A Study of Using Data Mining Techniques on Customer Value Analysis-A Case Study of Freight Forwarders Company

• Main Authors: Ying Jie Chen, 陳瑩潔
• Other Authors: S. W. Lin
• Format: Others
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/07324595302108383040

碩士 === 長庚大學 === 資訊管理學系 === 99 === The trend of globalization in economical environment in recent years has caused vigorous competitions for various industries and business. Owing to its geographical advantages in logistics, Taiwan counts on international trading as its important source of economical income. As the oil price continues to raise, and the global economical crisis caused by financial tsunami in 2008, the global economical environment is becoming more and more challenging everyday. To survive from this strict environment, and thus tend existing customer instead of losing them, enterprises need to count on CRM (Customer Relationship Management) to increase their competence and the loyalty of their customers. This study takes ocean freight forwarder as research object, obtains transaction data during some period of time, calculates MLE (Maximum Likelihood Estimation), WMLE (Weighted Maximum Likelihood Estimation) based on RFM model, combines the results of the experiments of K-Means algorithm, and divides customer clusters into four groups. Effective marketing suggestions that specifies each group are provided. This study then extracts the classification rules using C4.5 algorithm to obtain current consuming trait of customers by analysing rules. If the loss is going to happen, prevention actions can be taken. In short, the analysis results of this thesis can provide enterprises with marketing strategies and suggestions toward various groups of customers.