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Using AI and Machine Learning for Ancillary Revenue Maximization

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Ancillaries are key drivers of profit for airlines. Carriers are offering various ancillary products from traditional seat upgrades, priority boarding, baggage, airport transfers, and more, via a wide range of distribution channels. Additionally airlines are bundling ancillary products and flights to match traveler preferences. For ancillaries and fare families it is important to dynamically set the price to match travelers preferences and increase conversion rates. FLYR ancillaries allows airlines to dynamically set the ancillary and fare family prices, resulting in strong revenue strategies that optimize total revenue performance.

Ancillary Revenue Optimization at FLYR

In September, FLYR acquired Faredirect, bringing with them advanced ancillary revenue software. FLYR is now able to provide a comprehensive software solution to help maximize airlines’ commercial performance across all products and market conditions:

  • Faredirect’s technology combines multiple data sources to produce AI-powered, dynamic, revenue-maximizing strategies for ancillary and fare family prices.

Using AI and Machine Learning for Ancillary Revenue Optimization

Data proves that passengers are less price-sensitive with ancillaries than with airfares. FLYR’s AI-based Ancillary Revenue Optimization solution responds to this passenger behavior, combining historical trends and willingness-to-pay estimation. Cirrus™ determines the optimal selling price to maximize total revenue upon flight departure using deep learning technology. The platform operates on a continuous price spectrum, using the airline’s network’s full context to define an optimal price.

FLYR’s solution is capable of real-time ancillary prices for each customer shopping request or as a scheduled continuous price update into the existing shopping infrastructure. With FLYR’s Ancillary Revenue Optimization, airlines can seamlessly offer travelers the right ancillaries at the right price while optimizing ancillary and total revenue, and all within an easy-to-navigate user interface.

Find out more about how FLYR is unlocking even more ancillary revenue potential for airlines or get in touch.

The post Using AI and Machine Learning for Ancillary Revenue Maximization appeared first on FLYR Labs.


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