For some travelers, the wave of the future for airfare price structures could mean a sort of permanent airborne surge-pricing.
It’s called “dynamic pricing,” and it’s inching its way closer to a flight near you and your pocketbook.
Under a dynamic airfare pricing model, the airline identifies the potential passenger by the IP address of the device used to shop, and then riffles through its own data for any flight history on the customer and tailors an airfare specific to what the system predicts he or she will pay.
It could result in two shoppers getting different airfares for the same flight, even if they purchased their tickets at the same time, according to Travel Weekly.
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“2018 will be a very phenomenal year in terms of traction,” John McBride, director of product management for revenue management software company PROS, told the publication. “Based on our backlog of projects, there will be a handful of large carriers that move toward dynamic pricing science.”
But critics say transparency in pricing falls by the wayside under the dynamic, or next-gen, airfare model.
“You and I could be sitting in the same room on different computers or mobile phones, search the same route, airline and dates, and see different prices, even on a flight where there are as many seats in the same fare class,” USA Today guest columnist George Hobica wrote. “If you thought airfare shopping was challenging before, it’s only going to get moreso.”
Amadeus, a PROS competitor, sells its dynamic pricing software to airlines as a way to maximize revenue per flight, both by displaying fares that more price-sensitive customers are willing to pay, and by recognizing customers who are actually willing to pay more.
According to Travel and Leisure, that means consistent repeat customers and leisure travelers could see lower fares, while travelers using a corporate credit card could see higher fares.
PROS already works with 80 airlines worldwide, including Southwest, Lufthansa, Emirates and Aeromexico, according to Travel Weekly. It is still unclear under what time frame the model could be made to work for third-party sites like Expedia, Booking.com or Kayak.