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Wednesday, Jan 14, 2026

Coronavirus Has Upended Everything Airlines Know About Pricing

Coronavirus Has Upended Everything Airlines Know About Pricing

The pandemic has completely confounded the computers that spit out airfares based on passenger behavior. After an unprecedented drop in air travel due to the coronavirus, passenger airlines are being forced to make long-term, make-or-break decisions at a time of great uncertainty and minimal cash flow. So how are they planning to survive?
Airlines have lost the ability to extract as much money as possible from travelers. And their pricing computers may stay confused for some time to come.

The airline industry has been notorious for being the most difficult ones to profit from or indeed survive in, given almost every crisis seems to lead to a round of bankruptcies. The current crisis with the travel bans might just be the most severe of them all. This article talks about a completely new challenge the current crisis is posing for the industry – revenue management or seat pricing in plain English.

Whilst the emergence of ‘Big data’ based analytics has spawned off several new business models, airlines have been using statistical tools and algorithms based on huge swathes of historical demand data to price seats so as to optimise utilisation and pricing for decades now. Given significant changes in travel behaviour thanks to the pandemic, some of these could likely be permanent changes, historical data may not come in that handy in predicting demand patterns and therefore affect the industry’s ability to price seats optimally.

“Revenue management—the science of getting the highest price for an airline seat, hotel room or other perishable good or service—is based largely on historical data. With big-data computing, airlines know with surprising precision what the demand will be for the 2 p.m. flight to Chicago on the third Thursday of October. Except now they don’t, since so much of revenue management is based on past buying with no relation to a pandemic.

…Spot checks on busy routes show surprisingly little variation between pandemic fares this fall and summertime prices next year, when airlines hope there will be strong demand. In other words, pricing systems look confounded.

..It’s worth explaining how airlines actually price tickets. It’s a system that often frustrates consumers with rapid changes. The cheap prices never seem available when you want to go.

Airlines typically have a pricing department that sets a range of fares for each flight and includes rules that govern each fare, like a 14-day advance-purchase requirement. The lowest price might be a match of a cheap fare a discount carrier has in a particular market. The highest coach price will be the unrestricted, refundable walk-up fare. In between, there may be a dozen different prices.

Airlines also have a revenue-management department, separate from pricing. Revenue management decides how many seats to sell at each price and how many to hold back for higher prices, based on forecasts of demand and how flights are actually selling. Human analysts fine-tune computer results and mix in their own hunches and experience.

Every price gets loaded into reservation systems along with the availability of seats. If seven seats sell at one price and that’s all the airline allocated, the price a shopper sees jumps to the next available price.

Tom Bacon, a longtime airline-industry pricing executive and consultant who taught revenue management at the International Air Transport Association, thinks airlines need to move away from their reliance on historical data. He suggests they become more like online retailers that use factors like how many searches have there been for a particular product.

“Expedia or Amazon don’t think of it as: What did you sell three years ago and what’s the average sale for that over the past three years? They are now: What is hot now?” Mr. Bacon says.

Today, airlines say they are doing a lot of manual pricing and essentially pricing every flight as if it were a brand new route with no historical data.”
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