Top five pricing trends in airline revenue management
The fluctuating costs of airfare leave both travel management companies, and their customers confused. Fare pricing is complex, with many factors contributing to changes in seat prices. Because the average airline operating profit is just 3%*, it’s crucial that airlines 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.
1. Passenger profiling
Airlines profile their customers to help them adjust prices. An example of this is grouping passengers as either business or leisure – instituting different pricing structures for each group.
Leisure travelers typically book several months prior to departure, so fares are priced higher upon initial release. Depending on the response, the airline will then adjust the fare accordingly.
Business passengers book when the need arises and their cost is of less importance. An airline will easily 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.
2. Demand forecasting
Airlines have typically priced fares based on historical data – previous information or trends around a particular route. This information is limited, as there is not enough and/or insufficient information about certain routes.
Today, there are tools that can forecast demand for particular routes, based on a range of 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 that specialize in upcoming special events (e.g. sporting events) and their impact on demand for a particular flight.
3. 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 that can 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 huge amounts of data from their passengers, and AI can help turn the data into actionable insights on pricing and demand.
4. Dynamic pricing and fare optimization
Airlines use AI and various algorithms to adjust their fares based on a range of real-time data, optimizing the price paid per ticket. This technology considers factors such as competitor prices changes, customer segmentation, unfolding events, etc, and recommends pricing structures based on each individual 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 than a customer that has typically flown economy class on leisure routes – for the same seat.
5. Total offer optimization
The next stage of dynamic pricing is applying this technology to ancillaries and optimizing the entire product bundle – inclusive of fares and extras. Total offer optimization enables airlines to design and price a package for each individual customer, a retail experience akin to that offered by online retailers. Airlines that successfully deploy total offer optimization are beginning to offer each of their travelers the right travel experience –at the right time.