Consumer feedback in e-commerce platforms is an important source of information that determines subsequent consumer purchasing decisions. The consistency of content among feedback information by different consumers and its impact on sales has received little attention. Based on the theory of cue consistency, this study constructs a model for the impact of content consistency between different consumers’ feedback information on the sales, including the consistency of review texts, images, and answers, and explores the moderating effect of product prices. Based on large-scale real data from JD.hk, text mining and image analysis tools with the help of deep learning techniques are utilized to measure multiple content consistency features and theoretical models are examined through econometric models. Results indicate that the content consistency of review text, image, and answers all positively affect sales, which are positively moderated by product prices. The research findings expand the theoretical perspective of the relationship between online consumer feedback and sales, and provide practical insights for the operation and management of online merchants.