Analyzing the Effect of Customers’ commendation on the Sales performance of Goods in Digital Markets using Functional Regression Analysis

Online customer feedback plays a fundamental role in the purchasing decision-making process. It profoundly affects people's opinions and attitudes. The purpose of this study is to investigate the effect of one of the most important decision-making tools in the context of social business, namely customer advice by controlling other effective factors such as brand reputation, on the sales performance of empirical products. In this study, the book product selected as a unit of analysis and the sales rank of 162 of such a product in one year with 67,817 opinions from buyers and ordinary users of this product collected from the Amazon online store and analyzed using the regression method. The longitudinal data was analyzed by  functional regression. The evaluation of the cumulative effect of the recorded opinions on the sales rank of products in one year evaluated and recognized as the historical effect of the relevant variables in the functional regression model. Findings indicated that customer recommendations and their feedback on other product buyers significantly influenced product sales rankings. The cumulative effect of the opinions of regular users at the end of the review period on sales rank was evident, while the cumulative influence of the approved buyers' viewpoints during the review period had a nonlinear curve. Therefore, such an effect weighs more in the middle of the review period. In this study, compared to the regular users, the opinions of approved buyers had a 60 percent greater impact on product sales rankings.