The reason behind the rating: Text mining of online hotel reviews

Online customer reviews are a significant marketing resource for products and service business, often serving as a key reference point for potential customers. This study analyses a set of hotel reviews to find out what aspects of hotel experience are taken into consideration by customers when rating a hotel. We use text mining of hotel reviews to identify main features referred to by customers and determine their correlation with customer satisfaction or dissatisfaction. Our data set comprises reviews of ten hotels located in the vicinity of "Khao San Road" in the centre of Bangkok in Thailand, a popular holiday destination known as the centre of the "backpacking universe". The results highlight several main aspects affecting customer satisfaction, with friendly and helpful staff being the most influential one, whilst negative experiences with complementary services provided by the hotel, such as pool and Wi-Fi have the strongest impact on customer dissatisfaction. Other factors impacting customer satisfaction include cleanliness, room and bathroom interior, sleep quality and location. Our findings can be used to design effective feedback gathering and social media monitoring systems, and they also underpin a set of managerial implications regarding managing and marketing customer experiences in the hotel industry.