Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
383601 | Expert Systems with Applications | 2013 | 6 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jo-Ting Wei, Ming-Chun Lee, Hsuan-Kai Chen, Hsin-Hung Wu,