The growth of big data and availability of APIs is providing exciting new opportunities for making sense of travel data, even for a fledgling start-up like Rome2rio.
Airfares fluctuate wildly, but do follow certain obvious trends; longer flights cost more, and some airlines are more expensive per mile flown than others.
We recently started an internal project aiming to model approximate/typical air fares for the flight itineraries assembled by our system. Our aim was to use this model to improve the accuracy of our multi-modal routing engine. However, in the process we generated some interesting data worth sharing with the industry.
We modeled airfares using some simple parameters. To do this, we examined the economy class airfares displayed by Rome2rio to users over the past 4 months, totalling some 1,780,832 price points. We grouped the airfares by distance and selected the 20th percentile fare for each distance (where 20% of fares are less, and 80% are more), to produce the following graph: