A Study of Applying SVR on Customer Attrition Forecasting-The case of medical cosmetology

• Main Authors: Wu,Chaolin, 吳昭霖
• Other Authors: FANG TSOU, CHAO-TSONG
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/28107812988793042586

碩士 === 國立臺北大學 === 資訊管理研究所 === 100 === Customer Relationship Management (CRM) is a very active research area for decades, and has accumulated voluminous literature. For many organizations, it would be very difficult to analyze precisely all the customer attrition, especially in medical cosmetology in Taiwan. We, therefore, utilized several kinds of transaction information which are frequently used in evaluating customer value as our variables. These variables are RFM, Customer Trend Value and demographic variables. To combine the measurement of demographics with the psychological insights of psychographics, we use astrology as a variable for segmentation purposes. The main objective of this study is intended to use all the variables to establish a Support Vector Regression (SVR) model and tries to provide some suggestions to the medical cosmetology industry. Recently, SVR has been used to solve regression and prediction problems. In this study, we apply the SVR to customer attrition forecasting. In particular, the transaction data are usually complex. To ensure all the transaction date are correct, we use SQL command to check all the data prudently so the risk of incorrectly calculating the SVR model is greatly reduced. Our experimental results show that astrology variables have a significant impact on attitude toward cosmetic product if there is no financial risk. Finally, we can conclude that the customer attrition model based on SVR obtains a good balance among fitting ability, generalization ability and model stability by the Mean Square Error (MSE) test and discussion with experts.