Eye tracking delivers unmatched value to market research
Why is it that some products make an impression on customers while others just don‘t get it right? Eye tracking has become a popular, increasingly vital tool in market research. Many leading brands actively utilize eye tracking to assess customer attention to key messages and advertising (TV and print) as well as to evaluate product performance, product and package design, and overall customer experience. When applied to in-store testing, eye tracking informs about ease and difficulty of store navigation, search behavior, and path to purchase.
Eye tracking can help gain deep insights into Human Computer Interaction (HCI)
So what is Human Computer Interaction? Basically, HCI refers to any kind of interaction between a human and a computer of some sort. Think laptops, tablets, smart phones, simulators. Think websites, mobile apps, virtual reality. You get the idea.
Website testing
One emerging field utilizing eye tracking as methodology is usability and user experience testing. Eye tracking for website testing is a classic. How do people attend to real estate, communication, and calls to action (CTA)? If you‘re losing out on revenue, eye tracking data can deliver valuable insights into the gaze patterns of your website visitors – how long does it take them to find a specific product on your site, which kind of visual information do they ignore (but are supposed to see)? Cut to the chase and see what exactly goes wrong. Similar applications can be applied to mobile apps on tablets and smartphones.
Simulation
Driving behavior research utilizes head-mounted eye tracking technology combined with a number of other biometric sensors in a virtual reality (simulator) to gain a better understanding of human behavior in hazardous situations while driving. Where do drivers look when they face obstacles on the street? How does talking on the phone affect driving behavior? How exactly does speeding compromise visual attention? Insights of that kind can help improve hazard awareness and, for example, be applied to safe driving trainings and the development of further electronic driving aids.
Automotive research has embraced head mounted eye tracking for a long time to gauge drivers‘ visual attention – both with respect to navigation and dashboard layout. In the near future automobiles might be able to behave responsively toward drivers’ eye gaze, eye movements or the pupil dilation.
Neuroscience & psychology thrive on eye tracking
How do expectations shape the way we see the world? If you see a picture of a living room, you most likely know where to expect the TV (probably somewhere opposite the couch). If it’s in another spot, you might be baffled and gaze around the scene since your „scene semantics” (your “rules” of how a living room should look like) are violated.
Neuroscience and psychology utilize eye tracking to analyze the sequence of gaze patterns to gain deeper insights into cognitive processes underlying attention, learning, and memory. Another research strand addresses how we encode and recall faces – where do we look to extract the emotional state of others? Eyes and mouth are the most important cues, but there’s definitely a lot more to it. Finally, eye tracking provides insights into word processing, particularly how eye movements during reading are affected by the emotional content of the texts.
Learning & education can benefit from eye tracking
Seriously, what if learning would be an equally satisfying experience for all of us? What exactly does it take to turn learning into a successful adventure? Within the recent years, eye tracking technology has impressively made its way into educational science to help gain insights into learning behavior in diverse settings spanning from traditional „chalk and talk“ teaching approaches to digital learning.
Analyzing visual attention of students during classroom education, for example, delivers valuable information in regard to which elements catch and hold interest, which are distractive or fail to be seen – do students read or rather scan slides? Do they focus on the teacher or concentrate on their notes? Does their gaze move around in the classroom? Eye tracking findings like these can be effectively leveraged to enhance instructional design and materials for an improved learning experience in the classroom and beyond.
Eye tracking is used in medical research to study a wide variety of neurological and psychiatric conditions
Eye tracking in combination with conventional research methods or other biometric sensors can help assess and diagnose neurological diseases such as Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Obsessive Compulsive Disorder (OCD), Schizophrenia, Parkinson‘s, and Alzheimer‘s disease. Besides, eye tracking technology can be leveraged to detect states of drowsiness or support multiple other fields for medical use, quality assurance or monitoring.
Gaming and UX – how come eye tracking is the big hit among a growing number of web designers and developers?
Eye tracking has recently been introduced into the gaming industry and since then has become an increasingly prominent tool as designers now are able to assess and quantify measures such as visual attention and reaction to key moments during game play to improve overall gaming experience.
When combined with other biometric sensors, designers can utilize the data to measure emotional and cognitive responses to gaming. New trends and developments will presumably render it possible soon to take an active part and control the game based on pupil dilation and eye movements.
What to look for in eye tracking data?
Like no other experimental method, eye tracking renders it possible to quantify visual attention as it objectively monitors where, when, and what people look at. So much for the hard facts. Now let‘s get practical and have a look at the most common metrics used in eye tracking research and what you can make of them.
Fixation and gaze points
Without doubt, the terms fixation and gaze points are the most prominent metrics in eye tracking literature. Gaze pointsconstitute the basic unit of measure – one gaze point equals one raw sample captured by the eye tracker. The math is easy: If the eye tracker measures 60 times a second, then each gaze point represents 16.67 milliseconds. If a series of gaze points happens to be close in time and range, the resulting gaze cluster denotes a fixation, a period in which our eyes are locked toward a specific object. Typically, the fixation duration is 100 – 300 milliseconds.
The eye movements between fixations are known as saccades. What are they exactly? Take reading a book, for example. While reading, your eyes don’t move smoothly across the line. Instead, your eyes jump and pause, thereby generating a vast number of saccades. The visual span refers to how much text we can cover between fixations – on average, saccadic movements span 7 to 9 characters along the line of text. Trained readers have a higher visual span compared to early readers. Typically, saccades are measured in angle velocity.
Now imagine watching clouds in the sky as you pass your time waiting at the bus stop. Here, expect your eye movements to be quite the opposite as your eyes steadily follow the moving clouds. Unlike reading, locking your eyes toward a moving object won’t generate any obvious saccades, but a smooth pursuit trajectory.
As fixations and saccades are excellent measures of visual attention and interest, research in this field is experiencing a significant growth.
Heat maps
Heat maps are static or dynamic aggregations of gaze points and fixations revealing the distribution of visual attention. Following an easy-to-read color-coded scheme, heat maps serve as an excellent method to visualize which elements of the stimulus were able to draw attention – while red areas suggest a high number of gaze points and therefore an increased level of interest, yellow and green areas point toward flattening visual attention.
Here you can see the aggregated eye tracking replay on a packaging study:
Based on fixation position (where?) and timing information (when?) you can generate a fixation sequence. Dependent on where respondents look and how much time they spend, you can build an order of attention telling you where respondents looked first, second, third etc. This is a commonly used marker in eye tracking research since it reflects salient elements (elements that stand out in terms of brightness, hue, saturation etc.) in the display or environment that are likely to catch attention. AOIs which respondents look at first are typically visually more appealing (more salient) and are therefore of more interest.
Respondent count
The respondent count allows to extract information about how many of your respondents actually guided their gaze towards a specific AOI. A higher count might indicate that fixations and gaze points are driven rather by external aspects in the stimulus material.
Areas of Interest (AOI)
Areas of Interest, also referred to as AOI, are user-defined subregions of a displayed stimulus. Extracting metrics for separate AOIs might come in handy when evaluating the performance of two or more specific areas in the same video, picture, website or program interface.
Time to First Fixation (TTFF)
The time to first fixation indicates the amount of time it takes a respondent to look at a specific AOI from stimulus onset. TTFF can indicate both bottom-up stimulus driven searches (a flashy company label catching immediate attention, for example) as well as top-down attention driven searches (respondents actively decide to focus on certain elements or areas on a website, for example). TTFF is a basic yet very valuable metric in eye tracking.
Time spent
Time spent quantifies the amount of time that respondents have spent on an AOI. Since respondents have to blend out other stimuli in the visual periphery that could be equally interesting, time spent often indexes motivation and conscious attention (long prevalence at a certain region clearly point to a high level of interest, while shorter prevalence times indicate that other areas on screen or in the environment might be more catchy).
Advanced eye tracking metrics
With the core tools at hand, you‘re perfectly equipped to track the basics. Where, when and what do people look at? What do they fail to see? So far, so good. Now how about pushing your insights a bit further and stepping beyond the essentials of eye tracking? Want to peek beneath the surface? Sweet! Advanced metrics can help reveal emotional arousal and valence.
These 4 eye tracking metrics should definitely make it into your toolkit so you can draw the bigger picture.
Pupil size / dilation
Pupil size primarily responds to changes in light (ambient light) or stimulus material (e.g. video stimulus). However, if the experiment can account for light, other attributes can be derived from changes in pupil size. Two common properties are emotional arousal and cognitive workload. An increase in pupil size is referred to as pupil dilation, a decrease in size is called pupil constriction. In most cases pupillary responses are used as a measure for emotional arousal. However, be careful with rash conclusions as pupillary responses alone don’t give any indication of whether arousal arises from a positive (“yay“!) or negative stimulus (“nay!“).
Distance to the screen
Along with pupil size, eye trackers also measure the distance to the screen and the relative position of the respondent. Leaning forwards or backwards in front of a remote device is tracked directly and reflects approach-avoidance behavior. However, keep in mind that interpreting the data is always very specific to the application.
Ocular Vergence
Most eye trackers measure the positions of the left and right eyes independently. This allows the extraction of vergence, i.e., whether left and right eyes move together or apart from each other. This phenomenon is just a natural consequence of focusing near and far. Divergence often happens when our mind drifts away, when losing focus or concentration. It can be picked up instantly by measuring inter-pupil distance. Advanced metrics can help reveal emotional arousal and valence.
Blinks
Eye tracking can also provide essential information on cognitive load by monitoring blinks. Cognitively very demanding tasks can be associated with delays in blinks, the so-called cognitive blink. However, many other assertions can be derived from blinks. A very low frequency of blinks, for example, is usually associated with higher levels of concentration. A rather high frequency argues for drowsiness and lower levels of focus and concentration.
In Part 3 of this series we will look at how to get the most from eye tracking and what are the best practices.
Recent Comments