“Go your own way”: the user experience during traveling

"Go your own way"
the user experience during traveling

The Question: How can we measure user experience during traveling?
Noldus Consultant: Patrick Zimmerman, PhD
Case study write up: Patrick Zimmerman, PhD

Research shows that when people have to queue at the checkout counter, or while waiting for a bus or a train, the actual time spent in the queue is often shorter than the perceived time spent waiting. A phenomenon called “peak & end rule” plays an important role in these circumstances: any negative feelings caused by waiting will potentially be overruled by the positive effect of the queuing ending.

The Noldus Method

Given this “peak & end rule”, it is important to measure the user experience of a traveler during the journey; otherwise, you only measure the user’s response to the end of the journey. The journey gets washed out by the end of the experience. This is where our expertise in carrying out unobtrusive observations on naturalistic human behavior comes in handy.

The Noldus Solution

We conducted a pilot project called “Go your own way”, in which two participants were asked to travel via train from their homes in Amsterdam to the center of Utrecht. They were instructed to buy a beverage, a snack, and a birthday present at Amsterdam Central station prior to boarding the train. One participant was put under time pressure, while the other was free to travel at his own pace. Both participants were equipped with the following devices:

  • Tobii Pro eye tracking Glasses for scene recording (using the built-in camera). This provided us with the exact location of the participant and a capture (with a gaze overlay recording) of what the participant was looking at during the whole trip.
  • TomTom sports watch to measure heart rate and GPS location of the participant.

All data was synchronized in The Observer XT software which allows for accurate data synchronization and powerful data analysis.


Based on the scene and gaze overlay recordings, we manually coded the pertinent activities and locations of both participants during the whole journey. Although we ensured that both participants knew Amsterdam Central station equally well, the ‘time-limited’ participant seemed less sure of location, as he checked the route-signs more frequently than the ‘free’ traveler.

The combination of heart rate measurement and scene recording showed that changes in heart rate were purely the result of changes in activity (walking vs. standing or browsing in a shop). The time spent walking through Amsterdam Central was greater for the ‘free’ participant compared to the time-limited one, simply because the free participant had more time to do the shopping.

The scene-recording video showed that the time-limited participant had great difficulty buying a train ticket due to a faulty ticket machine. This was clearly reflected in the time spent buying a train ticket between the participants.

However, as the “peak & end rule” predicts, this was not reflected in the final evaluation score of the whole journey, which was 10-out-of-10 for the time-limited traveler and 8-out-of-10 for the free traveler. Despite the difficulty encountered, the time-limited traveler gave a better rating to the overall experience than the free traveler.


  • The Insights

Despite the pilot nature of the project, and the inclusion of only two participants, the results clearly show that by observing a traveler during a journey we can capture things that would go unnoticed by a questionnaire after the trip.

Using eye tracking glasses allows us to see what a participant is looking at (which products in a shop, what billboards) during their journey; when combined with detailed behavioral observations, we as user experience researchers can have better insights into the complete traveling experience.



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