Growth of digital brand name through customer satisfaction with big data analytics in the hospitality sector after the COVID-19 crisis

Abstract

This study examines the best practices for the optimization of the corporate digital brand name by taking into consideration customers’ behavioral big data and web analytics. In the first stage of the study, customers’ satisfaction big data have been extracted with the assistance of a web scrapping tool from TripAdvisor for 189 hotels in Hubei province, and behavioral data from Hubei province hospitality websites have been gathered with the assistance of web analytics platforms for 5.7 million website visitors for the last 18 months. In the second stage of the research, those data have been statistically analyzed including descriptive, correlation, and regression analysis. Then, a fuzzy cognitive map has been created to present the intercorrelation between the parameters and two optimization scenarios have been developed for digital brand name and customer satisfaction. Finally, an Agent-based model has been created in order to simulate the customers’ behavior in the corporate website and TripAdvisor. The results indicated that hotels in Hubei province need to invest less in social media advertisements than search engine advertisements in order to achieve a competitive advantage and improve their digital brand name. Additionally, hotels need to develop their websites with more engaging content to maintain the customer on the corporate website for more time in order to optimize customer satisfaction in contrast to healthcare and libraries websites.