Leveraging data warehousing and mining to improve customer satisfaction in the hospitality sector

In today’s data-driven economy, the hospitality industry faces increasing pressure to personalize guest experiences and maintain high levels of customer satisfaction. This paper explores how integrating data warehousing and data mining techniques can provide actionable insights to enhance service delivery and guest satisfaction in the hospitality sector. The study begins with an overview of current challenges and data utilization trends within the industry, highlighting the role of structured data consolidation and analytical tools in strategic decision-making. As a practical case study, La Veranda Hotel in Larnaca, Cyprus, is examined using a two-phased experimental setup: data warehouse design using a star schema for customer-related metrics and subsequent data mining through OLAP operations and association rule mining via Weka. Findings reveal key satisfaction trends based on guest demographics, booking patterns, and room preferences, demonstrating how hospitality providers can leverage intelligent data systems to optimize guest experience. This study found that 95% of highly satisfied guests stayed fewer than five nights, over 45% gave a perfect satisfaction score, and room type, guest origin (notably UK and Cyprus), and peak months (June, Sept, Oct) significantly influenced satisfaction outcomes.