Customer relationship management in the hairdressing industry: An application of data mining techniques |
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| Authors: | Jo-Ting Wei Ming-Chun Lee Hsuan-Kai Chen Hsin-Hung Wu |
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| Affiliation: | 1. Department of Business Administration, National Changhua University of Education, Changhua, Taiwan, ROC;2. Department of Business Administration, National Changhua University of Education, Changhua, Taiwan, ROC;3. Department of Culture-Based Creative Design, National Taitung College, Taiwan, ROC;4. Department of Business Administration, National Changhua University of Education, No. 2 Shida Road, Changhua City 500, Taiwan, ROC |
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| Abstract: | ![]()
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. |
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| Keywords: | Customer relationship management Marketing strategies Hairdressing Data mining RFM model |
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