Development of methodology for classification of user experience (UX) in online customer review

Abstract

In e-commerce, customer feedback has become an essential source of insight into a product or service's user experience (UX). The study of UX helps to integrate customers' potential needs into the product's design. Because customer reviews in e-commerce are not structured and categorized, it is necessary to analyze UX based on customer opinions systematically. This study tries to structure UX in a product's positive/negative context through a neural network-based self-organizing map (SOM). As a result of analyzing 10,482 reviews on wireless earbuds in BestBuy, an electronic product e-commerce platform, it was confirmed that it is a suitable method for categorizing user experiences between reviews and deriving important factors. In particular, the difference in core UX elements by positive/negative context of the product was verified based on the star rating. The results of this study are expected to contribute to product improvement and business improvement that reflect customer needs by companies or designers who design products for end-users.