Product text snippets should highlight the product features that are appealing to customers. Nevertheless, the features in current product snippets mainly are often decided based on the understanding of vendors or advertisers, and may fail to contain the features appealing to customers. This paper investigates how product text snippets generation can benefit from online customer reviews. In doing so, an automated method is designed, in which features and the opinions are extracted from online reviews, and are further used for product text snippet generation. To verify the effectiveness of the proposed method, we conduct two experiments and the results show that the extracted features and the snippet are effective in inviting potential customers, compared with the baseline ones. Experimental results demonstrate that 1) the extracted features are more appealing to customers; and 2) the snippets generated based on the extracted features are more likely to be clicked.