Investigating Key Attributes in Experience and Satisfaction of Hotel Customer Using Online Review Data: A Case Study of Five-Star Hotels in Colombo, Sri Lanka

Abstract

The rapid growth of online travel platforms has generated a substantial amount of user-generated content, which offers valuable insights into customer experiences in the hospitality industry. This research examines the key factors of customer satisfaction in five-star hotels using online review data. It focuses on four five-star hotels in Colombo, Sri Lanka, based on a dataset of 66,314 Google reviews. To analyze and identify the most prominent themes in customer feedback, a big data analytics approach was employed, combining text mining techniques with keyword frequency analysis and semantic network analysis. The findings show that service quality, staff friendliness, cleanliness, and overall hotel environment are frequently mentioned elements that influence customer satisfaction. The network analysis further demonstrates a strong relationship between service-related attributes and positive guest experiences, highlighting the central role of service interactions. The study contributes to hospitality and tourism literature by demonstrating the usefulness of big data analytics in extracting meaningful insights from online reviews to gain a better understanding of customer behavior. The findings suggest practical implications for hotel managers seeking to improve service quality, enhance customer satisfaction, and strengthen their competitive advantage through data-driven decision-making.