Eye Tracking in UX Design: Key Insights from Our Literature Review

As a digital product designer, I'm always looking for ways to understand how users interact with my designs beyond what they can articulate. After all, what users say and what they actually do can be quite different. This is where eye tracking technology has become a point of curiosity in my design process.

Recently, I had the opportunity to collaborate on a comprehensive literature review titled "Eye Tracking - Reliability and Integration in User Research" with my talented colleagues Chinemelum Jennifer Udenze, Shen Zhang, and Eliana Zuluaga at the University of Brighton. The insights we uncovered have transformed how I approach user research in my design practice, and I wanted to share some key takeaways.

What is Eye Tracking and Why Should You Care?

Eye tracking is a non-invasive method that captures and analyzes visual focus, gaze duration, and eye movement sequences. It provides objective data on where users look, how long they focus on different elements, and the path their eyes follow when navigating interfaces.

As designers, we make countless assumptions about how users interact with our products. Eye tracking gives us concrete data to validate or challenge these assumptions, revealing insights that traditional usability testing might miss.

What Eye Tracking Can Tell Us

Our literature review identified several key metrics that can transform how we understand user behavior:

• First Fixation Time (FFT): How quickly users notice specific elements
• First Fixation Duration (FFD): How long they initially focus on elements
• Dwell Time: Total time spent looking at particular areas
• Gaze Patterns: How users visually navigate through interfaces
• Heat Maps: Visual representations of attention concentration

The research shows that task difficulty correlates with higher cognitive load, resulting in more fixations, longer dwell times, and increased rereading rates. Even pupil dilation can indicate when users are struggling with complex tasks.

Real-World Applications I've Found Valuable

One fascinating finding from our literature review was how color and shape influence user experience on smartphone interfaces. Liu, Cao et al. (2021) used eye tracking to reveal that icons with uniform colors caused longer fixation times - something that would be difficult to discover through interviews or surveys alone.

Another key insight came from Souza, Aviz, et al. (2022) who compared experienced versus non-experienced users on a government website. Their eye tracking data showed that non-experienced users scanned screens more extensively, taking longer to complete tasks. This kind of information is golden for designing interfaces that work for users across experience levels.

Beyond What Users Tell You

One of my favorite examples from our research involved patients using peritoneal dialysis equipment, studied by Mussgnug, Waldern et al. (2015). Initial assumptions based on traditional video recordings suggested users focused mainly on the device itself. However, eye tracking revealed they were primarily paying attention to connectors and packaging.

This perfectly illustrates why we need to go beyond what users tell us. Eye tracking reveals their actual visual priorities, which often differ significantly from their reported experience.

Integrating Eye Tracking with Other Research Methods

While eye tracking provides powerful insights, our review found it's most effective when combined with other research methods:

• Usability Testing: Add eye tracking to understand not just what users do, but where they look while doing it
• Interviews: Compare what users say with where their visual attention actually goes
• Task Analysis: See how visual attention patterns change during different task phases
• Emotion Tracking: Zhu and Lv (2023) suggested combining EEG with eye tracking to understand emotional responses to design elements

Practical Considerations for Implementation

Before diving into eye tracking, our literature review highlighted several factors to consider:

1. Hardware Selection: Consider your research needs when choosing between head-free, head-boxed, or head-restricted setups (Valtakari et al., 2021)
2. Participant Factors: Be aware that certain user groups might require specialized approaches
3. Environmental Conditions: Remote systems offer flexibility but may sacrifice data quality
4. Data Analysis Focus: With the vast amount of data generated, narrowing your focus to specific research questions is crucial
5. Cost Considerations: Balance desired insights with available resources

Limitations to Keep in Mind

No research method is perfect, and our review identified several limitations of eye tracking:

• Equipment Requirements: Specialized hardware and expertise can be costly (Veeravalli, 2023)
• Accuracy Issues: Factors like head movement or improper calibration can affect results
• Participant Variability: Not all users will provide equally usable data
• Context Limitations: What users look at doesn't always reveal why they're looking there

My Takeaway for Fellow Designers

As a product designer, I've found the insights from our literature review on eye tracking to be incredibly valuable additions to my research toolkit. Eye tracking provides objective data that complements and enhances subjective feedback, helping me design interfaces that truly align with how users naturally interact with digital products.

The key is using eye tracking as an enhancement to your research process, not a replacement for other methods. When combined with traditional research approaches, it creates a more complete picture of the user experience.

This blog post is based on the literature review "Eye Tracking - Reliability and Integration in User Research" by Chinemelum Jennifer Udenze, Vishnu Vijayan, Shen Zhang, and Eliana Zuluaga at the University of Brighton. Our collaborative research explored the evolution, applications, limitations, and future directions of eye tracking technology in user experience research.