32 Pages Posted: 11 Oct 2016
Date Written: September 30, 2016
Online Word-of-Mouth has great impact on product sales. Although aggregate data suggests that customers read review text rather than relying only on summary statistics, little is known about consumers’ review reading behavior and its impact on conversion at the granular level. To fill this research gap, we analyze a comprehensive dataset that tracks individual-level search, review reading, as well as purchase behaviors and achieve two objectives. First, we describe consumers’ review reading behaviors. In contrast to what has been found with aggregate data, individual level consumer journey data shows that around 70% of the time, consumers do not read reviews in their online journeys; they are less likely to read reviews for products that are inexpensive and have many reviews. Second, we quantify the causal impact of quantity and content information of reviews read on sales. The identification relies on the variation in the reviews seen by consumers due to newly added reviews. To extract content information, we apply Deep Learning natural language processing models and identify six dimensions of content in the reviews. We find that aesthetics and price content in the reviews significantly affect conversion. Counterfactual simulation suggests that re-ordering review content can have the same effect as a 1.6% price cut for boosting conversion.
Keywords: Consumer Purchase Journey, Product Reviews, Review Content, Deep Learning
Suggested Citation: Suggested Citation
Liu, Xiao and Lee, Dokyun and Srinivasan, Kannan, The Effect of Word of Mouth on Sales: New Answers from the Comprehensive Consumer Journey Data (September 30, 2016). NET Institute Working Paper No. 16-09. Available at SSRN: https://ssrn.com/abstract=2848528 or http://dx.doi.org/10.2139/ssrn.2848528