Unlocking the Power of AI Innovation in Airline Retailing

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Today’s travelers want customizable options, greater pricing transparency, and more convenient ways to manage their travel plans. As the airline industry adapts to meet these expectations, the shift toward a more personalized and efficient retailing strategy has become paramount. 

Driven by offer and order management, modern airline retailing is transforming how carriers market their services and how passengers experience air travel. At the heart of this transformation is the integration of artificial intelligence (AI), a technology that is not only reshaping the fundamentals of airline bookings but also redefining the possibilities within the travel ecosystem. 

“Offer management, powered by AI, allows airlines to present the right offer to the right customer at the right time,” said Surain Adyanthaya, president of PROS, an AI-powered airline retailing platform. “Instead of a one-size-fits-all approach, airlines can now offer bundles and ancillary services more likely to resonate with each passenger.” 

SkiftX recently sat down with Adyanthaya and Jonas Rauch, principal scientist at PROS, to explore how AI-powered retailing can help airlines drive revenue and profitability while increasing customer satisfaction and loyalty. 

How Ancillaries Enable Customization

According to Skift Research, the airline industry sold a record $118 billion of ancillary products in 2023, highlighting the growing importance of ancillary revenue streams for airlines. This surge in ancillary sales underscores the increasing demand for customizable travel experiences.

“Travelers want to personalize their travel experiences by selecting seats, meals, in-flight entertainment, and additional services,” Adyanthaya said. “Most travelers now prefer airlines that offer a personalized experience. However, this demand poses challenges for airlines constrained by legacy systems that focus on seats rather than the overall experience. Airlines can adapt to this changing customer preference with updated technology stacks that enable offer and order frameworks.” 

Offer and order frameworks enable airlines to personalize and dynamically adjust their service offerings based on individual customer data. This approach not only enhances the travel experience by aligning with passenger preferences and behaviors but also allows airlines to optimize revenue through targeted ancillary sales. By leveraging real-time context and historical insights, airlines can deliver more relevant pricing and more relevant products, creating highly relevant and appealing packages that improve customer satisfaction and loyalty.

The Importance of Pricing Transparency 

Meeting traveler expectations is not only about providing the right offers at the right time — it’s also about delivering transparent pricing. With the unbundling of services like baggage, seat selection, and in-flight amenities, airlines must ensure their pricing is clear and straightforward and avoid surprising customers with hidden fees or unexpected costs at checkout. 

“Transparent pricing builds trust with travelers, who expect a clear and comprehensive breakdown of costs to make informed decisions without hidden fees,” Adyanthaya said. “A survey by IATA revealed that 74 percent of travelers consider transparency in ticket pricing an important factor in trusting and choosing an airline. This need for pricing transparency is also being recognized by governments — many of which increasingly require the elimination of junk fees — a positive trend that is likely to continue globally.”

In addition, AI-driven platforms like PROS automate complex pricing rules, significantly reducing the manual intervention required. This not only streamlines operations but also minimizes pricing errors, leading to optimal revenue generation and better resource allocation. 

“With automated pricing rules, airlines can ensure that their teams focus on strategic tasks rather than getting bogged down with manual processes,” Adyanthaya said. 

The Transformative Role of AI

By analyzing vast amounts of data, AI can predict customer preferences and behavior, allowing airlines to tailor offers and services to individual needs. This personalization extends beyond seat selection and meal preferences — it also includes dynamic pricing, which optimizes both the composition of offers and the pricing of ancillary services like seat reservations. 

“Several factors influence dynamic pricing, including the limited availability of certain services,” Rauch said. “For example, dynamically pricing high-demand exit row seats ensures those who value them most can access them, which helps airlines use their resources more efficiently and increase revenue. It also benefits customers by allocating premium seats to those who need them most. If the airlines gave away these seats for free, someone who doesn’t need them might get them, while a very tall person, who would benefit significantly from the extra legroom, might not.” 

According to Rauch, PROS uses state-of-the-art cloud technology and machine learning frameworks to enable a dynamic ancillary pricing model that is highly flexible and can price nearly anything as long as the necessary data is available. 

“Any data scientist will tell you that developing a good model is one thing, but deploying it at scale, where it serves hundreds of thousands or millions of customers daily, is the hard part,” Rauch said. “The PROS platform handles this complexity, allowing scientists to focus on model quality while the platform ensures seamless deployment and operation.” 

How airBaltic Drives Profitability and Customer Engagement

Latvia’s flag carrier, airBaltic, significantly enhanced its ancillary retailing strategy by leveraging PROS AI-powered Dynamic Ancillary Pricing platform. 

“The first ancillary they applied it to was seat selection because that’s a very high-value ancillary, not only in revenue but in customer satisfaction,” Adyanthaya said. “The results were immediate and impressive. They saw a 6-percent increase in ancillary seat revenue because it optimized the offers presented to passengers utilizing a technique known as efficient price exploration, whereby the AI model varied in an optimal way the prices for different customer segments according to an expectation of what they were looking for. The model self-selected a compelling offer based on their response to these offers.” 

This automated A/B testing approach allowed the AI to determine the optimal ancillary prices, enhancing both revenue and customer satisfaction. The implementation’s success was evident in airBaltic’s decision to move quickly from proof of concept to full production. 

“It drove more profitability, resulted in higher customer engagement, and shortened their proof-of-concept phase because the results were so compelling,” Adyanthaya noted. “The personalized services clearly made a difference, leading airBaltic to expand the use of this technology throughout their network.”

How a Multi-Airline Network Transformed Its Pricing Strategy

Another PROS client, Lufthansa Group, faced the added complexity of managing pricing structures across a network of nine different airlines. PROS helped Lufthansa streamline its revenue management capabilities by integrating these airlines into a single revenue management and dynamic pricing instance. 

“Passengers don’t think about the traditional booking class structure,” Adyanthaya said. “They think in terms of the best price for themselves. We’ve developed our continuous pricing AI to come up with the exact best price to offer for that consumer.”

As an extension of this dynamic pricing work, PROS and Lufthansa also worked together to introduce new Request-Specific Pricing models, which adjust prices in real-time based on various market signals. Unlike traditional pricing models that offer fixed prices based on predefined fare classes, Request-Specific Pricing considers multiple factors during the booking request, including supply and demand, characteristics of the trip, and current market conditions. 

“Using AI algorithms to consider various factors of each trip request has led to higher conversion rates and improved customer satisfaction, resulting in 2- to 3-percent additional revenue growth over Lufthansa’s already high baseline,” said Adyanthaya. “We’re excited to see how this will continue to transform the travel industry in the coming months and years.” 

Unlocking the power of AI innovation in airline retailing is not just a technological advancement but a strategic revenue generation imperative. AI-driven offer and order management systems enable airlines to deliver personalized, transparent, and dynamic experiences that meet the evolving expectations of modern travelers. By leveraging AI, airlines can optimize revenue, enhance customer satisfaction, and build lasting loyalty.

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This content was created collaboratively by PROS and Skift’s branded content studio, SkiftX.