Discover Consumers Patterns Using Data Mining in Mobile Telecommunication Market

• Main Authors: Chen-Wei-Pai, 白宸瑋
• Other Authors: Wen-Chen-Chu
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/eqm2p9

碩士 === 長榮大學 === 企業管理學系碩士班 === 98 === Clustering analysis is a common method for marketing segmentation, including multivariate analysis and artifical neural network. This study aims to compare four clustering methods︰(1)intergration of SOM(Self-Organization-Map) with K-means, (2)the SOM, (3)the Ward’s, (4) the two-stage . Select the best two of them to combine with decision trees and association rule for applying in the 3G mobile (The 3rd Generation Mobile Telecommunication) value-added services which divides each segmentation with service attribute, consumers motivation, and lifestyle to discover consumer characteristics. The results show that method(1) and method (4) are better performance than other methods. Moreover, the “Application-oriented” of method (1) with decision trees and association rule and “"Realistic oriented” of method(4) with decision trees and association rule both are highly prefer life applications and entertainment service. “Message-oriented” of method(1) and “Emotion-oriented” of method(4) both highly use message and monitoring services as well as consumers motivation is highly affected by life needs. The paper finds out the scopes of consumers’ characteristic through decision trees. The association rule is able to dig out the demographic data and mobile usage situation , whereas the decision tree can not find out. Therefore, integration of different clustering methods for marketing segmentation can help comprehend each segmentation more detail.