A study on customer satisfaction in Bali's luxury resort utilizing big data through online review

Bali is known as one of the region's most popular and long-established mass tourism destinations. However, the tourism sector in Indonesia saw a drastic decrease in the number of local and foreign tourists due to COVID-19. The objective of this study is to analyze the factors that are related to customer satisfaction post-COVID-19 in Bali's resorts. The data consist of a total of 7370 hotel reviews collected from Google Travel. Text mining was used to conduct a frequency analysis to determine which attributes were frequently mentioned. Additionally, semantic network analysis was used to analyze customer experiences and satisfaction in Bali resorts. As a result, the top 88 keywords were divided into five clusters such as 'Location', 'Health Protocol', 'Destination Resort', 'Value', and 'F&B'. The first quantitative analysis, factor analysis, shows there are 18 words out of 88 words related to six different clusters. Furthermore, the absolute value result of the linear regression analysis indicated that intangible service is affecting customer satisfaction negatively. As a result of the factor analysis, the two aspects that are related to the intangible service, 'hospitality' and 'staff', are considered to be the most important aspects of resorts and should be improved in order to increase customer satisfaction.