Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 40, Issue 18, Pages 7513-7518Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2013.07.053
Keywords
Customer relationship management; Marketing strategies; Hairdressing; Data mining; RFM model
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Funding
- National Science Council in Taiwan, R.O.C. [NSC 99-2221-E-018-012-MY2]
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With the increase of living standards and the sustainable changing patterns of people's lives, nowadays, hairdressing services have been widely used by people. This paper adopts data mining techniques by combining self-organizing maps (SOM) and K-means methods to apply in RFM (recency, frequency, and monetary) model for a hair salon in Taiwan to segment customers and develop marketing strategies. The data mining techniques help identify four types of customers in this case, including loyal customers, potential customers, new customers and lost customers and develop unique marketing strategies for the four types of customers. (C) 2013 Elsevier Ltd. All rights reserved.
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