Empowering Consumer Decision-Making: Decoding Incentive vs. Organic Reviews for Smarter Choices Through Advanced Textual Analysis

Abstract

Online reviews play a crucial role in influencing seller–customer dynamics. This research evaluates the credibility and consistency of reviews based on volume, length, and content to understand the impacts of incentives on customer review behaviors, how to improve review quality, and decision-making in purchases. The data analysis reveals major factors such as costs, support, usability, and product features that may influence the impact. The analysis also highlights the indirect impact of company size, the direct impact of user experience, and the varying impacts of changing conditions over the years on the volume of incentive reviews. This study uses methodologies such as Sentence-BERT (SBERT), TF-IDF, spectral clustering, t-SNE, A/B testing, hypothesis testing, and bootstrap distribution to investigate how semantic variances in reviews could be used for personalized shopping experiences. It reveals that incentive reviews have minimal to no impact on purchasing decisions, which is consistent with the credibility and consistency analysis in terms of volume, length, and content. The negligible impact of incentive reviews on purchase decisions underscores the importance of authentic online feedback. This research clarifies how review characteristics sway consumer choices and provides strategic insights for businesses to enhance their review mechanisms and customer engagement.