A Study on the Customer Segmentation and Personalized Recommendation Systems

• Main Authors: Hsiao-Hsuan Hsu, 胥孝萱
• Other Authors: Huan-Ming Chuang
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/49525829815076619901

碩士 === 雲林科技大學 === 資訊管理系碩士班 === 98 === The business market compared to the consumer market has the characteristics of smaller number of customers with huge amount of transaction money. Consequently, it is important for suppliers to implement the concept of relationship marketing, to offer their customers valuable customized services through effective customer segmentation and personalized recommendation systems. At the same time, to make most of their limited resources. In this study, customer lifetime value (CLV) is evaluated in terms of RFM variables. The K-means algorithm then is applied to segment customers by their CLVs. Further, the concept of product taxonomy is applied to associate rule mining and Collaborative Filter to enhance their effectiveness. Research results will provide business markets helpful guidance regarding build and maintain beneficial long-term mutual relationships with their valuable customers.