Paper Key : IRJ************710
Author: Jayabharathi S
Date Published: 15 Apr 2025
Abstract
Hotel revenue management systems aim to maximize revenue by analyzing various customer and operational data. This dataset explores key parameters such as customer credit scores, room prices, occupancy rates, seasonal demand, and customer booking patterns. It provides a detailed look at factors influencing revenue generation, including high-value customer identification, loan eligibility for financial offerings, and dynamic pricing strategies.The data encompasses customer demographics, financial attributes, and behavioral trends, offering insights into optimizing pricing, identifying peak demand periods, and enhancing booking strategies. By leveraging these variables, the system supports data-driven decisions, such as adjusting prices based on occupancy rates and customer demand patterns. This analysis underscores the significance of integrating financial metrics and customer behavior into revenue optimization processes.Such systems not only improve financial outcomes but also enhance customer satisfaction by tailoring services to their preferences and behaviors, fostering long-term loyalty. This study showcases the role of data analytics in transforming hotel operations into agile, customer-centric revenue models. Keywords: Customer Demographics , Behavioral Trends, Occupancy Rates, Seasonal Demand, Customer Booking Patterns, Data-Driven Decisions, Financial Metrics, Pricing Strategies, Revenue Generation, Customer Satisfaction, Demand Analysis, Operational Efficiency