Singapore, 2007. p. 1743-1746.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A case study of applying spectral clustering technique in the value analysis of an outfitter's customer database

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AU - Wu, Hsin Hung

AU - Lo, Chiao Fang

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N2 - 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. © 2007 IEEE.

AB - 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. © 2007 IEEE.

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KW - Promotion strategy

KW - Spectral clustering technique

U2 - 10.1109/IEEM.2007.4419491

DO - 10.1109/IEEM.2007.4419491

M3 - Conference contribution

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SN - 9781424415298

SP - 1743

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BT - IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management|IEEM IEEE Int. Conf. Ind. Eng. Eng. Manage.

CY - Singapore

T2 - 2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007

Y2 - 1 July 2007

ER -

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

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