A Study on Applying Data Mining Tools to Customer Value Evaluating and Marketing

• Main Authors: Li-ting Lin, 林莉婷
• Other Authors: none
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/24168504721065960528

碩士 === 世新大學 === 資訊傳播學研究所(含碩專班) === 99 === Based on the rapid development of global information technology, E-commerce becomes a needed business mode for each company. As the Internet with instantaneity, interactive, the low cost, no time, non-geographical restrictions, buyers can shop anytime and anywhere by using the Internet. Therefore, for the companies, the marketing method through the Internet has getting more and more imperative. In this thesis, a domestic online shopping site was selected as a research target. The result of this study provides an appropriated marketing strategy by mining data with actual transaction data, and by forecasting and database with transaction records. The study analyzes the customer value with the recency, frequency and monetary of these recent shopping experiences. Furthermore, the research applies the decision tree clustering to understand the relevance of the groups and the attributes by separating customers through the rfm method. Using customer valuation analysis to segment the customers into four groups which including “high value”, “high potential”, “high growth” and “uncertain”, to enable enterprises to invest resources to specific target customers and help reduce costs and increase profitability. According to the above results, this study will help companies better understand the customers. Then the company could make appropriate marketing strategies for different values of the customer, in order to improve the business profitability.