We introduce a novel personalized E-commerce system through mobile devices. By providing mobile clients’ preferred service category or items in a shopping mall website, the problem of the limitation of resource of mobile devices can be solved. In this paper, the preferred service items are inferred by analyzing customers’ statistical preference transactions and consumption behaviors in the website. In computing the statistical preference transactions, we consider the ratio of the length of each service page and customers’ staying time on it. Also, our system dynamically provides the personalized E-commerce service according to the three different cases such as the beginning stage, the positive response, and the negative response. In the experimental section, we demonstrate our personalized E-commerce service system and show how much the resource of mobile devices can be saved.