How predictive analytics is helping airlines see through the clouds

Countless events in the modern customer journey are making it even harder for airlines to match demand with the right offer. 

People travel for a reason and airline revenue management teams have often struggled to predict precisely where demand will come from in their market. 

This results in missed opportunities for the airlines and leaves customers frustrated by a lack of choice and high prices. 

However, predictive analytics technology can help solve many of the challenges faced by revenue managers.

With so many business, sports and cultural events happening around the world, airlines have traditionally found it challenging to keep up with local events.

For example, did you know that in the U.S. alone, there are more than 20,000 professional conferences that change location every year?

These conferences can attract more than 30,000 people each, with all the peripheral services potential too.

Being able to understand these catalysts for travel is essential for forecasting airline demand in a smarter, more comprehensive way.

It’s traditionally been a challenge for revenue management to keep up with changing global events, due to countless sources of information that must be tracked externally. 

The lack of visibility creates unhappy customers and costs billions in supply chain problems and lost revenues.

The better airlines can understand what is happening in their markets, the better they can scale up supply to meet peaks in demand. They can be proactive rather than reactive, increasing operational efficiency while the customer benefits from increased choice, capacity and personalisation.

This is where predictive analytics technology comes into play, and technology partners and airlines need to work together to bringing this tech to the forefront of air travel.

This is why Amadeus has been partnering with technology partners who are recognised experts in their fields to provide airlines with powerful predictive technology. 

How predictive analytics technology works

The value of predictive analytics is knowing exactly when and why a demand spike is happening. 

The leading predictive analytics technologies simplify event forecasting through collating, aggregating and verifying local, national and international scheduled and unscheduled events into one place, giving companies the ability to forecast what events are happening and when, in order to plan accordingly months in advance.

For example, Amadeus has partnered with PredictHQ, whose predictive analytics technology is used by companies such as Uber and Domino’s. It draws on more than two billion data points to identify events in thousands of locations. 

This saves revenue managers hours each month that they would otherwise spend searching for events – inevitably missing some ‐ and entering that data manually in spreadsheets.

Companies can then use that intelligence for planning, pricing and marketing. For example, Booking.com uses predictive analytics to help set prices so travellers know which days are more or less expensive to travel and this technology is now being adopted by airlines.

By pairing travel data with real‐world event information, airlines can benefit from a unique in‐market picture of potential demand versus current supply.

Predictive analytics in actions

Airlines are large and complex businesses that have established processes, so it’s key to seamlessly integrate predictive analytics into the wider planning suite.

Airlines that are exploring predictive analytics include SAS and airBaltic. 

These tests will help travel technology providers to identify potential integration models, best practices and help source even more airline‐oriented data that can improve planning.

Travel technology providers currently have concepts of how airlines could use predictive technology, but by taking an ‘integration designed by airlines’ approach they can get a true picture of how airlines will use this intelligence.

What does the future hold?

Going forward, we can expect to see predictive technology used to improve network planning and expect airlines to enjoy greater visibility over the catalysts behind travel. 

Forecasting could be applied to similar revenue management features for personalised shopping recommendations, for example.

As airlines aim to offer increasingly personalised services to customers, we can expect predictive technology to help improve revenue management, merchandising, customer experience management and more.

And we’re only at the beginning. It’s an exciting time to be in aviation.