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How Willingness-to-Pay is Changing Airline RM Forever

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If you’ve talked to PROS recently, you’ve likely heard about our Willingness-to-Pay (WTP) forecasting and optimization science, which helps airlines better forecast and adjust class availability based on price sensitivity.

What is so exciting about Willingness-to-pay? It lays the foundation for RBD-less, class-free revenue management and dynamic pricing. It allows airlines to get closer to continuous pricing based on science and AI, and it’s an important step to implementing true offer optimization and modern airline retailing.

Why Willingness-to-Pay?

We’ve outlined the PROS vision around airline dynamic pricing as a critical enabler for airline retailing. Many airlines have started down this path, and while there is still a lot of work to do, the immediate benefit is incremental revenue.

Benedikt Zimmermann, Senior Director, Head of business Development, Lufthansa Group, quote image

Without true, class-free dynamic pricing, revenue dilution caused by buy-down continues to be problem revenue management departments work to solve every day. Willingness-to-Pay forecasting is an industry-first technology that helps airlines scientifically combat buy-down and drive incremental revenue.

How does Willingness-to-Pay work?

WTP uses AI to forecast the relationship between price and demand, or price sensitivity, for a given product. It then incorporates the price sensitivity into an optimization decision, performs the network and leg optimizations, and sets the class availability based on that price sensitivity.

By determining the lowest available class based on this price sensitivity, the demand is pushed into the higher classes, thereby alleviating buy-down and ultimately capturing more revenue.

As easy as that may sound, WTP is an incredibly detailed forecasting and optimization process, and it involves a deep understanding of price sensitivity.

In this case, price sensitivity indicates how much demand change there will be given a change in price. Highly price sensitive demand means that a small change in price can result in a large change in demand. Less price sensitive demand means that a change in price does not result in a large change in demand. The algorithm that you choose for determining the price sensitivity of the passenger is critical, and of course, hotly debated.

Forecasting Price Sensitivity

PROS has been addressing the price sensitivity problem for many years, continuing to update the approach. This started with PROS Hybrid Forecasting and Optimization, which was revolutionary in its approach. This method forecasts on availability data to determine which portion of the demand is price sensitive and which is product sensitive. Hybrid opened the door for airlines to begin addressing this problem, and an earlier version of this science quickly proved successful, helping one airline increase revenue in three key markets by 4.7%, with the six routes generating an additional US$1.5 million in fare revenue. Read the full case study here: Willingness-to-Pay Solution Recaptures Revenue with Leading Science.


Building on that success, the PROS Product Management and Science teams set out to explore an option that could improve on the results of hybrid and create our path toward the future of revenue management with continuous dynamic pricing. The solution is what we now call Willingness-to-Pay Forecasting and Optimization, available in PROS RM solution.

The solution focuses on using the value of the passengers that have booked rather than using the class code of the booking, an important step in helping airlines to break away from class codes. You can read more in-depth about PROS WTP forecasting methodology for airlines and how it impacts availability calculations in PROS Real-Time Dynamic Pricing in the e-guide Breaking Down Willingness-to-Pay in Airline RM.

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What’s Next?

Willingness-to-pay is game changing for airlines as they revolutionize how they retail and deliver on the Offer and Order vision. More flexible pricing means that airlines can shape and price products based on what they know about the passenger through science. Airlines that implement this science now will be better equipped to further their dynamic pricing strategies, and ultimately deliver on offer optimization and order management.

Interested in learning more? Contact PROS to learn more about our willingness-to-pay science and how it can help your airline capture market demand better.

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About the Author

Justin Jander is a Director of Product Management, focusing on the Revenue Management products at PROS. Justin has been with PROS for 11 years, all within the Product Management group, focusing on the travel products. During that time, he has overseen the continuous improvement of the PROS revenue management products. In order to understand the needs of the always-changing industry, he has worked with airlines across the world, which allows him to understand the business problem and translate that into features that can improve the RM system. Justin earned a Bachelor of Science degree in Mathematics from Stephen F. Austin State University and a Master of Science degree in Statistical Science from Southern Methodist University.

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