Effects of Negative Customer Reviews on Sales: Evidence Based on Text Data Mining

Abstract

The effects of online customer reviews on sales have been widely studied, especially with regard to Internet shopping and e-retailing. The majority of the literature, however, has focused on the volume and valence, and produced mixed results. For an in-depth understanding of the effects of customer reviews on sales, the present study uses text data mining to investigate how the text content of negative reviews impacts online sales. Content association and topic extraction were the methods used. Relevant data were collected from JD.com, and three factors - content topic, proportion, and consistency - were highlighted to unveil the underlying mechanism of effects of negative reviews on sales. The study results will enable marketers to understand the effects of customer reviews on Internet sales and help them to improve customer satisfaction and loyalty. Management implications and future research directions are also presented.