Article Summary:
Air France-KLM has successfully implemented “Advanced Airline Profile” filtering technology from Amadeus, which blocks 70% of irrelevant traffic to its system. This technology, powered by machine learning, aims to help airlines manage search traffic as New Distribution Capability (NDC) volumes increase. The implementation has enabled Air France-KLM to focus on relevant NDC shopping requests, resulting in higher conversion rates, lower system strain, and a smoother experience for travelers. Maxime Boussard, NDC program director at Air France-KLM, highlighted the benefits of sharper performance, more meaningful queries for travel sellers, and an improved traveler experience.
Key Points:
- Air France-KLM implemented “Advanced Airline Profile” filtering technology from Amadeus to block 70% of irrelevant traffic.
- The technology, powered by machine learning, went live with two airlines in May.
- The aim of the technology is to help airlines manage search traffic as NDC volumes increase.
- The implementation has led to higher conversion rates, lower system strain, and a smoother experience for travelers.
- Maxime Boussard, NDC program director at Air France-KLM, emphasized the benefits of sharper performance and a smoother traveler experience.
Actionable Takeaways:
- Adopt Advanced Filtering Technologies: Airlines should consider adopting advanced filtering technologies, such as the “Advanced Airline Profile” from Amadeus, to block irrelevant traffic and improve system performance. This can lead to higher conversion rates, lower system strain, and an improved traveler experience.
- Leverage Machine Learning for Traffic Management: The use of machine learning in filtering technologies can help airlines manage search traffic more effectively as NDC volumes increase. This can result in sharper performance, more meaningful queries for travel sellers, and a smoother experience for travelers.
- Focus on Relevant NDC Shopping Requests: By focusing on relevant NDC shopping requests, airlines can enhance their conversion rates and provide a smoother experience for travelers. This can lead to a competitive advantage in the travel industry.
Contextual Insights:
The implementation of advanced filtering technologies, such as the “Advanced Airline Profile” from Amadeus, reflects the ongoing trend of leveraging technology to improve efficiency and customer experience in the travel industry. As NDC volumes continue to increase, airlines must adopt innovative solutions to manage search traffic effectively. Machine learning plays a crucial role in this process, enabling airlines to focus on relevant NDC shopping requests and enhance their conversion rates. This trend is likely to continue, with more airlines adopting advanced filtering technologies to stay competitive in the market. The use of machine learning in traffic management also highlights the importance of data-driven decision-making in the travel industry, as airlines leverage data to optimize their operations and improve the traveler experience.
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