We’re introducing a new section called “Ask the Expert.” We’ll use this periodic feature to answer some of the common questions related to airline data and air service development that we hear from our customers and industry colleagues. We also invite our readers to submit their own questions to: info@airlinedata.com. We’ll compile your feedback and answer your questions in the months ahead. We’ll always ensure our answers are informative and interesting without all the techno mumbo-jumbo. However, if you ever want more in-depth information, or if you have any comments you’d like to share, you can always reach us at the same info@airlinedata.com address.
This month’s question is about airport leakage studies:
“All the catchment studies I’ve seen analyze originating traffic leaking from my home airport. Is it possible to quantify inbound leakage, which I define as traffic from out-of-town that is flying into nearby airports instead of mine?”
The answer is a resounding YES.
We’ll cover the details shortly, but first it’s helpful to understand the evolution of the data used for leakage analyses. Several years ago, the most common approach used MIDT-based data. This approach analyzes the zip code locations of travel agencies booking tickets. Early on, it was one of the few insights commonly available to airports, airlines, and consultants alike. However, it has some drawbacks: 1) it generally does not include data from low-cost / ultra-low-cost carriers or tickets booked directly through an airline’s web site, 2) it’s based on booked, not ticketed, data (so you might have “phantom” bookings in the data), and 3) the zip codes are agency-based – not passenger based. This means the data requires a lot of adjustments – some of it more art than science – to account for these gaps.
In recent times, additional sources have come onto the market offering actual ticketed information. These sources have the added benefit of providing purchasing zip codes rather than the agency-based zip codes, and they have evolved to become a very common source of many leakage studies today. However, similar to MIDT-based studies, they have their drawbacks: 1) most low-cost and ultra-low-cost carriers are excluded, 2) they do not contain bookings made directly through an airline’s web site, and 3) transactions from certain credit cards types might not be part of the data.
In all cases, the traditional data types described above lack the ability to assess inbound leakage on a stand-alone basis. This is because they are limited by the information contained in a passenger booking or ticket. These sources can pinpoint where a ticket was purchased and what airport a passenger used to start a journey, but what about the other end of the ticket? What if you want to know about the people coming into your region using a competing airport, but who are vacationing or doing business near your airport instead? What if you want inbound or outbound leakage information for low-cost / ultra-low-cost carriers?
New solutions on the market from multiple vendors now offer internet browsing-based data that can answer these questions and more, including estimates for direct bookings to airline web site webs. Our newest product, Airport Catchment Analytics, takes this internet browsing data approach one step farther. We combine commonly-available internet browsing-based data with Hospitality Industry information and our own adjusted DOT flown data. This provides airports with an innovative approach to both outbound and inbound leakage analyses that fills in the gaps without the need for intensive adjustments. Whether it’s traditional outbound leakage insights, quantifying inbound leakage, or better understanding the impact of passenger leakage on low-fare / ultra-low-fare carriers, adjusted internet browsing-based data sets are blazing new frontiers, and the possible applications to leakage analyses are endless.
If you are curious on what this new internet browsing-based leakage data may look like and how it can enhance your business case, contact us to schedule a demo at info@airlinedata.com.
