The Study of Mobile Phone APP Software User Browsing Behavior Clustering

• Main Authors: Ju-Min Liao, 廖如閔
• Other Authors: 邱垂昱
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/mw7jw4

碩士 === 國立臺北科技大學 === 工業工程與管理系碩士班 === 102 === With development of information technology, finding useful information existed in vast data has become an important issue. Company must understand their customers and customer value analysis turns to be an important tool. In this research, we used PSOSOM (particle swarm optimization and self-organizing map) clustering to analyze user loyalty of mobile phone App (application can be abbreviated as App) software, and then RFM (recency, frequency and monetary) analysis described the user behavior. According to the market segmentation, special offers to the varied consumer group can stimulate purchasing behavior. Let customers from online to offline physical channel then drives sales and enhances brand. Finally, improve click-and-mortar conversion rate effectively.