How many times have you tried to book a ticket online and got frustrated by all the options and the cluttered information? Though travel sites embrace the importance of usability and constantly try to improve their sites, still they often fail to deliver a great customer experience (reference). The reason, in many cases, is that the goals of the travel site and that of the user conflict. You might be stressfully looking for a last-minute ticket to see your loved one, while the travel site wants to sell you a package of vacations to Mallorca. It’s not the right moment, but the travel website unfortunately doesn’t know it, and craves to convert… Result? FAIL!
Due to these conflicting interests, travel sites are always a great topic for usability analysts. In this case, I only wanted to test where do users click to select the cheapest ticket. A crucial point for travel websites to convert and keep users happy. For the purpose of the study I selected four popular travel websites that I often use myself:
eDreams, Travelocity, Hipmunk and Cheaptickets.
The 4 travel websites
I quickly set up four, identical, independent Usabilla tests -one for each website- recruiting participants via Twitter and our monthly newsletter.
Number of participants per test
In the tests I described a scenario to the participants: “Assume that you’re planning a round trip flight from Amsterdam (AMS) to San Francisco (SFO). Departing on the 1st of July and returning on the 10th of July.” And asked them to perform a one-click task: “Where do you click to buy the cheapest ticket?”
A fairly easy task, but how did the four websites score?
Participants clicked where they thought they could buy the cheapest ticket, and Usabilla visualized the actions with heatmaps (participate yourself in one of the tests)
In total I recruited 262 participants, out of which 235 participants completed the task. Completion rate: 90.5%
I decided to rank the four websites against two metrics:
- Metric 1: Time to complete task – How fast can participants find the cheapest ticket?
- Metric 2: Success Rate – What percentage of the participants clicked on the desired area?
Time to complete a task
Hence, the mean time to accomplish the given task varied between 15.5 s (Cheaptickets) to 24.3 s (Travelocity). A significant difference of 56.7% that proves Cheaptickets as the big winner against the “time to complete task” metric. Hipmunk followed with 19.1 seconds, eDreams came third with 21.9 seconds and Travelocity performed the least with 24.3 seconds.
But how did the four sites score against the Success Rate metric? Did participants click where I wanted them to click? To measure the successful clicks I used a Google spreadsheet that Paul created in Google Docs. The spreadsheet allows you to export the points from your test to a Google Docs spreadsheet, and focus on the clicks that matters to you. You can also do the same with notes ( for more details read this blogpost).
By defining the successful areas for the four websites on the spreadsheet, I could measure the Success-Rate (successful clicks to total clicks).
Cheaptickets scored 29.7%, Hipmunk 21.7%, Travelocity (19%) and eDreams (13.3%). Only 1 every 8 participants clicked on the desired area for eDreams.Very low Success-Rate…
To declare a winner for this test I decided to weigh the two metrics the same, and reward with 4 points the first, 3 points the second, 2 points the third and 1 point the last of each test. Summarizing the results in the following table, the winner is…Cheaptickets scoring the absolut 8 points in the two metrics!
|Website||Metric 1: Time to complete task (s)||Metric 2: Success-Rate (%)||Total score (points)|
Task: Where do you click to buy the cheapest ticket?
But why did Cheaptickets score better than the rest? Looking again at the four websites, Cheaptickets is the only one that presents in a table, a quick overview of the tickets according to price and then breaks down each single ticket into detail. Users can easily scan the table and quickly go for the cheapest one (or the one with no stops etc.). Concluding from this test, a ticket table seems to improve the time to find a ticket as well as the succes-rate significantly.
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