π Introduction: Todayβs session focuses on hotel data, statistics analysis, and benchmarking. We will explore the importance of data in revenue management.
π Importance of Data: In the digital age, data is considered valuable. Hotels have access to various data sources, and understanding how to use this data effectively is crucial for analyzing customer behavior and business insights.
π Data Sources: Data in hotels typically comes from:
ποΈ Handling Data: To manage hotel data:
π Data Visualization: Tools like Power BI can help visualize data, making it easier to understand business insights and customer behavior.
π Daily Pickup Report: This report tracks room bookings and cancellations, helping to forecast future occupancy and revenue.
π Booking Curve Analysis: This analysis helps understand booking patterns over time, allowing for better forecasting and decision-making.
π‘οΈ Hot, Warm, and Cold Analysis: This analysis categorizes occupancy rates to inform pricing strategies based on demand.
π Booking Lead Time: Understanding how far in advance guests book can help in planning and managing expectations.
π Benchmarking: To measure hotel performance, compare metrics like occupancy and ADR against competitors using tools like STR.
β Questions: If you have any questions about hotel data, statistics, or benchmarking, feel free to ask!
π Next Session: Tomorrow, we will discuss forecasting and budgeting.