Learn How Xebia implemented Machine Learning to build a solution that can help client in predicting the group booking cancellation.
What all steps helped the business in taking decisions and prioritizing inbound and outbound flights?
The Xebia team devised a mechanism to compute the value score of each flight based on various passenger parameters such as age, gender, loyalty tier (if any), number of infants, number of medical case/wheelchairs, number of first/business/economy passengers, connection flight timing details of connecting passengers etc. Clustering algorithm were used to segment flights into five profiles and each profile was validated with business users to arrive at the priority order.
To get a copy of complete case study fill-in the form, so we can take you to download page.
Key Benefits
- Define better overbooking plans
- Better revenue management
- Build better forecasts
- Improved passenger load factor