NLP-Driven Insights on Boutique Hotel Satisfaction

ABSTRACT

Boutique hotels are highly desirable due to their personalized service. However, studies have not examined differentiating factors of boutique hotels that could explain the nuances of this profitable niche in the hospitality industry. It is also difficult to ascertain customers’ needs through feedback and surveys as they do not explicitly highlight the reasons for their satisfaction or dissatisfaction. In this study, we attempt to assess 12,949 user reviews collected from TripAdvisor to understand the drivers of stay experience and satisfaction. We use a natural language processing (NLP)-based methodology to extract important themes and use that information to predict star ratings. This paper demonstrates that ease of booking is an important determinant of satisfaction; while service, facilities/amenities, and stay experience are the major causes of dissatisfaction for guests. Further, we have compared the US and UK markets and discovered that the US market favors stay experiences while the UK prefers more amenities.

KEYWORDS:

• Boutique hotels
• customer reviews
• guest experience
• natural language processing (NLP)
• expectation disconfirmation theory

Disclosure statement

No potential conflict of interest was reported by the author(s).