Case study

Hotel Cancellation Prediction

Revenue protection through predictive analytics.

XGBoostFeature EngineeringPandas

+18%

Accuracy

0.91

AUC

Problem

Unpredictable cancellations erode hotel revenue and break overbooking strategy.

Solution

Gradient-boosted model on historical bookings with feature engineering on seasonality, lead time, and customer signals.

Impact

Improved prediction accuracy by 18%, enabling smarter pricing and overbooking.

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