Study of Hotel Satisfaction of Visitors Based on Booking.com`s Online User Reviews

The hotel industry is a highly competitive industry with many competitors on the market. At the same time, there is a change in consumer trends: customers are becoming well-informed, demanding, and selective in the services they offer. The choice of the final decision when booking a hotel, the user makes, relying not only on price indicators, a list of services offered, but is based on other people's consumer experience. The penetration of the Internet into hotel industry has led to the emergence of e-forums and e-platforms where people can exchange information about the hotels they have visited. The reputation of the hotel on the online platforms began to affect the workload of the hotel and the resulting revenue. In order to maintain and enhance the hotel’s reputation, it is necessary to research customer satisfaction and online customer reviews in order to carry out activities to make the hotel more attractive to potential customers. But, due to the large amount of information received from online reviews on Internet platforms, it is almost impossible to conduct such research manually. Recently, the processing of textual information has become possible to carry out artificially, using methods of machine learning. Accordingly, to solve the problem in the study of a large amount of information, methods of machine learning are used. In accordance with the purpose of this work - to study customer satisfaction based on the feedback they left on the Internet platform, the following tasks were done: to study the theoretical aspect of consumer satisfaction and methods for studying it, to examine the European and Russian hotel markets, to analyze previous studies of online research services, build a design study and implement it. The result of this work is the formation of practical recommendations based on the conclusions drawn from the study.