By Cory Mathews, Sales Director Americas, Aviation Week

For years, the aviation industry has worked to answer a seemingly simple question: Where are passengers actually coming from?

While the question may sound straightforward, the answer is far more complex. Understanding passenger origins influences everything from air service development and airline recruitment to infrastructure planning and tourism strategy.

To better understand passenger behavior and market demand, airports and consultants have traditionally relied on settlement data, credit card transactions, mobile device information, and cookie tracking. While these data sources provide useful insight, they also come with significant limitations.

Corporate card and settlement data can look impressive—millions of transactions, polished dashboards, and charts that make for compelling presentations. The challenge is that billing locations are often nowhere near the actual traveler.

For example, I live on Vancouver Island. If my corporate card is registered to a company office in Sarasota, Florida, and I take the ferry from Victoria to Tsawwassen, some traditional datasets can suddenly conclude that Sarasota is generating passenger demand to and from Vancouver Island. Congratulations—Florida is now apparently helping drive Canadian ferry traffic.

Then came mobile data, arguably the biggest trend in post-COVID aviation analytics. For a while, it felt like the industry had found the silver bullet. Airports, airlines, and consultants were leaning heavily into mobile datasets to explain passenger behavior and forecast demand.

While this provides valuable insight, it also has weaknesses—especially since a device is not necessarily a passenger. Other limitations include strict privacy regulations in parts of Europe, limited representation in rural markets, small sample sizes in certain regions, and inconsistent visibility across international borders. Looking at some mobile datasets, you could almost believe the Canada-U.S. border had turned into The Wall from Game of Thrones. Except, of course, passengers absolutely cross.

After evaluating a wide range of data sources, one approach consistently stood out: search data modeling. Why? Because search behavior offers something many traditional datasets struggle to provide—global scale, strong geographic visibility, and privacy-compliant insight into traveler intent. When people search online for flights, airport parking, hotels, rental cars, or destinations, they generate valuable geographic signals about where demand originates and how travelers plan their journeys.

A good example can be seen through analysis of Toronto Pearson International Airport (YYZ). Using Aviation Week’s Catchment Analyzer platform, the visualization tool highlights passenger activity extending across Southern Ontario and into Western New York, demonstrating how major hub airports often draw traffic from well beyond their immediate metropolitan areas.

The dashboard reveals where passengers are located, which competing airports they use, how far travelers are willing to drive, and which international markets are generating demand. In the YYZ example, strong international demand can be seen for destinations including London, Hong Kong, Manila, Paris, Seoul, Rome, and Istanbul.

Because the information is presented visually and interactively, complex travel patterns become significantly easier to identify, understand, and communicate. This allows airports and stakeholders to move beyond static spreadsheets toward more actionable, data-driven decision-making.

For airports, this matters more than ever.

The industry continues to face operational and strategic pressures ranging from workforce constraints and infrastructure demands to changing passenger expectations and evolving airline networks. At the same time, competition for air service development opportunities continues to intensify.

The future of catchment analysis is not about choosing one dataset over another. The strongest methodologies combine multiple perspectives to build the clearest picture possible.

As airports continue adapting to changing traveler behavior, data sources that better capture real passenger intent will become increasingly important to long-term planning, network development, and understanding the true reach of an airport’s catchment area.

With over two decades of experience in aviation, travel, and data intelligence,

Cory Mathews is passionate about helping aviation and aerospace stakeholders transform data into actionable insight — and results. He joined Aviation Week, the industry’s most trusted source of data, insight, and intelligence, in 2019. As part of Informa, Aviation Week benefits from access to deep expertise and resources across a global network of industry

specialists, enabling comprehensive solutions for clients. Cory has also held senior commercial roles at Cirium, strengthening his expertise in aviation analytics, fleet intelligence, and market forecasting. He brings strong experience in commercial aerospace, aircraft leasing, MRO, OEM strategy, and defense. cory.mathews@aviationweek.com

DISCLAIMER

This article was provided by a third party and, as such, the views expressed therein and/or presented are their own and may not represent or reflect the views of Airports Council International-North America (ACI-NA), its management, Board, or members. Readers should not act on the basis of any information contained in the blog without referring to applicable laws and regulations and/or without appropriate professional advice.