This document discusses building better prototypes using AI. It describes a company that builds software to provide instant web design feedback using machine learning models trained on large datasets of user studies. Their tool, called EyeQuant, analyzes visual attention, clarity, and emotional response to designs and provides over 85-90% accurate feedback within seconds to help designers improve their prototypes faster. It encourages visiting their website eyequant.com to try the tool.

1. Building better prototypes with AI

2. We build software for instant
web design feedback
web

3. Why is this so important?
web

4. Today’s design process
web
Understand
Problems
Design new
solution
Figure out
if it’s better

5. Today’s design process
web
Understand
Problems
Design new
solution
Figure out
if it’s better
DATA DATA

6. Today’s design process
web
Understand
Problems
Design new
solution
Figure out
if it’s better
DATA DATA
Hunches &
Opinions

9. Tomorrow's design process
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Data during the design process

10. We’re solving this with machine learning
web

11. Large Scale Data
Acquisition Studies
Machine Learning & Predictive
Modelling
Instant Results via SaaS
Application & API
Methodology
>85-90% Accuracy Results within seconds

12. How to get results from the webapp
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16. Visual Attention Analysis:
Is the most important content seen immediately?
web

17. Simple model for focus & clarity: 3 W’s
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What Why Where next?

19. Are there any distractors?

21. How eye-catching is one area
compared to another?

23. Visual Clarity Analysis:
How clean and clear is my design?
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25. What’s contributing to clutter?

27. Emotional Analysis:
Will users perceive my design as stimulating?
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29. So how do I use it today?

30. Idea Prototype EyeQuant Learn

31. bit.ly/2qB3vyR
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