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Technology and AI have revolutionized countless facets of the airline business over the past few years, including back-end operations, revenue management, and customer service. However, for the last several decades, flight search has largely remained the same.
As airlines and travel sellers seek solutions to customers’ flight-search frustrations, data fragmentation is a central issue. According to Jason Song, founder and president of PKFARE, today’s search experience is partially limited by existing flight-search algorithms, which underutilize the vast amounts of traveler data available and seldom recommend a tailored result suited to travelers’ individual needs.
Furthermore, data formats across airline distribution channels need to be standardized. Airlines often provide different flight availability and pricing across direct channels (e.g., their websites) versus third-party platforms like online travel agencies (OTAs) or Global Distribution Systems (GDS). This fragmentation makes it difficult for ticket sellers to offer an easy-to-compare view of all available options.
“The airline industry is lacking the data services and technology needed to meet passengers’ diverse demands effectively,” Song said.
To solve these issues, the industry is turning to emerging AI technologies to close the gap between what customers want to see and what ticket sellers have been able to offer them until now.
Closing the Traveler Data Gap
The travel industry is highly reliant on search giants that ticket sellers say are complicating the process with too many options. Enhancing ticket sellers’ ability to access and interpret all relevant traveler details — and provide them in increasingly customer-friendly ways — is crucial to overcoming the hurdle.
“Flight searches often present up to 200 options, requiring passengers to sift through excessive choices,” said Song. “This significantly increases the effort required for passengers.”
The latest generation of natural language AI tools can help address the problem of missing traveler data, offering increasingly tailored results based on individual preferences like family seating, loyalty status, and specific in-flight amenities. By leveraging existing traveler data to create a variety of search scenarios using generative AI, airlines and OTAs can enhance personalization, which could lead to higher loyalty and increased conversions.
For example, proactive AI-driven flight search solutions based on a specific traveler’s profile can unlock opportunities to capture a sale based on a clearer picture of travelers’ details and needs. A flight search may not immediately recognize the needs of a loyal business traveler who typically books for herself but is now shopping for a family vacation. However, if the customer shared with an AI assistant that she has two kids traveling with her, it could combine loyalty offers alongside a travel package that offered seats together, kids’ meals, extra luggage, and more.
“AI enables differentiation strategies,” Song said. “For example, for the same family travel query, the airline could also give you a family-rate discount voucher for hotels on this journey. [These types of personalized options] will also make you go back to the same airline next time.”
How AI is Overcoming Airline Distribution Data Challenges
The fragmentation of airline distribution data is a systematic issue that requires industry-wide collaboration to normalize various datasets for optimizing search capabilities. Generative AI can enhance the collection, normalization, and analysis of supply data, which can then be packaged as a carefully organized and easy-to-compare offering for passengers.
In addition, generative AI is revamping how sellers solve inconsistent availability. AI can combine flights from multiple low-cost carriers to offer more effective and efficient options than traditional search engines.
“If you plan to travel to Singapore and Hong Kong, journeying from Atlanta, you would naturally think that’s three tickets, one ticket to Hong Kong, one from Hong Kong to Singapore, another from Singapore back home,” Song said, giving an example.
“However, if the AI finds out Cathay Pacific, based in Hong Kong, or Singapore Airlines, based in Singapore, is providing a free stopover option,” he continued, “there could be only one ticket that permits you to stay in Hong Kong or in Singapore for one day to take a meeting, and it could even compare different stopover choices to save money and time.”
The Next Frontier for Flight Search
Generative AI offers significant potential to create interactive dialogues based on passenger needs, which will help optimize the search process. So far, no search engine has been able to drive meaningful innovation in this area, and airlines and travel sellers can seize the opportunity.
“Over the past 10 years, PKFARE has accumulated a vast amount of data on user search requests, flight solutions, ancillary services, and airline change and refund rules,” Song said. “We will use the data to train and develop the most effective algorithms and solutions, better facilitating travel sellers and catering to the end user.”
As it leverages supplier and traveler data, PKFARE aims to build on its existing data resources by expanding direct connections with airlines, which will help them gain deeper insights into their offerings, gather valuable market feedback, and better package their services to fulfill traveler needs. Additionally, PKFARE will integrate traveler shopping data from its parent company, DerbySoft, to validate the search experience across both flight and hotel sectors.
AI has the potential to enhance customer satisfaction, increase revenue, and differentiate airfare sellers. Investing in these technologies to improve the search experience is essential to staying competitive in the rapidly evolving airline business.
For more information about PKFARE’s flight search services, click here.
This content was created collaboratively by PKFARE and Skift’s branded content studio, SkiftX.
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