Enhancing Customer Experience in Tourism and Hospitality With Machine Learning Framework

Even without taking into account its environmental component, tourism industry is a crucial area of economic and social growth due to its economic and regional relevance. Customers frequently use the increasing amount of online reviews to inform their purchasing decisions. On the other hand, nothing is known about how managers react to internet reviews of hotels. One of the main sectors of the tourist and hospitality industries is the hotel sector. The paper discusses classifying and forecasting customer attitudes. The paper presented a novel paradigm for classifying and forecasting customer attitudes. The client testimonials came from a hotel in India. The customer reviews were processed in the following stage and fed into different machine learning algorithms. The RF, LR, NB, and BRDT algorithms were employed in this work. The BRDT algorithm outperformed the others in terms of output. Additionally, the BRDT was used to extract the key elements driving the excellent customer experience. Ultimately, a number of intriguing findings about the impact of feature count on machine learning algorithm performance were noted.