Top five pricing trends in airline revenue management

Airline pricing advancements

The fluctuating airfare prices leave travel management companies and corporate customers confused. Fare pricing is complex, with many factors contributing to changes in seat prices. Because the average airline operating profit is just 3%*, airlines must use effective pricing strategies to make the most money for their products while maintaining affordability for their customers.

As technology becomes more advanced, airlines are pricing more precisely. Below are five trends that are revolutionizing revenue management.

Passenger profiling

Airlines profile their customers to adjust prices.  An example is grouping passengers as either business or leisure and instituting different pricing structures for each group.

Leisure travelers typically book several months before departure, so fares are priced higher upon initial release.  Depending on the response, the airline will then adjust fares accordingly.

Business passengers book when needed, and their cost is less important. An airline will quickly know which routes are popular with business travelers. On these routes, prices usually start low to help fill the aircraft to minimum capacity.  Fares then rise steadily as the time of travel approaches.

Demand forecasting

Airlines have typically priced fares based on historical data and previous information or trends around a particular route.  This information is limited, as there are not enough or insufficient details on specific routes.

Today, some tools can forecast demand for particular routes based on various external factors. Traditionally, adjustments have been made for days of the week, weather, public holidays, and political situations. Now, more complex data are used to forecast demand for a particular route, such as tools specializing in upcoming special events (e.g., sporting events) and their impact on demand for a specific flight.

Artificial intelligence and machine learning

Forecasting events and their effect on pricing is only the first step. The next step is knowing how they impact demand.  Airlines are experimenting with AI algorithms to predict this impact and loop it into forecasting processes.

Currently, demand forecasting is limited to seats.  Predicting the demand for ancillary products and services, such as extra baggage, priority boarding, etc., requires more effort. Easyjet is one airline already using AI to forecast demand for its passengers’ food preferences on specific routes.

Airlines collect vast amounts of data from their passengers, and AI can help turn the data into actionable insights on pricing and demand.

Dynamic pricing and fare optimization

Airlines use AI and various algorithms to adjust their fares based on real-time data, optimizing the price paid per ticket. This technology considers factors such as competitor price changes, customer segmentation, and unfolding events, and recommends pricing structures based on each customer’s potential willingness to pay.  For example, a customer that has previously flown business class or is about to achieve a loyalty status may be offered a higher price for the same seat than a customer that has typically flown economy class on leisure routes.

Total offer optimization

The next stage of dynamic pricing is applying this technology to ancillaries and optimizing the entire product bundle, including fares and extras.  Total offer optimization enables airlines to design and price a package for each customer, a retail experience akin to that of online retailers.  Airlines that successfully deploy complete offer optimization are beginning to offer their travelers the right travel experience at the right time.

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