Every day at INFARE we collect 1 billion airfares. Number which has been rapidly increasing and it is expected to surpass 1.5 billion by November 2016.
All these observations are added to those alreday stored in our database, which presently amount to 350 billion.
How to increase the utilisation of this huge amount of information is an ongoing and exciting challenge for us.
After introducing Machine Learning Technologies and enlarging our Tech Stack, we have focused our research on Airfare Predictions.
Predictions represents our latest endeavour, goal and challenge!
Predictions in Pharos
Predictions will be featured in upcoming versions of Pharos, our Airfare Analytics.
Being Pharos aimed at supporting revenue management and pricing activities, the introduction of airfare predictions brings the usability of the tool to a whole new level.
Airfare predictions will be accessible via Latest Prices and Price Evolution Displays.
In the first version, it will be possible to get estimations of how prices will look like a number of days or weeks from now via the Latest Prices Display.
Later on, the Price Evolution Display will show how prices are expected to develop getting closer to the date of departure.
Last but not least, smart prediction-based Alerts will be available in Pharos.
After setting-up personalised alerts, you will be able to get a notification every time an unexpected change occurs.
Demand Curve Estimations
Our Data Scientists are collaborating with analysts in a number of Airlines to develop estimations of Competitors’ Demand Curve.
The idea behind this project is to combine Airlines’ own historical and current demand curve with our information on market prices. By doing so it is possible to estimate competitors’ Demand Curve, thus getting indisputable competitive advantage.