Abstract
This case study applies RFM model and K-means method in the value analysis of the customer database of an outfitter in Taipei, Taiwan. By considering gender, birth date, shopping frequency, and the total spending, six clusters have been found among 675 member customers from the company's database. In addition to the clustering analysis, different promotion strategies for the members of different clusters are provided. The analyses show that Clusters 5 and 6 are the two most important groups that the company has to devote resources into. Moreover, the company might ration resources for the customers in Clusters 1 and 2 because they do not contribute enough values to the outfitter.
| Original language | English |
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| Title of host publication | Global Perspective for Competitive Enterprise, Economy and Ecology - Proceedings of the 16th ISPE International Conference on Concurrent Engineering |
| Pages | 665-672 |
| Number of pages | 8 |
| Publication status | Published - 2009 Dec 1 |
| Event | 16th ISPE International Conference on Concurrent Engineering, CE 2009 - Taipei, Taiwan Duration: 2009 Jul 20 → 2009 Jul 24 |
Publication series
| Name | Global Perspective for Competitive Enterprise, Economy and Ecology - Proceedings of the 16th ISPE International Conference on Concurrent Engineering |
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Other
| Other | 16th ISPE International Conference on Concurrent Engineering, CE 2009 |
|---|---|
| Country | Taiwan |
| City | Taipei |
| Period | 09-07-20 → 09-07-24 |
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All Science Journal Classification (ASJC) codes
- Software
Cite this
Wu, H-H., Chang, E. C., & Lo, C. F. (2009). Applying RFM model and K-means method in customer value analysis of an outfitter. In Global Perspective for Competitive Enterprise, Economy and Ecology - Proceedings of the 16th ISPE International Conference on Concurrent Engineering (pp. 665-672). (Global Perspective for Competitive Enterprise, Economy and Ecology - Proceedings of the 16th ISPE International Conference on Concurrent Engineering).