The rapid development of the Internet has led to increasing online shopping and accumulated large amount of complicated, multi-dimensional and temporal transaction data. Many e-retailers and analysts are focusing on these data to study customers' shopping behaviors. In this study, based on product gravity, a visual analytical method focusing on individuals is proposed to analyze hierarchic production data and the features of shopping behaviors, which allows analysts to observe each consumer's shopping behaviors more directly so as to discover the features of their shopping behaviors more easily. Finally, the experimental results are presented to prove the effectiveness of the method.