Applying Data Mining Technique in Customer Relationship Management: Taking G Chain Optical Company as an Example

• Main Authors: Tsai,Chung-Cheng, 蔡忠政
• Other Authors: Pai, Fan-Yun
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/9h2c9s

碩士 === 國立彰化師範大學 === 企業管理學系 國際企業經營管理(IMBA) === 104 === Myopia, hyperopia, and presbyopia glasses belong to a professional necessity not a general consumption commodity. The development of medical science and technology and improvement of the material of lens and frames increases the durability of glasses that significantly change the glasses consumption patterns, which result in lower customer retention rate. Due to the popularity of disposal contact lenses, the market of the traditional contact lenses has become more competitive. With the above reasons, this study intends to analyze consumers’ behaviors through data mining by dividing those consumers into different customer groups and then discuss strategies to enhance customer retention rate. This study uses G chain optical company as example by converting and analyzing the three-year transactions data from this case company through self-organizing map and K-means method based on RFM model. Customers can be divided into 12 groups. By incorporating the philosophies from Ha and Park and customer value matrix by Marcus, four kinds of customer types are identified including the best and loyal customers with 11.9% (R, F, and M are above the average values), the best but lost customers with 0.1% (R is below the average but F and M are above the averages), uncertain and new customers with 32.6% (R is above the average but F and M are below the averages), and uncertain but lost customers with 55.4% (R, F, and M are below the averages). The best and loyal customers and best but lost customers yield 12.0% in this G chain optical company, while the uncertain and new customers and uncertain but lost customers are 88.0%, indicating that there is a room to improve business operations. A top priority is to reduce the proportion of uncertain customers by the following marketing strategies: increasing the needed commodities by the customers, providing the discounts for the customers to improve and meet their spending habits, and informing new products information to customers.