The airline industry is experiencing a transformation in retailing strategies to meet the growing demands of modern travelers, who seek customizable options, pricing transparency, and convenient ways to manage their travel plans. This shift is being driven by offer and order management, with the integration of artificial intelligence (AI) playing a key role in reshaping how airlines market their services and how passengers experience air travel. By leveraging AI-powered retailing platforms, airlines can present personalized offers to customers, enhancing the overall travel experience and driving revenue and profitability.
Ancillaries have become essential for airlines looking to offer customizable experiences to travelers. Ancillary revenue streams have surged in recent years, with travelers seeking to personalize their travel by selecting seats, meals, in-flight entertainment, and additional services. Offer and order frameworks powered by AI enable airlines to tailor their service offerings based on individual customer data, optimizing revenue through targeted ancillary sales. By leveraging real-time context and historical insights, airlines can deliver relevant pricing and products, improving customer satisfaction and loyalty.
Pricing transparency is crucial in meeting traveler expectations. With the unbundling of services, airlines must ensure that their pricing is clear and straightforward to avoid surprising customers with hidden fees or unexpected costs. Automated pricing rules driven by AI platforms like PROS streamline operations and minimize pricing errors, leading to optimal revenue generation and better resource allocation. Transparent pricing builds trust with travelers, who expect a comprehensive breakdown of costs to make informed decisions without hidden fees.
AI plays a transformative role in airline retailing by analyzing vast amounts of data to predict customer preferences and behavior. This personalization extends beyond seat and meal preferences to dynamic pricing, optimizing offers and pricing of ancillary services based on demand and customer needs. By utilizing state-of-the-art cloud technology and machine learning frameworks, AI-powered platforms like PROS can deploy dynamic pricing models that are flexible and highly scalable, enabling airlines to serve millions of customers daily with personalized offers and services.
case study, airBaltic leveraged AI-powered dynamic ancillary pricing to enhance their retailing strategy and drive profitability and customer engagement. By applying AI technology to optimize seat selection offers, airBaltic saw a 6-percent increase in ancillary seat revenue and higher customer satisfaction. The success of this implementation led airBaltic to expand the use of AI technology throughout their network, resulting in increased profitability and customer engagement. Similarly, Lufthansa Group partnered with PROS to streamline revenue management across a network of nine airlines, resulting in higher conversion rates and improved customer satisfaction through Request-Specific Pricing models.
In conclusion, 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 technology, airlines can optimize revenue, enhance customer satisfaction, and build lasting loyalty. The strategic use of AI in airline retailing is not just a technological advancement but a revenue generation imperative that is transforming the travel industry. With the continued adoption of AI-powered solutions, airlines can adapt to changing customer preferences and enhance the overall travel experience for passengers.
