In the past, eye tracking was seen as a niche, expensive technology with very limited application. However, eye tracking has become more accessible and now has use cases that include controlling an iPhone using just your eyes, the design of VR headsets, playing video games, sports performance analysis, and even driver safety features in cars.
There’s still some debate though about the utility of eye tracking in UX research. Some people feel that eye tracking research remains too expensive to conduct and yields inconclusive results.
This post describes how eye tracking works, its application in UX research, and whether advances in technology have made eye tracking more affordable for UX research.
Keep your eyes peeled!
Eye-tracking is a technology that records and generates data based upon eye movements. The information allows you to see where users are looking on screen, what caught their attention, and what they missed or skipped.
This lets you know if users are noticing your key messaging and call-to-action buttons, along with other key UI elements. Eye tracking can be used to monitor eye movements on videos, static adverts, and websites. This makes eye tracking an important method for content testing.
Additionally, the technology doesn’t just tell you where users are looking, but also how long they’re looking for. This gives you an understanding of what grabs users attention, as well as what they overlook.
Eye tracking data tells you not only where users are looking, but also how long they’re looking for. Additionally, it helps you understand:
With this information, you can identify if users are noticing key UI elements such as messaging and call-to-action buttons and move to fix:
Eye testing can be incorporated into the testing process at any point, whether at the start, middle, or end of a project. You can test early concepts with low-fidelity wireframes, and use prototypes for core usability testing at the mid-point of a project.
Apart from usability testing and interface design, you can also leverage eye tracking in several other areas of the design process:
Eye tracking works through the combination of three key factors: the fovea and parafovea, fixations, and saccades.
The fovea is a small spot on the retina responsible for fine, detailed vision. Eye tracking detects where a person’s fovea fixates and the movements in between fixations (infrared light is used to identify corneal reflections called PCCR). The parafovea — the area just outside the fovea — provides peripheral vision to determine where to fixate next.
Users focus their eyes on areas known as “fixations.” Fixations describe periods when the eyes are relatively stationary because they’re taking in information. Fixations range in duration from 60 milliseconds when reading to several hundred milliseconds when examining photographs or images.
Some of the most commonly used fixation-related metrics include:
Saccades are rapid eye movements that occur between fixations. They represent periods of visual search when specific information acquisition isn’t taking place. The direction and distance of saccades are indications of:
You can collect eye tracking data through the following methods.
Gaze paths represent the summation of fixations and saccades over time. These “scanning patterns” can indicate which areas caught the user’s interest, while longer, more circuitous routes often signify confusion or a lack of direction with the viewing task.
Use a heatmap to visualize the data: areas in green show where some users looked, whereas red areas display where the most fixations happened:
Blinking can be a good indicator of attention: You blink less when paying attention and more when attention wanes. To use this method, record:
Pupillometry describes pupil size and its changes. Most eye tracking systems measure pupil size as a byproduct of monitoring eye movement. Unlike with goal-directed visual search, your pupil dilation isn’t under voluntary control. Pupils dilate in response to:
Because of this, changes in pupil diameter can be a useful measure of selected cognitive and emotional reactions to stimuli in real time.
The biggest drawback of eye tracking is that it doesn’t capture peripheral vision very well. Peripheral vision makes up 98 percent of your visual field, and you use it to choose where to fixate your fovea next. For example, powerful cognitive phenomena like satisficing can be leveraged by engaging your peripheral vision.
Also, by itself, eye tracking cannot tell you why someone is looking at something. It can tell you what they see, but not necessarily their conditioning or habits they perceive by. For example, most users skip areas on a page where banner ads are placed (such as the right side) or by their shape based on previous experience.
Other issues with eye tracking technology include:
Given these short-comings, eye tracking should ideally be used alongside other types of behavioral and attitudinal data. Be aware that questions and tasks can influence participants’ attention, making eye tracking data even less objective.
Think through your study before you embark on it. Like any data research, a complete, well-thought-out plan with clearly defined objectives and hypotheses is essential.
Eye tracking isn’t a very flexible method (unlike an interview or a usability test, where you can adjust your script on the go). If something goes wrong, you have to start over again. So take your time to plan and think about the research questions, the hypothesis, the testing environment, the tools, participants and tasks thoroughly.
To conduct an eye tracking study, follow these steps:
When recruiting, consider that there will be some unsuccessful sessions for many reasons, such as failed calibration or the participants not keeping their heads in one position. Accuracy depends on the tool and method — it’s possible that one out of five sessions will not yield usable data.
While eye tracking offers the most precise measure of visual attention, alternatives may provide a more general understanding. Some alternatives, like mouse tracking, are readily available, while others may require specialized equipment or software. The type of information needed determines which alternative is most suitable.
Some alternatives to eye tracking are:
An area of innovation to watch out for is eye tracking using mobile-phone cameras. As phone cameras improve rapidly and with open-source software, the cost of eye tracking research could become almost free in the future.
In UX research, eye tracking involves observing where test participants focus on and the order in which they navigate content. This is based on phenomena like fixation, saccades, blinks and pupil dilation.
Gaze patterns identified by eye tracking data can be used to generate charts like heatmaps. Interpreting this data can assist the placement of UI elements, understand if your interface is too cluttered, and leverage peripheral vision to suggest further information journeys.
The applications of eye-tracking in UX are diverse and span multiple areas, from usability testing and interface design to marketing, accessibility, research, and education. However, eye gazing technology is far from perfect. Not only is it expensive, it struggles to map peripheral vision. Ideally, eye tracking analysis should be used (if at all) to complement other research methods, such as collecting behavioral and attitudinal data.
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