Marketing

Reservation

Service (business)

Tourism

Customer advocacy

Hospitality industry

Computer science

Customer intelligence

Business

Computer network

Customer retention

Service quality

Advertising

Hospitality

Political science

Consumer behaviour

Artificial intelligence

Customer to customer

Sentiment analysis

Machine learning

Customer satisfaction

Current Issues in Tourism

Customer retention has been one of the most recognized research issues in the service industry. The next on the list is predicting customer behaviour or understanding customer intent, which is particularly important for the hospitality and tourism industries. This study investigates the customers' hotel revisiting behaviour using a large-scale customer review data, which can shed light on the potentiality of (i) identifying the factors that are associated with the customer revisiting behaviour and attracting more customers to reuse their services and (ii) predicting future customer revisiting behaviour to a hotel. We analyse the data of 105,126 customers of an online hotel reservation service, and conduct a sentimental analysis on the user feedback reviews. By comparing one-time visitors and re-visitors, our analysis shows that the feedback reviews of re-visitors tend to (i) contain more words in a sentence and (ii) reveal more positive/negative sentiments than those of one-time visitors. On the other hand, the feedback reviews of one-time visitors tended to include more analytical and anxious words than those of re-visitors. The findings can serve as a foundation for the use of big data analysis in hospitality and tourism research.

Understanding customers' hotel revisiting behaviour: a sentiment analysis of online feedback reviews