Customer relationship management in the hairdressing industry: An application of data mining techniques

Jo Ting Wei, Ming Chun Lee, Hsuan Kai Chen, Hsin Hung Wu

研究成果: Article

52 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)7513-7518
頁數6
期刊Expert Systems with Applications
40
發行號18
DOIs
出版狀態Published - 2013 八月 14

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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