Predicting online product sales via online reviews, sentiments, and promotion strategies
Purpose The purpose of this paper is to investigate if online reviews (e.g. valence and volume) online promotional strategies (e.g. free delivery and discounts) and sentiments from user reviews can help predict product sales. Design/methodology/approach The authors designed a big data architecture and deployed Node.js agents for scraping the Amazon.com pages using asynchronous input/output calls. The completed web crawling and scraping data sets were then preprocessed for sentimental and neural network analysis. The neural network was employed to examine which variables in the study are important predictors of product sales. Findings This study found that although online reviews, online promotional strategies and online sentiments can all predict product sales, some variables are more important predictors than others. The authors found that the interplay effects of these variables become more important variables than the individual variables themselves. For example, online volume interactions with