Demand Forecast for Hotels
Forecast Accuracy converted into increased Business Margins for Hotels.
Make decisions based on when you will have rooms available for customers and at what price, with the constraint of fixed room capacity.
The purpose is to improve Demand Prediction based on the available internal/external data.
Case Study - Hotel chain
50 hotels in Europe. 6,000 rooms. $150 annual revenue. Avg price per room: $75
Revenue attributed to Demand Forecast
Profit attributed to Demand Forecast
Tailored predictive algorithms
We blended human predictions with machine learning to achieve the best possible results. Beforecaster's algorithms are created under the principle that forecasting accuracy is a means to a business end.
Tapping into the right sources
Exploits data from a variety of sources that included historical demand, weather, events, epidemics, or transportation prices.
Avoiding Forecasting Waste
We never take for granted that all forecasters add value to a prediction. We eliminate any prediction elements that return poor results.
Every time new data arrives in the system, Predictions are updated. It warns users whenever it detects changes worth communicating.