Framework for Sentiment-Driven Evaluation of Customer Satisfaction With Cosmetics Brands

Cosmetics brand managers' efforts in monitoring customer satisfaction and service quality have suffered due to the lack of effective analysis methods. In order to derive more comprehensive and objective insights into customer opinions on product quality and preferences for cosmetics brands, this study derived an online-review-based process for evaluation of customer satisfaction. The present study developed a systematic approach to the evaluation of relative customer satisfaction with cosmetics brands via sentiment analysis and statistical data analysis, and interpreted the determinants of positive and negative opinions via Term Frequency-Inverse Document Frequency (TF-IDF) analysis. To illustrate the efficacy and applicability of the proposed approach, an empirical case study applying it to the global top 26 cosmetics brands was conducted, which evaluated relative customer satisfaction with brands and examined the main causes of positive and negative opinions. The proposed approach is expected to be employed by cosmetics companies to realize or improve satisfaction with the brands that customers evaluate. Furthermore, we hope that it can be used as a source of fundamental data that could be applied to efforts to improve both brand competitiveness and provision of systematic services.