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Predictive analytics takes historical data and searches for patterns that can be used to anticipate and respond to future events. By leveraging the huge potential of a predictive model, airline revenue accounting departments can minimize revenue leakage, increase profits, and build more efficient and effective financial processes.

Automation, combined with forecasting can make it easier to more profitably price tickets, estimate no-shows before they eat up precious travel time and lead to empty seats, better maintain aircraft for more schedule regularity, and coordinate capacity.

According to Blue Yonder, predictive analytics can allow airlines to perform up to ten times better on key performance indicators. So how can airline revenue accounting take advantage of this model? 

Seat and Capacity Optimization

Airlines lose money when passengers cancel reservations or fail to show up for their flight. When an aircraft flies at less than capacity – especially when the empty seats could have been prevented – it’s a waste of resources. And when travelers become no-shows, the delays can lead to higher handling costs and lost loyalty. Blue Yonder found that between 5 and 10 percent of departure delays at major hubs are due to no-shows, and cost airlines more than $2.5 million per year.

Predictive analytics allows airlines to anticipate the number of cancellations and no-shows for each flight and to offer newly opened seats at adjusted prices. In addition, airlines can coordinate this information with cargo handling to hold bags of no-shows and get flights in the air on time.

By looking at passenger traits, flight classes, airport terminals, plane types, time of day, and flight capacity, analytics offers a no-show probability range for each flight, helping revenue accounting departments create and follow an informed overbooking policy.

Price Optimization

For any given passenger, the types and costs of tickets will vary at several points in time leading up to the departure. Net demand prediction can help airlines optimize their pricing practices even further, automating the collection and analysis of data to determine the market’s response to price changes and promotions.

Predictive analytics looks at sales performance patterns and allows for both short and long-term pricing strategies, and allows airline revenue departments to examine the effects of promotions over time. By looking at the promotion channels, targeted customers, and more, airlines can develop more sophisticated processes and avoid wasted efforts in the future. This combined with demand prediction, seasonal trends, and other factors makes for a much more individualized experience for every type of traveler, and enables up-to-the-minute pricing changes that remain aligned with overall company strategy.

Loyalty Program Optimization

One airline, noticing that its loyalty program members were leaving in droves, sought to learn why this was. They invested extensive time and money on manual research, and found that loyalty members didn’t feel they had anything to gain by staying on – but this was only part of the picture. By applying predictive analytics, they were able to forecast churn before it happened and take informed actions by understanding what type of a response each action would get. This type of two-step prediction does wonders for reducing churn, and can also help airlines make tough determinations, such as which loyalty customers to offer open seats to.

Campaign Management

Ancillary products are big business for airlines, and they require promotion and precise targeting. But it can be hard to predict what will come out of any given customer communication, and to determine the cause and effect of campaigns. For example, many airlines will target high-revenue customers with luxury offers, without understanding that a large portion of those targeted may never respond to the promotion, while those who would have responded in the first place were never targeted. Predictive analytics makes marketing campaigns more profitable – and can even help airline revenue accounting departments reduce their budget while increasing sales.

Predictive analytics is a beacon of light for airline revenue accounting departments. It does require a large amount of data, however, as well as data refinement and analysis. By partnering with an IT vendor that can gather, store, and partition data, airlines will be uniquely positioned to leverage predictive analytics and increase profitability.


Read how predictive analytics can improve your airline's revenue and enhance customer experience.

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