Navigating the dynamic hospitality landscape, premier hotels in India encounter a perpetual challenge: comprehending the intricate factors that drive guest satisfaction. While existing research provides broad insights, the nuances of the luxury segment are often overlooked. This study aims to bridge this gap by meticulously analyzing reviews from over a hundred premier hotels in major metro cities in India, focusing on the 5-star category. The research identifies seven key attributes influencing reviewer perceptions and reveals distinct patterns. Food Quality, Hotel Staff, and Service emerge as powerful predictors of both positive and negative sentiments, while Cleanliness and Comfort exhibit unique impacts. Through the application of logistic regression and sentiment analysis, and Natural Language Processing (NLP) techniques such as tokenization, lemmatization, and VADER sentiment analysis on online reviews, this research quantifies the influence of each attribute. The findings contribute to a deeper understanding of guest expectations and provide actionable insights for hotel management to tailor offerings and enhance guest experiences. This study significantly contributes to the ongoing discourse on customer satisfaction in the hospitality sector in India.