Booking Cancellation Prediction Results in Revenue Increase for Hotel

Objectives

  • The client, a hotel, experienced significant revenue loss due to high rates of booking cancellations. 
  • The booking cancellations have additionally impacted their room pricing and allocation strategies.
  • The goal was to leverage improved predictions of demand to boost revenue, refine cancellation policies, and optimize overbooking and inventory management approaches.

Solution

  • A predictive model based on artificial intelligence (AI) was developed to forecast booking cancellations. 
  • This model underwent training and testing with comprehensive data attributes provided by the hotel’s reservation system.
  • Through its dataset, a comprehensive collection of inputs was obtained, encompassing guest demographics, past booking data, types of rooms booked, duration of stay, and the channels through which bookings were made. 
  • This ensured a thorough analysis of the predictive model.

Benefits / ROI ​

  • The AI model achieved a 93% accuracy rate in predicting which bookings would be cancelled. 
  • This high level of precision enabled the hotel to manage potential cancellations more effectively, reducing the impact on revenue.

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