Eye tracking is a popular research method for identifying which images or words capture people’s attention. It is widely used by market researchers, designers and psychologists to gain insights into complex cognitive processes, such as why people look at a specific point first, or the order in which they view a series of images. However, eye tracking alone can’t tell us the underlying reasons for people’s viewing behavior. In this post, we’ll explain how previous research results and individual interviews can be used to clarify these reasons and turn the raw data generated by eye trackers into usable research results.
Who uses eye tracking data?
Eye tracking is extremely popular with market researchers who want to understand where viewers will look first on a given space, and why. By analyzing the effect of advertisements on various test subjects, marketers can design more effective ads. The same concept applies to a wide range of designers in the creative and visual space, from graphic designers to artists and video game developers. The main benefit of eye tracking is unquestionable: it can precisely identify what drew the attention of a test subject and what they avoided altogether.
A brief history of eye trackers
According to research from EyeSee, eye movement studies began as early as 1879 with simple naked-eye observations. The first eye tracking device was invented in 1908 by Edmund Huey and the seminal text – “Eye Movements and Vision” was published in 1967. Research into eye-tracking flourished throughout the 1970s and 1980s when computers became powerful enough to support real-time eye tracking.
By the late 1990s, advertising agencies such as EURO RSCG were using eye-tracking data to help design more effective online ads, graphics and buttons. Throughout the 2000s, eye tracking helped businesses and scientific organizations gain insights into human behavior.
During this time, a small Swedish startup – Tobii – steadily grew from a simple ‘garage’ operation in 2001 to become one of the world leaders in eye tracking technology today. Tobii has regularly developed both its support software and its product range over the years and has won numerous awards for its technology and innovations, business and entrepreneurship.
Other companies such as SensoMotoric Instruments (SMI) and LC Technologies have produced similarly valuable eye tracking solutions. The Facial Action Coding System uses eye-tracker technology together with a facial movement detector to recognize basic emotions to evaluate the emotional state of the research subject. Other devices, particularly the Gazepoint eye-tracker, have seen widespread use and adoption.
Key insights from eye tracking research
In 1879, French ophthalmologist Louis Émile Javal became the first person to observe that readers’ eyes make fast movements (saccades) and short pauses (fixations) as they move through a text. This observation underpinned the study of eye tracking and it was only following the advent of modern computing that researchers could gain more precise insights.
For example, in 2006, Jakob Nielsen identified that our eyes follow an F-shaped pattern when we read web content. Nielsen observed that readers pay more attention to the first sentences in a paragraph and don’t read every word. He also discovered that readers often leave a page if they don’t see what they want within the first few paragraphs. Nielsen’s research was repeated and confirmed, but further studies revealed that most readers over the age of 60 read online content as if they were reading a newspaper, whereas younger age groups do not.
Nielsen’s research helped advertisers and retailers design store interiors that would help boost sales. Advances in eye trackers themselves also helped with data collection. Whereas early solutions involved the research subjects wearing bulky eye cameras, both Tobii and Gazepoint developed featherlight eyeglasses that can record where people look with pinpoint accuracy.
Modern eye tracking glasses can give accurate data about people’s behavior, perception, attention and interest in anything they see. This can include printed text and images such as newspapers, magazines and billboards or any screen interface such as computers, laptops and mobile devices. This data is hugely valuable to any company or researcher who wants to understand how to capture someone’s attention and prevent them from losing focus.
What are eye tracking results and how do you interpret them?
Eye tracking data covers three main areas in determining the efficiency of any visual interface.
- Which area(s) drew the attention of the research subject?
- What was the viewing sequence?
- Which areas drew the most attention and which were ignored?
To measure these three areas, eye trackers will count the number of saccades and fixations. As eye trackers generate a large set of data, these data sets can be presented as a graphical matrix. Data from multiple test subjects can be averaged to display a summary as aggregated data. There are two main ways to present this data: opacity maps and hotspot maps. These are examples of scan-path analysis images and we’ll briefly explain each one.
What are opacity maps?
Opacity maps, or focus maps, show which areas of a page receive the greatest number of fixations. The entire image is blacked out and the areas of interest are revealed. The below image reveals where most test subjects looked on a sample webpage. The opacity map indicates the degree of attention that participants paid to each area.
What are scan-path analysis images?
The duration of a person’s fixations is revealed by scan-path analysis images. The following scan path analysis image shows the length of fixations: the larger the circle, the longer test subjects looked at the given area. The image shows that no one paid any attention to the logo in this advert!
This scan path analysis image show which areas of the web page received the most fixations. Knowns as a hotspot image, different shades of blue indicate the areas attracting the most attention. The darker blue circle in the top left of the following image indicates that this area attracted the greatest degree of visual attention.
How do researchers use eye tracking results?
One of the most common techniques for using eye tracking data is to test the results of multiple images and arrangements and compare them to see which is most efficient. Images of human eyes and human faces draw the most attention and the direction of someone’s gaze carries significance. Research shows that participants always look into the person’s eyes first or at the person or object that the person is looking at.
The following image from Eyetrackshop illustrates the differences in saccades and fixations made by male and female test subjects. The red hotspots around the woman’s face and eyes show that this area was the first and most important target of the viewers’ gaze.
How are eye-tracking research studies designed?
To prepare and conduct an efficient eye tracking research study, you need to first decide whether you want to analyze hotspot images individually or use aggregated images for analysis. When analyses one by one, hotspot images from 5 to 8 participants qualify as qualitative research. To obtain aggregated data for quantitative research you would need 39 participants. The type of visual interface – online or offline – also makes a difference in how you design your study.
As ophthalmic and multifocal eyeglasses may be unable to properly calibrate the eyes of certain test subjects, it is important to invite more participants to the test than you need. Also, given that research results indicate over-60s view online interfaces differently, you need to accommodate their needs if they are part of the target group. Research shows that people in this age bracket have greater difficulties interpreting icons and prefer stable page layouts. Given our aging society, the over-60s will become an increasingly important target group.
How do you analyze eye-tracking images?
Although eye tracking results will reliably indicate where people looked, how long for and the order in which they looked at various areas, researchers can easily draw false conclusions from the data without additional knowledge. Current best practice is to focus on two main areas: what tasks were the participants asked to undertake and what were their reasons for looking? We’ll briefly explain these two factors separately.
Consider previous research and instructions
To interpret eye tracking results effectively, you must take into account the task the participants were asked to undertake when analyzing eye-tracking results. What were they asked to look at or do? What instructions were they given? How long did they have?
Conduct a personal interview
Eye tracking data often indicates that test participants returned their gaze to one particular spot. It’s worthwhile talking to the subjects briefly to ask them about their experiences. Of course, no one is able to recall their eye movements, by you can obtain useful data by discussing with them what they saw.
For example, the following image shows saccadic eye movements on a web interface and demonstrates how content can lead the eyes of test participants. You may find that participants had preconceived ideas and expectations (a mental model) about what information they expected to find and where it would be located.
While eye-tracking devices yield extremely accurate data by recording the gaze of test participants, research shows that the data alone cannot reveal the underlying reasons as to why people choose to look where they do. Prior research and brief interviews with the participants can help to clarify the data and draw more accurate conclusions. Eye tracking data cannot be separated from an understanding of what the participants were asked to do or look at when they took the test. Ultimately, this is what will turn colorful hotspot images into usable research results.