AI takes flight in airline pricing

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As travelers prepare for summer getaways, airlines are increasingly turning to artificial intelligence (AI) to enhance their pricing strategies and maximize revenue. Fetcherr, an Israeli startup, is at the forefront of this technological revolution, offering an AI-powered platform that helps airlines navigate the complexities of dynamic pricing.

Revolutionizing pricing with AI

Fetcherr's AI technology leverages reinforcement learning models to simulate various pricing scenarios and determine the most profitable strategies under diverse market conditions. This innovative approach has attracted significant attention from major airlines such as Virgin Atlantic, Azul Brazilian Airlines, and Royal Air Maroc.

“By predicting future market trends and optimizing pricing strategies proactively, Fetcherr’s large market model (LMM) enables high-frequency, informed decision-making,” said Roy Cohen, CEO and Co-founder of Fetcherr, in an interview with PYMNTS.

Reinforcement learning, a subset of machine learning, involves an agent optimizing its behavior through interactions with a dynamic environment, guided by feedback in the form of rewards or penalties. Fetcherr employs these models to continually improve and refine airline revenue management strategies, aiming to optimize revenue-based key performance indicators (KPIs) set by the airlines.

Addressing industry challenges

Fetcherr's rise coincides with the airline industry's struggle to recover from the pandemic's impact. For example, JetBlue has had to cut and eliminate routes in response to ongoing industry challenges as it strives to regain profitability.

Despite these hurdles, corporate travel has rebounded, mirroring the robust growth in leisure travel over the past three years. Airlines such as Delta, United, and Alaska Airlines have reported strong first-quarter results, indicating a promising recovery.

In this context, Fetcherr’s AI-powered pricing system offers a potential solution for optimizing revenue management in a rapidly evolving market. According to Cohen, the technology has led to performance improvements typically in the high single-digit percentages, with some networks experiencing double-digit gains.

Overcoming development challenges

The founders of Fetcherr, with expertise in deep learning, algorithmic trading, eCommerce, and digitization, identified a significant opportunity to apply these technologies to the airline industry. Traditional revenue management systems often struggle to keep pace with rapid market changes, a limitation that Fetcherr aims to address.

However, developing Fetcherr’s AI system was not without its challenges. The company had to navigate issues related to legacy infrastructure and data diversity. Cohen explained that they streamlined integration by creating an onboarding process that layers their AI over existing systems without causing major disruptions or requiring substantial investments. Advanced data processing technologies were also employed to normalize varied data sets, thereby enhancing AI performance and decision-making accuracy.

Broader implications and future plans

As the summer travel season progresses, industry experts and competitors will closely monitor the performance of Fetcherr’s AI-powered pricing system. Airlines using Fetcherr’s technology have reported significant revenue improvements, with some networks seeing double-digit gains. This success is attributed to the system's automation and high-frequency capabilities, enhanced by the LMM provided to revenue management teams across their operational pipeline.

Looking ahead, Fetcherr aims to expand its AI pricing solutions beyond the airline industry. “Our large market model is designed to be industry-agnostic, capable of anticipating market dynamics and simulating business cases across various sectors,” Cohen said. “While we continue to drive innovation in the airline industry, our goal is to disrupt other traditional industries as well, empowering them through AI.”

Ethical considerations and broader AI applications

The use of AI in pricing strategies inevitably raises questions about potential ethical concerns and biases. Cohen emphasized that avoiding ethical concerns and biases was integral to the design process from the outset. For instance, features with potential bias projection are excluded from the system's access from the early stages.

Beyond pricing strategies, AI applications are gaining traction across the airline industry. Delta Air Lines has partnered with Exscientia, a British AI-powered drug discovery company, to explore how AI can enhance customer experience and streamline business processes. Alaska Airlines uses AI to improve fuel efficiency and reduce emissions by optimizing flight paths and speeds. Meanwhile, EasyJet employs AI algorithms to better predict customer demand and optimize seat pricing.

Airlines are also harnessing AI to improve operational efficiency. Airbus’s AI tool “Skywise” helps airlines monitor aircraft health and predict maintenance needs, while Boeing uses machine learning to streamline its supply chain and manufacturing processes.

As the travel industry continues to evolve and adapt to new technologies, companies like Fetcherr are positioning themselves at the forefront of this transformation. The success of their AI-powered pricing system during the summer travel season could have far-reaching implications for the future of airline revenue management and the broader application of AI in business strategies.

“Fetcherr’s long-term vision is to broaden the reach of our AI technology throughout the airline industry, enhancing essential operational aspects to boost growth, efficiency, and customer satisfaction,” Cohen concluded. “We aim to create Air Commerce for the broader travel sector with dynamic pricing, advanced analytics, and comprehensive offer management.”

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