ONLINE REVIEWS CAN TELL US HOW THE EXPERIENCE OF THE GUEST WITH THE VIETNAMESE HOTEL

Online booking systems have transformed the travel industry by creating vast information platforms. These platforms enable customers to share their experiences, significantly influencing the destination choices of others. For hoteliers, this wealth of user-generated content is an invaluable resource, offering direct insight into the guest perspective. Consequently, analyzing this feedback has become essential for understanding and improving customer satisfaction. Although many studies have employed machine learning techniques to analyze sentiment in this data, these methods have overlooked the specific context of natural language, failing to capture the specific context and linguistic nuance embedded in customer reviews. This study aims to explore customer satisfaction with Vietnamese hotels using a mixed-methods approach. This approach combines linguistic rules, sentiment corpora, and the Python VADER library to mine the big data of customer reviews effectively. By combining algorithms and formulas, the research can measure guest satisfaction with specific aspects of the hotel. The data for this study were collected from TripAdvisor, and it is a large dataset of 32,447 individual reviews of over one thousand hotels in Vietnam. To achieve a high degree of detail, a granular 1–5 scoring scale was implemented, allowing for the classification of feedback into specific categories ranging from "strongly dissatisfied" to "strongly satisfied" for each distinct aspect of the hotel experience, such as service, staff, and cleanliness. The findings revealed an overall customer satisfaction rate with the hotel's quality at 84.3%. Interestingly, the highest satisfaction score for the "staff" aspect was slightly higher at 84.83%, highlighting a subtle discrepancy between general guest sentiment and their experiences with particular amenities or services. The results confirm that a linguistic rule-based method provides a more detailed and accurate understanding of customer satisfaction. This approach helps hotel management to understand and pinpoint specific operational areas that require improvement or reinforcement. It offers deeper insights into customer preferences and facilitates the creation of customer personas. In a highly competitive hospitality market, this study also provides a clear viewpoint for making targeted enhancements to gain a competitive edge.