Airline competition is a driving force in the airline industry. In fact, it is increasing year on year. Consumers and travellers themselves are becoming more and more well-informed; quite often, travellers are even better informed than the airlines are on their own competitive positioning.

Millions of US Dollars are being invested in giving travellers better tools to find the best offers, and not nearly enough to offer the airlines the tools they need to stay competitive at any time, through any sales channel.
 
In a keynote speech at the AGIFORS Revenue Management Study Group on May 8th, our CEO Nils Gelbjerg-Hansen presented and discussed a new and innovative way to better model and capture airline competition using machine learning.
 
Modelling Airline Competition using Machine Learning

Infare on stage: Nils Gelbjerg-Hansen, CEO at Infare, delivering a keynote speech
at the AGIFORS Revenue Management Study Group 2019

 
Historically at Infare, we have delivered what airlines have requested – and will continue to do so. But when it comes to this new initiative, we are investing in resources to better guide our airline customers towards what we think they should be asking us to monitor for them, based on our own expertise.
 
Besides looking at the traditional factors, such as logical city-to-city competitions, we also look at the bigger picture. This includes the catchment area, which then also include competitors that would not normally be considered by airlines, yet some consumers would consider as an alternative.
 
Along with catchment area, we’ve also added capacity into the equation. If an airline departing from another city has a very low fare, but also a very low capacity, it would score lower on the competition scale when compared to a competitor with a much higher capacity. These measures allow us to get a better understanding of airline competition.
 
We’ve discovered that our airline customers do not frequently reconsider who their competitors are. And although we agree that certain competitive situations often remain unchanged, there are many changes that consumers spot before the airlines themselves do. This is information we want to bring forward before it impacts profit margins.
 
If you have missed the keynote speech by Nils Gelbjerg-Hansen in Panama but you are at the IATA Symposium in Athens on 25th June be sure to come and hear what our Data Scientist Vadim Skritskiy has to say on the topic, as he will be on stage along with other industry influencers.
 
IATA Aviation Data Symposium Modelling Airline Competition using Machine Learning

 

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