A complete guide for Eye-Tracking testing in UX Research
This article includes a complete guide for eye-tracking testing from scratch level, including when it can be used in UX research, how can you set it up, evaluate, collect data, and analyze it?
Let me tell you a story: it’s 6 a.m. on Monday morning, and the alarm clock is ringing (brrring…!). Two brothers, Bobo and Jojo, wake up and need to get ready for school, then they go to the bathroom and brushed their teeth, but they haven’t opened their eyes since leaving their bed.
Wait for a second, they haven’t even opened their eyes yet? But how did they find the brush and toothpaste to clean their teeth? I believe some of you have either been through something similar in your lives or perhaps something else happened to you and later you realized it.
We humans frequently respond or behave unconsciously with our everyday activity as a result it became of our daily routine, practice, and the same thing happens with our digital media also. When we use Instagram to check the story, maybe we are buying something from Amazon, or watching a video on YouTube, we unconsciously communicate with them the majority of the time.
So we as researcher generally try to understand human behavior and attitudes in three ways:
- Self-Report (what users say): Self-reported measures are measures in which respondents are asked to report directly on their own behaviors, beliefs, attitudes, or intentions.
- Observational (what users do): Observation (watching what people do) would seem to be an obvious method of carrying out research in psychology and which gives a richer understanding of their behavior.
- Physiological Measures (what users' bodies do or react): It gives you another layer of information about users' unconscious behavior.
So here we will be focusing on Physiological Measures. But the question is why it is so important in UX research?
As you can see in the diagram above, if we gather three distinct types of test evidence for a person, it would be more concrete or rich information because self-report (what users say) might contain some user bias, and observational data (what users do) may contain some observer bias, but physiological measures are completely natural data since humans are unable to control their unconscious actions and behaviors. So if you are looking for some unconscious behavior of your users for your study and you want to add more solid evidence in your research data then collecting physiological measures is the crucial thing.
In this article, We will just are looking at eye-tracking in the physiological measurements category.
Eye-tracking 👀
Why Eye tracking is important in UX research?
Purpose of Eye-tracking:
- Where they are looking.
- How long they are looking.
- How their focus moves from item to item on your web page.
- What parts of the interface they miss.
- How they are navigating the length of the page.
- How size and placement of items on your existing site or on proposed designs affect attention.
let me give you an example: If you find that people aren’t clicking on the right-hand section of the banner Ad to alter the product images (image thumbnail) as seen below, how can you validate your design with the user that section is being looked at or not?
Perhaps I think you have understood the problem statement and we need to do user research in order to understand the root cause of the problem, but what method we should use?
Since we are not sure how users perceive this Ad when they looked at it suddenly or at the first time, we can’t get rich information by asking the user (user interview) why they are not clicking on this area to explore the different product images because what human say and do most of the time it will be different and we might get some bias results, hence we will be choosing Observational study and Physiological Measures (eye-tracking) to understand their unconscious behavior.
Please note: Apart from UX researsch we use eye tracking in Medical Research, PC and Gaming Research, Human Factors and Simulation, Market Research like to understand the customer’s shoping behaviour in a shop. However, in the field of user experience research, we don’t just use eye monitoring to understand users’ behavior; we integrate it with usability testing, qualitative studies, and other approaches.
Steps of eye-tracking test
Here are the below steps in order to run the eye-tracking test.
- Identify the design which you would like to validate: In this step, we would identify the problem statement and which need to validate through research.
Example: In order to understand where our consumer is looking and how they are perceiving the content in the Ad, we need to verify the above Ad (Fig-4) with an eye-tracking test.
2. Identify the eye tracker device or software: We will be identifying the technologies for eye-tracking tests in this section. There are a variety of eye-tracking systems and applications on the market, each with its own range of benefits and drawbacks. So choose the technology based on your preference.
3. Identify the metrics which you need after the test:
Common eye-tracking Metrics: There are many metrics associated with eye-tracking data. The following are the most common eye-tracking metrics used by UX researchers.
- Sequence
- Entry time (Time of first fixation)
- Dwell time or Time spent
- Hit ratio
- Revisit
- Revisitor
- Average fixation
- First fixation duration
- Fixation count (Number of fixation)
Later, I will be explaining the detailed information about the above metrics.
4. Calibrate device or software: Here we will calibrate our eye-tracking software or devices before running the test.
5. Run the test with your participants: In this step, we will be giving our participants the task and run the test.
6,7. Collect the data and analysis and synthesis: This is the most important aspect of the eye-tracking test; we will get two kinds of data from it. A. Qualitative data and B. Quantitative data. Let me give you a more detailed description.
A. Qualitative data:
- Eye moment scan path (Gaze plots): This gaze plot shows(Fig -7) how one participant processed a web page in a few minutes. The bubbles represent fixations — spots where the eyes stopped and looked at; the size of the bubble is proportional to the duration of the fixation.
*A fixations is defined by a pause in the eye’s moment within a well defined area.
- Gaze replay: This video clip is a gaze replay — it shows how one participant’s eye processed a page on the Nework Times.
B. Quantitative data:
- Heat map: This heat-map (Fig -8) is an aggregate from many participants performing the same task. The collared areas indicate where people looked, with red areas signifying the most amount of time, followed by yellow, green, and blue respectively.
- Area of interest (AOI): The most common way to analyze eye-tracking data is measuring visual attention on a specific element or region it explains how visual attention is distributed across a webpage or sense, but whether participants notice certain things and how much time was spent looking at them.
Example: (Fig -9)is an example of how to define a specific region on the page. These regions are typically referred to as “look zones” or “area of interest (AOIs)”. AOI are essentially those things that you want to measure as defined by the set of x,y coordinates.
8. Highlight the findings:
Area of Interest (AOI) visualization: It is an efficient way to analyze the eye movement data by AOIs is through a bringing chart.
AOI has can be measure with the following types of metrics:
A. Sequence: It is basically the order or sequence of gaze points in another word which section user noticed at first, second, third, and thus in a particular area.
Example: If a user notices a button a first on a page then the Sequence of that area is 1.
B. Entry time (Time of first fixation): During the total test time when the user’s eyes go in a particular element or area then that’s the entry time of that element or area.
Example: If a user notices a button in 2 seconds after loading the page, then the Sequence Entry time is 2000 ms.
C. Dwell time: Dwell time is the total amount of time spent looking within the AOI. This includes fixations and saccades within the AOI, Including revisiting.
Generally the greater the dwell time, the greater level of interest in AOI. As a general rule of thumb, dwell time less than 100 ms participants processed a limited amount of information. A dwell time greater than 500 ms generally means the participant had an opportunity to process the information.
D. Hit ratio: It is a percentage of participants who had at least one fixation with the AOI. In other words, this is the number of participants who saw the AOI.
Example: In Fig-11, 13 out of 13 participants (or 100%) were fixed within the particular AOI.
E. Revisit: Revisits are the number of times that the eye fixates within an AOI, leaves the AOI, and returns back to fixate within the AOI.
Revisits indicate the “stickiness” of the AOI.
F. Revisitors: It is the number of people who revisit within an AOI.
Example: In Fig-11, 8 out of 13 participants revisits within the particular AOI.
G. Average fixation (Fixation duration): The average fixation duration tells you how long the average fixation lasted and can be determined for either individuals or for groups.
Fixation durations typically range from 150 ms to 300 ms, it gives the relative engagement with the object. The greater the average fixation duration, the greater level of engagement
H. First fixation duration: The first fixation duration provides data about how long that first fixation lasted.
If a participant has a short Entry time or Time of First Fixation, and long first fixation duration, the area is in all likelihood very eye-catching, in other words, that section easily grabs users’ attention and the attention period is more.
I. Fixation count (Number of fixations): It is the total number of fixations with an AOI.
This is strongly correlated with the dwell time.
Pupillary response 👁
It is closely related to the use of eye-tracking in UX research is the use of information about the response of the pupil. The most eye-tracking system must detect the locations of the participant's pupil and calculate the diameter to determine where s/he is looking. Consequently, information about pupils' diameter is included in most eye-tracking systems.
When does pupil size change?
The study of pupillary response, or the construction and dilations of the pupil, is called Pupillometry, and construction and dilations happen because of some common following reasons:
1. Ambient Light: The Pupil contract and dilates in the response to the Ambient Light. The normal pupil size in adults varies from 2 to 4 mm in diameter in bright light to 4 to 8 mm in the dark.
2. Photographs: Pupils of both sexes dilated after seeing pictures of people of the opposite sex. In females, the difference in pupil size occurred also after seeing pictures of babies and mothers with babies.
3. Cognitive load: Pupillary responses can reflect activation of the brain allocated to cognitive tasks. Greater pupil dilation is associated with increased processing in the brain.
4. Interest: If the brain found something to interest then the pupil dilates, in other words, the greater the interest level is the larger pupil size.
As a result, by measuring the diameters of users’ pupil, we can determine how enjoyable our design is, how they are comfortable or stressed, and how much cognitive load is needed while they are seeing or using this.
Well, now you have got enough information about eye-tracking testing and it’s time for your turn.
Please comment below if you have any doubts or facing any issues while you are doing your own eye-tracking test.
All the best!
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