The data of reviews and ratings in the online market can provide guidance for company's production and business activities. In this paper, firstly, we build a BP neural network model to help identify "useful consumer reviews." Then, we use the fuzzy comprehensive evaluation method to identify the most successful and failing goods. Next, we achieve the time series prediction of product reputation by making use of ARIMA model. Finally, we use word segmentation and K-means clustering algorithm to determine whether stars and comments have radiation effects. [ABSTRACT FROM AUTHOR]