Application of text mining methods for evaluating consumer experience: case of St. Petersburg’s restaurants

Abstract

In the context of digitalization, Internet resources have a significant impact on consumer preferences, and online reviews form expectations and behavioral attitudes of consumers. In this study, we propose a methodological approach that combines structural topic modeling and regression analysis, which allowed us to identify key satisfaction factors in the St. Petersburg restaurant industry. The results indicated that the quality of service and the atmosphere become key in forming further behavioral intentions. The proposed methodology can be adapted for analyzing online reviews in various fields, such as hotel business, tourism, online retail and services. The study substantiates the applicability of text mining in customer experience management and strategic marketing, expanding existing approaches to studying consumer behavior.