Research About The Online Review Effects On Sales Of New Products And Old Products

With the fast development of the internet and E-commerce, online shopping has been very popular. Online shopping adds to consumer uncertainty about the quality of products and service, so online stores have established user rating system and online review has become an important source of product information for consumers. A survey of CNNIC shows that online comment has become the most important factor which influences consumer purchase decisions.Meanwhile, online reviews caused concern of the academic. Research of online reviews can be classified into two categories, and one is the researches about the impact of online reviews one individual consumers purchase intentions, and the other is the research about the influence of online reviews on product sales at the market level.Consumers depend on online review to different degrees for products in different sales stages. In this study we try to find the effect of user reviews on products sales in different sale stages.We present this research hypothesis based on theory of consumer purchase decision behavior, theory of innovation diffusion, information overload and information value theory. Based on the information of209types of cell phones on a large e-commerce website, this article tries to find out the influence of user reviews on the sales of products new to shelves and that put on shelves earlier, and analyzes how different the effects are. Besides the review amount and valence, the article also addresses the influence of review distribution on the sales.The results show positive correlation of the recent review amount and coefficient of variation with recent sales. When the positive review ratio is higher than0.9, there is no significant correlation of the positive review ratio with the recent sales, and when it below0.9, it has significant effect on product sales. The research also points out that recent review amount affects recent sales of new products more than that of old ones. Based on the findings above, we put forward advices about review management and rating system design.