5-Star Hotel Customer Satisfaction Analysis Using Hybrid Methodology
This work addresses customer satisfaction analysis for hotel marketing, but it appears incremental as it applies existing techniques to a specific domain without clear novelty beyond the combination.
The research tackled the problem of analyzing customer satisfaction from online reviews for 5-star hotels by proposing a hybrid methodology combining data mining and natural language processing techniques, resulting in very accurate experimental outcomes.
Due to the rapid development of non-face-to-face services due to the corona virus, commerce through the Internet, such as sales and reservations, is increasing very rapidly. Consumers also post reviews, suggestions, or judgments about goods or services on the website. The review data directly used by consumers provides positive feedback and nice impact to consumers, such as creating business value. Therefore, analysing review data is very important from a marketing point of view. Our research suggests a new way to find factors for customer satisfaction through review data. We applied a method to find factors for customer satisfaction by mixing and using the data mining technique, which is a big data analysis method, and the natural language processing technique, which is a language processing method, in our research. Unlike many studies on customer satisfaction that have been conducted in the past, our research has a novelty of the thesis by using various techniques. And as a result of the analysis, the results of our experiments were very accurate.