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Trust & Security: User Search Data For Airlines – Definition and Examples

User Search Data For Airlines – Definition and Examples

In a recent post about user search data, we talked about how airlines can use this data to provide more relevant experiences to customers visiting their online channels. But what exactly is user search data? Watch this 35 second video, showing an example of a booking flow where user search data can be collected and then we will talk about what exactly those data points are.

There are two different segments of user search data that can be collected in this flow:

Browser-related information (automatic)

This information is collected automatically by browsers.

Here we see the user begin at the Google search page. Notice all of the information on the SERP is in English, meaning the browser’s language is set to English.

Next, the browser knows the device that the user is searching on. In this case, this was a desktop search, meaning the webpages will be optimized for the desktop experience.

Last, the browser knows the user’s geographic location – “geolocation” – by using information from your access point to find you. This means that the search engine will try its best to give you the most geographically-relevant search results.

User-entered data (voluntary)

This data must be voluntarily entered by a user, either in a search engine or within an airline’s booking flow. This data can be used to supplement the browser-related information to provide the most relevant experience to that user.

In the example above, the user types in “flights to abu dhabi” in Google, showing the destination (“to”) that they are interested in (“abu dhabi”).

Continuing the booking flow to Etihad‘s site, we see the user has landed on a “Flights to Abu Dhabi” (user entered data) page showing all origins in the United States (browser-related information). Notice this doesn’t include an origin city because the user didn’t show clear intent about where they want to depart.

The next user-entered data points are the ones that further refine the available offers for that search request: “MIA” (Origin); “5/9/2017” (Departure Date); “5/17/2017” (Return Date); “1 Traveler” (Number of Travelers); “Economy” (Fare Class).

With this final set of data, Etihad’s booking engine is able to provide hyper-relevant flight options based on the combination of browser-related information and user-entered data.

Innovator – Lufthansa Group

“We are proud to receive the Innovator award in the PROS Outperformer Customer Awards. Over our 37-year partnership, Lufthansa Group and PROS have co-innovated advanced solutions that have transformed revenue management and pricing across our network. From AI-powered pricing and real-time offer optimization to next-generation demand forecasting, these innovations have driven efficiency, alignment, and measurable impact. As we advance with initiatives like Request Specific Pricing and Dynamic Ancillary Pricing, PROS remains a trusted partner in our journey toward smarter, AI and data-driven aviation,”