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The Role of Eye Tracking in User Experience Research...

The Role of Eye Tracking in User Experience Research

(Download at: http://www.usercentric.com)

Webinar presented on behalf of the Human Factors and Ergonomics Society (HFES)

December 11, 2009
By Gavin Lew, Managing Director of User Centric

Back to 2009 Publications Index
Gavin Lew, Managing Director of User Centric, presented a Webinar on behalf of the Human Factors and Ergonomics Society (HFES) on December 11, 2009. During this Webinar, The Role of Eye Tracking in User Experience Research, Gavin described eye tracking measures, methods, and applications to user experience research. User Centric is well known for its eye tracking research through the widely-published works of both Gavin Lew and Associate Director, Aga Bojko, a leading expert in the field.

The HFES launched a series of Webinars in 2009; in 2010 there will be webinars on a bi-monthly basis.

Webinar summary:

The ability to track eye movements for scientific research has existed for generations. Recent technological advances in this area have made both data collection and analysis easy. Thus, what was once an extremely cumbersome and time consuming research endeavor, now is a very intriguing research technique—with the visual outputs sometimes being perceived as having more value than the data itself. With the growing number of eye tracking system installations in both academic and commercial research centers, a discussion of the role of eye tracking in user experience research is critical.

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About the Human Factors and Ergonomics Society

The Human Factors and Ergonomics Society was founded in 1957. Its mission is to promote the discovery and exchange of knowledge concerning the characteristics of human beings that are applicable to the design of systems and devices. The Society's 5,000+ members advocate systematic use of human factors knowledge to achieve compatibility in the design of interactive systems of people, machines, and environments to ensure their effectiveness, safety, and ease of performance. Through its 21 technical groups, 35 local chapters and 31 student chapters, the Society encourages education and training for those entering the human factors and ergonomics profession and for those who conceive, design, develop, manufacture, test, manage, and participate in systems.

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Eye Tracking in User Experience Research - Webinar Eye Tracking in User Experience Research - Webinar Presentation Transcript

  • The Role of Eye Tracking in User Experience Research HFES Webinar Series Prepared by User Centric, Inc. Gavin Lew Managing Director glew@usercentric.com Presentation Delivered 11 December 2009
  • Outline The Basics Eye Tracking and UX Research The Case for Quantitative Analysis Ceilings and Floors Method case study on packages Q&A 2
  • Eye Tracking The Basics 3
  • Eye Tracking: The Basics Basics of Eye Movements Eye tracking is a research technique that captures eye behavior in response to a visual stimulus “Eye-mind hypothesis”: where people look is where they focus their attention Saccadic eye movements (most Saccade (line) common) consist of: Fixation (circle) – Fixations – Saccades 4
  • Eye Tracking: The Basics Sample Eye Measures Quantitative Measures Meaning Informativeness of an area / user interest in the # fixations on an area area Info clarity / info density / info processing Fixation length demands # fixations before target Time to 1st target fixation Layout effectiveness / search demands Scanpath complexity % users fixating on an area Order of 1st fixation Prominence / perceived importance of an area # visits to area Cognitive processing demands / user mental Pupil diameter workload / emotion 5
  • Eye Tracking: The Basics Eye Trackers Eye tracker determines the position of one or both eyes multiple times (30 – 1000+) per second Commonly used eye trackers differ in physical form, setup procedures, and tracking methodology: 6
  • Eye Tracking: The Basics The Tobii Eye Tracker Our eye tracker: Tobii 1750 – Integrated into a 17” computer monitor – No restraints, freedom of head movement – Binocular tracking – Sampling rate 50 Hz – Quick and automatic calibration 7
  • Eye Tracking: The Basics Lab Setup Moderator’s station to view Face Tobii 1750 remote eye-tracking eye gaze in real time and camera system integrated into a 17” control eye tracking software monitor (set to 1024 x 768 px) One-way mirror Moderator Participant 8
  • Eye Tracking Eye Tracking and UX Research 9
  • Eye Tracking: Eye Tracking and UX Research Three Dimensions of Feedback How people evaluate objects − Commercials − Packages − Online advertisements − Products − … © December 11, 2009 10
  • Eye Tracking: Eye Tracking and UX Research Attitude What users “say” ... Influencers – Social status – Emotion – Coolness / Hip Reveal – Feature importance – Purchase intent © December 11, 2009 11
  • Eye Tracking: Eye Tracking and UX Research Behavior What users actually “do” Ultimately, behaviors are what we wish to shape Give users context, a task and stimuli and then – Observe what users do Behavior drives usage © December 11, 2009 12
  • Eye Tracking: Eye Tracking and UX Research Attention What users “focus” on What happens inside the head Sometimes users are unaware Often attention measured by eye tracking © December 11, 2009 13
  • Eye Tracking: Eye Tracking and UX Research Eye Tracking in UX Research 14
  • Eye Tracking: Eye Tracking and UX Research How Can Eye Tracking Help Usability Testing? TASK: Find a branch near you Page with no gaze. With something hard to find. That’s impossible. 15
  • Eye Tracking: Eye Tracking and UX Research How Can Eye Tracking Help Usability Testing? ET FINDINGS: (1) Average # fixations before the target link was found: 112 (2) The top right corner of the page attracted initial & the most fixations. Ah, quant data… 16
  • Eye Tracking: Eye Tracking and UX Research How Can Eye Tracking Help Usability Testing? TASK: Find a list of indoor climbing walls. So… she only considered the first two results? 17
  • Eye Tracking: Eye Tracking and UX Research How Can Eye Tracking Help Usability Testing? ET FINDING: She looked at (considered) more results than just the top 2. 18
  • Eye Tracking: Eye Tracking and UX Research How Can Eye Tracking Help Usability Testing? Typically in usability testing, we collect: – Behavioral measures (e.g., clicks, time) – User self-report (e.g., RTA) Eye tracking can: – Support and illustrate UT findings – Help determine user expectations – Augment usability findings by filling in the gaps between • Observable events • User comments 19
  • Eye Tracking: Eye Tracking and UX Research How Can Usability Testing Help Eye Tracking? Different eye movement patterns produced by the same person looking at the same picture… Why are they all so different? Yarbus, A. L. Eye Movements and Vision. Plenum. New York. 1967 20
  • Eye Tracking: Eye Tracking and UX Research How Can Usability Testing Help Eye Tracking? TASK: Estimate people’s ages. Different eye movement patterns produced by the same person looking at the same picture… but in a different context! TASK: Estimate the family’s material circumstances. Yarbus, A. L. Eye Movements and Vision. Plenum. New York. 1967 21
  • Eye Tracking: Eye Tracking and UX Research How Can Usability Testing Help Eye Tracking? TASK: Find the museum hours. 22
  • Eye Tracking: Eye Tracking and UX Research How Can Usability Testing Help Eye Tracking? ET FINDINGS: (1) All users looked at the image. (2) Time spent looking at the image: 30% of all time spent on page. Great! Image got lots of attention! 23
  • Eye Tracking: Eye Tracking and UX Research How Can Usability Testing Help Eye Tracking? Actual target link So this is bad… 24
  • Eye Tracking: Eye Tracking and UX Research Usability Testing and Eye Tracking Usability Eye Tracking Provides context for… Testing reveals factors reveals (mostly) that contribute outcomes of Illustrates and helps understand to the outcomes interaction ANSWERS PROVIDES PRACTICAL MORE QUESTIONS DETAILED ANALYSIS 25
  • Eye Tracking: Eye Tracking and UX Research Eye Tracking In Isolation Yields Uncertainty Eye tracking has limited applicability when used in isolation – A fixation on a face may indicate recognition, liking, dislike, or confusion – More fixations may indicate interest or inefficient search Instead combine with attitudinal and behavioral probes – Learn the “why” – Just knowing where people look is often insufficient 26
  • Eye Tracking: Eye Tracking and UX Research Context is Key for Eye Tracking Is this good or bad? Were users told to: – Signup for Newsletters? – Learn about services? – Read publications? – Look for a job? Or worse, they were not given any context at all Always ask about the context / task! © December 11, 2009 – Proprietary and Confidential 27
  • Eye Tracking The Case for Quantitative Analysis 28
  • Eye Tracking: The Case for Quant Analysis Heatmap: Classic Eye Tracking Output With thousands of data points to analyze, interpretation should be based on data… © December 11, 2009 – Proprietary and Confidential 29
  • Eye Tracking: The Case for Quant Analysis Visualizations Facilitate, Not Interpret © December 11, 2009 – Proprietary and Confidential 30
  • Eye Tracking: The Case for Quant Analysis Graphs are Visualizations too… Show Me Data © December 11, 2009 – Proprietary and Confidential 31
  • Eye Tracking The Case for Quantitative Analysis • Case Study 32
  • Eye Tracking: The Case for Quant Analysis Selecting One Design Concept 1 Concept 3 Existing Homepage Concept 2 Concept 4 © December 11, 2009 – Proprietary and Confidential 33
  • Eye Tracking: The Case for Quant Analysis Free View: First Impressions Client identified key business goals MY ACCOUNT Between-groups design – Each group saw a different design PERSONAL /BUSINESS PROMO 1st impressions task: – You are looking for a new wireless provider and you decided to check what Verizon Wireless has to offer... Homepage was shown for 10 sec. © December 11, 2009 – Proprietary and Confidential 34
  • Eye Tracking: The Case for Quant Analysis Which Won? CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4 EXISTING Remember the measures? What is the heatmap showing?!?! % of users who fixated? Fixation length? # of fixations? Eye Tracking: The Basics Sample Eye Measures Quantitative Measures Meaning CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4 EXISTING Informativeness of an area / user interest in the # fixations on an area area Info clarity / info density / info processing Fixation length demands # fixations before target Time to 1st target fixation Layout effectiveness / search demands Scanpath complexity % users fixating on an area Order of 1st fixation Prominence / perceived importance of an area # visits to area Pupil diameter Cognitive processing demands / user mental Oh, wait. Maybe workload / emotion this will help 36 © December 11, 2009 – Proprietary and Confidential 35
  • Eye Tracking: The Case for Quant Analysis You Must Know the Measure! % users who fixated each area CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4 EXISTING Order in which the areas were first visited CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4 EXISTING © December 11, 2009 – Proprietary and Confidential 36
  • Eye Tracking: The Case for Quant Analysis Quantitative Results % users who fixated each area CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4 EXISTING A C A A C C B B B B A C B A C KEY AREAS OF INTEREST AREA A: My Account 100% 79% 77% 64% 68% AREA B: Promo 100% 100% 100% 100% 100% AREA C: Personal/Business 100% 85% 80% 100% 52% Order in which the areas were first visited CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4 EXISTING KEY AREAS OF INTEREST AREA A: My Account 2nd >5th > 5th 3rd 4th AREA B: Promo 3rd 1st 4th 2nd 1st AREA C: Personal/Business 1st 2nd 1st 1st 3rd © December 11, 2009 – Proprietary and Confidential 37
  • Eye Tracking: The Case for Quant Analysis Quantitative Results # of fixations on an area (out of ~31 on average) CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4 EXISTING KEY AREAS OF INTEREST AREA A: My Account 3.8 3.4 2.3 2.2 2.3 AREA B: Promo 8.2 8.0 5.5 6.5 8.3 AREA C: Personal/Business 8.2 4.2 3.5 6.9 3.2 TOTAL 20.2 15.6 11.3 15.6 13.8 © December 11, 2009 – Proprietary and Confidential 38
  • Eye Tracking: The Case for Quant Analysis Bottom Line Link measures to research question MY ACCOUNT When looking at data, avoid the allure of reading tea leaves PERSONAL /BUSINESS PROMO Ask: – What is the context/task? – What is the measure? – Where is the quant? © December 11, 2009 – Proprietary and Confidential 39
  • Eye Tracking Ceilings and Floors 40
  • Eye Tracking: Ceilings and Floors Commercial aired in 2003 FYI: Commercial is for a cable TV, Internet and telephone provider 41
  • Eye Tracking: Ceilings and Floors What Did You See? Services offered Internet web page Money in a piggy bank Let’s see what Participant #7 saw… 42
  • Eye Tracking: Ceilings and Floors Participant #7’s Gaze Replay 43
  • Eye Tracking: Ceilings and Floors What Did Participant #7 See? Key words Watched pig Even followed the mouse! In testing, we asked about the commercial… – Love it – I want the deal So, you go and get it! – Literally. Participant asked to open a browser and off they went – They even entered the URL… 44
  • Eye Tracking: Ceilings and Floors TV Commercial to Web “Handshake” Empirical weblog data: – 20% clicked the pig 45
  • Eye Tracking: Ceilings and Floors Results Attitude – Viewers liked the ad – Some even “loved it” and wanted to get the “deal” Behavior – In the study, 23% clicked (empirically, 20% click) Note how Eye Attention Tracking was not used in isolation… – 70% looked • But, the pig spins around, so some glances will occur – Setting a 150ms threshold (look at pig, read, etc.) • 40% looked • Relative to ad spaces on site 46
  • Eye Tracking: Ceilings and Floors Ceilings and Floors Not everything you design gets attention (there is a “ceiling”) Designers and marketers tend to assume that if you build it, 100% will see it What would you say about these results? We said: – Not bad. Your ceiling was 40% and you are getting 20%. – To improve click-thru, improve attention. • If you do not attend, you will not click. Eye Tracking is useful answer: Do user NOT CLICK because – They looked, but the value proposition <> click (marketing). – They never looked (design). 47
  • Eye Tracking Comparing Search Results: Bing vs. Google 48
  • Eye Tracking: Bing vs. Google Comparing Two Search Results Pages Research objective: – Compare the distribution of attention on equivalent areas of Bing and Google – Assess how much attention is captured by elements that are unique to Bing Participants (N=21) completed search tasks for each engine – Two informational (e.g., "Learn about eating healthy") – Two transactional (e.g., "Book a last minute vacation“) 49
  • Eye Tracking: Bing vs. Google Gaze Duration for One Task © December 11, 2009 – Proprietary and Confidential 50
  • Eye Tracking: Bing vs. Google Results: Similarities Google and Bing did not differ in amount of attention on the organic search results – In each search, all participants looked at the organic search results, spending an average of 7 seconds in that area Attention on the sponsored links located above the organic results was similarly high for both Bing and Google – Over 90% of participants looked in that area during each search. 51
  • Eye Tracking: Bing vs. Google Results: Differences Sponsored links on the right attracted more attention – Bing (~42% of participants per search) than they did on Google (~25% of participants per search) – Participants who fixated on these links spent approximately 2.5 seconds looking at the area during transactional searches and 2 seconds during informational searches 52
  • Eye Tracking Method Case Study on Packages 53
  • Eye Tracking: Method Method Case Study Study objectives: – Determine how the client’s packaging compares to competitors’ packaging in Marketing terms of noticeability and visual engagement / interest – Assess the findability and clarity of the information on the client’s package as compared to the information on the Usability competitors’ packages Wearable eye trackers vs. remote eye trackers 54
  • Eye Tracking: Method A Walk Down The Aisle… Macro-level: – Participants saw pictures of aisles – Five picture frames per store (2 s per frame) – Each showed the entire prepaid phones display – However, the display was in a different position in each frame to simulate the changing view of a moving customer (in a “freeze frame” way) and minimize the effect of product position in the picture 55
  • Eye Tracking: Method Product View Micro-level: Front Back – Participants saw pictures of individual packages – Given tasks to answer to find information on the package itself – Participants were able to “flip” package around by clicking Q3: Can you Q2: What is The answer is: browse the The answer is: the brand of ______ Web on this ______ this phone? phone? 56
  • Eye Tracking: Method Actual Package Experience Constructed shelves Participants were different from the macro- and micro-level study – Far view – Up close – Manipulation – Selection decision – Discussion 57
  • Eye Tracking: Method Measures Memory – Free recall of products and brands – Recognition exercises of products and brands Preference – First impressions from afar – Likes and dislikes Performance tasks – Accuracy of finding answers to tasks – Efficiency in time to find answers (excluded incorrect answers) Eye tracking (computed based on package area) – % who looked (noticeability) – # of fixations (visual engagement) 58
  • Eye Tracking Q&A 59
  • Q &A Final Takeaways Eye Tracking should be combined with other UX techniques – Avoid using ET in isolation Context matters – One can change a heatmap with just four words! When looking at a heatmap, ask: – What was the task or context? – What is the heatmap showing? • % who fixated, gaze duration • # of fixations, etc. • Each measure reveals a different story… With so much data, where is the quantitative analysis? 60
  • Q &A Q & A? Questions? Additional references: – Me: glew@usercentric.com – Peer-reviewed journal articles, presentations, white papers on www.usercentric.com – ET case study of package labels by Aga Bojko in Tullis and Albert’s book, Measuring The User Experience – ET global case study in Bob Schumacher’s book, The Handbook of Global Research • www.globaluserresearch.com • www.elsevierdirect.com 61