Online Product Evaluation System Based on Ratings and Review

Abstract

The decision-making process for product design and improvement is hindered by traditional user research methods due to the rapid updating pace, limited survey scopes, small sample sizes, and labor-intensive procedures. This study suggests a novel method for gathering valuable online evaluations from e-commerce platforms, develops a system for measuring the effectiveness of a product and suggests ways to improve a product using sentiment analysis and opinion mining of online reviews. The method's efficacy is supported by a sizable body of user reviews for smartphones, from which we can reliably estimate the product's unfavorable review rate with only a 9.9% error using the assessment indication system. After considering the entire method in the case study, improvement strategies are suggested. The strategy is applicable for product evaluation.