GazeHits is a design assistant tool to know how your design is perceived in terms of visual attention. It bases itself on state-of-the-art visual attention computer models to identify the elements and features that captures attention. GazeHits makes easy to analyze alternative designs and decide when a work is ready to present it to your customer.

1. Visual
Perception
Analysis with
GazeHits

2. 2

3. Visual
perception
analysis
1. What is GazeHits
2. GazeHits for conversion optimization
3. Science behind
4. Technology under GazeHits

4. ● Qualitative
− Expert opinion
● Eye tracking
− Is costly and time consuming
− Requires hiring tens of people to
acquire reliable data
− Does not trace the drivers of
attention
CC BY 2.0 SMI - Neil Rickards
Conventional
visual
perception
analysis

5. GazeHits,
beyond eye
tracking
● Immediate and Mobile
● Predicts first 3 seconds of eye tracking
with high accuracy
● Predicts visual clutter perception with
high correlation (0 to 100)
● Provides insight in why something is
eye-catching or cluttered
● Provides quantitative indicators to be
integrated with analytics

6. Importance of
visual
perception in
marketing
● “If consumers’ attention is not caught in
the first place, all findings [on message
appreciation and acceptance] in ‘forced
exposure’ research are valueless.”
Wedel and Pieters. Review of marketing research.
(2008): 123-147.
● “The density of visual detail in terms of
color, luminance, and edges hurts brand
attention and attitude toward the ad”
Pieters, Wedel, and Batra. "The stopping power of
advertising: Measures and effects of visual
complexity." Journal of Marketing (2010): 48-60.

7. ● Just upload and image
− from drive
− from camera shot
● Functionality
− Heatmap
− Opacity map
● Quantitative strength
− Region selection
− Visual clutter
www.gazehits.com
FREE on Beta
How it works?

8. Visual
perception
analysis
1. What is GazeHits
2. GazeHits for conversion optimization
3. Science behind
4. Technology under GazeHits

9. Pre-testing in
web design

10. Pre-testing web
designs in
e-commerce

11. Pre-testing ads
in online
newspapers

12. In context visual
attention
assessment

13. In context
windows
assessment

14. Visual
perception
analysis
1. What is GazeHits
2. GazeHits for conversion optimization
3. Science behind
4. Technology under GazeHits

15. ● Acquires 10-100 Mb/s through retinal
photoreceptors
● Our eyes move all the time: Saccades
and Fixations
− Otherwise photoreceptor adaptation would make
us blind in seconds
● Just one degree of visual field is
perceived with high acuity at a time
− That part under the spot of the Fovea
● Certain stimuli receive enhanced neural
processing
● Fixations
− Keep the fovea around a fixed point during 0.5s
− 2-3 fixations per second
4 facts about
human visual
system...

16. What is visual
attention?
● Roughly, the set of operations that select
visual information
● Key role in
− Building visual concepts to represent
reality
− Object perception
− Focusing cognitive effort on important
stimuli

17. ● Biases of the visual system: e.g. looking
at the center
− Unrelated to the specific image
● Top-down Relevance related to task,
intention, and knowledge of observer
− Dependent on observer motivation
and experience, generally divergent
● Bottom-up Saliency arising from the
physical features of the scene
− Universal and common to any
observer with healthy vision
What are the
drivers of
attention?

18. Pop-out
fenomena

19. Visual
perception
analysis
1. What is GazeHits
2. GazeHits for conversion optimization
3. Science behind
4. Technology under GazeHits

20. Models of
attention
● Bioinspired
− Decompose and analyse images following
observed operations in the human visual system
− Implement hypothesis on neural operations
● Traceability is possible
● Robust performance across different types
of images
● Unaware of semantics or task
● Machine learning
− Learn to reproduce fixations registered in eye
tracking experiments
● Capable to learn semantics and
task-related behavior
● Reproduce biases in training data set
● Black box. No traceability

21. AWS, the model
under GazeHits
● Based on the image representation by the
visual cortex
− Hubel and Wisel, Nobel Prize of
Medicine 1981
● Based on statistical operations shown by
the human visual system
− Decorrelation and normalization
contrast

22. Technology
under GazeHits
● AWS as the bioinspired component
− Accurate and robust to biases and
changes in image types
− Ranked first with sAUC (no biases) in
MIT CAT2000, the largest benchmark
available
● Machine learning used for task-related
prediction
− Can be trained with conventional
analytics data

23. Competitors ● Feng-Gui (https://www.feng-gui.com/)
− Based on some kind of algorithms
● Attention Wizard
(https://www.attentionwizard.com/)
− Based on algorithms to provide web
heatmaps
● Eyequant (http://www.eyequant.com/)
− Based on machine learning (only for
webs)
● 3M Visual Attention Service
(http://solutions.3m.com/wps/portal/3M/en
_US/VAS_NA/Home/)

24. www.gazehits.com
info@gazehits.com
Let us hear from
your specific
needs