Predicting User Behavior in E-commerce Based on Psychology Model

Abstract

Web sites are making great effort to understand the user's behavior in order to make the Web sites easy to use and further increase their profits. This paper presents a method to predict the user's buying behavior based on psychology model. We employ the method to analyze online store data and treat the clicking and buying as user's attitude and behavior. Then, a new model, that is used to predict the user's future buying behavior, is built based on the attitude-behavior relationship theory. We then verify the model and simultaneously estimate its parameters by path analysis. Our method is evaluated by comparing with traditional naive Bayes classification algorithm. Experiments results show that our model is more effective in predicting buying behavior and finding out users who are more profitable to Web sites.