neuro-design optimization for creative agencies
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Measuring the emotional impact of digital imagery on consumer behaviour.
Optimizing Creativity Through Neuroscience
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2The Emotive Power of Imagery
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3Pioneering CGI
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4Pioneering CGI
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5Pioneering CGI
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6Saddington Baynes : Creative Production Specialist
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7Art and Science?
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Introduction
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Saddington Baynes : The Draw of Neuroscience
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10Saddington Baynes : The Draw of Neuroscience
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11But Are Gut Instinct Enough?
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12Resistance to Traditional Measures
Measuring the emotional impact of creativity has been a challenge using traditional research tools
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4.7 6.3 6.7
13Creative Industry Resistance to Traditional Measures
Doesn’t feel right
Biggest gulf in credibility for traditional tools
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14Over-reliance on Rationalized Research >>>>Emasculation
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15Energy Suppressed
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16Emotion Flattened
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17Great Campaigns Lost in the Bin?
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18Fresh Approach? Fresh Obstacles?
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19Client v Agency
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20Shackled or Liberated?
New Image
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21Client Push v Agency Pull
Desire Affordability Speed
Agency Differentiation
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22Intro to Engagement Insights
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MOTION
SENSOR
Insight
Neuro
FascinatingRetail
Safari
Emotion
Behaviour
Engagement Insights : Selection of Approach
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24Engagement Insights™
VW
Reliability
WorryRisky
Safari
Reassurance
Trust
True implicit research technology
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DON’T THINK OF A WHITE BEAR
AUTOMATIC, IRREPRESSIBLE COGNITION
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DON’T FEEL ANY EMOTION
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implicit research technology, n. A specialized set of indirect research tools that can reveal System 1 processing by measuring unintentional and uncontrollable responses to stimuli.
Implicit research techniques must not be direct, deliberate, controllable self-assessments.
- Nosek, Hawkins & Frazier, 2011
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“FAST EXPLICIT” TECHNIQUES REQUIRE AN EXPLICIT
JUDGMENT (INTENTIONAL & CONTROLLABLE) AND OFTEN
MEASURE THE RESPONSE TIME (INDIRECT) – MEETING ONLY ONE
OUT THREE IMPLICIT CRITERIA
Does Response Latency = Implicit?
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An Example of True Implicit
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Implicit emotional associations with brands
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Implicit emotional associations with creative assets
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Implicit emotional associations with creative assets
Does it really matter?
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CONSCIOUS BRAND PREFERENCE
(DERIVED FROM MAX DIFF)
BRAND RESPONSE LATENCY
(“FAST EXPLICIT”)
r = .88
“Fast Explicit” Brand Liking
Con
scio
us P
refe
renc
e
for F
eatu
red
Bran
ds
Implicit measures should be additive (different in a meaningful way)
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CONSCIOUS BRAND PREFERENCE
(DERIVED FROM MAX DIFF)
SUBCONSCIOUS EMOTIONAL ASSOCIATIONS
(“TRUE IMPLICIT”)
Sentient Prime® True Implicit Emotional Associations With Brands
r = .46
Con
scio
us P
refe
renc
e
for F
eatu
red
Bran
ds
Implicit measures should be additive (different in a meaningful way)
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0.63
0.430.35
USA Today Admeter Fast ExplicitTrue Implicit
Correlation with Behavioral Contagion (source: Digital SOV iSpotTV top 20 ads)
VALIDATION OF SENTIENT PRIME® TRUE IMPLICIT
Global, Mobile, True Implicit
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Device, OS and Web Browser Agnostic = representative true implicit research
technology.
GLOBAL. MOBILE. TRUE IMPLICIT.
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WITH OVER 100 MILLION SUBCONSCIOUS ASSOCIATIONS MEASURED ACROSS THE GLOBE IN THE LAST YEAR ALONE, SENTIENT PRIME® HAS THE LARGEST DATABASE OF CONSUMER IMPLICIT ASSOCIATIONS IN
THE WORLD
Automation
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Scientifically valid true implicit tests ready in under five minutes
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Automated design and analysis enables rapid test & learn
In the voice of the Creatives
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45How are you now using Engagement Insights day to day?
Engagement Insights™
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Exploration
Testing Examples
Engagement Insights™
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Attribute Selection
Engagement Insights™
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Case Study 1: PreVis vs Final imagery
Engagement Insights™
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Pre-vis - a strong indicator of attribute resonance
PreVis Final image
Engagement Insights™
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PreVis - a strong indicator of attribute resonance
PreVis
Final
Engagement Insights™
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Pre-vis - a strong indicator of attribute resonance
PreVis Attribute scores
Engagement Insights™
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SB Post production- amplify the engagement
Final Attribute scores
Engagement Insights™
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Visual Saliency
Heat map Fog map
NSX PreVis
Engagement Insights™
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Visual Saliency
NSX Overhead w/ flare
Heat map Fog map
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55Asics Example
Engagement Insights™
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Methodology
Most widely used parameters:
• Car Colour • Car Angle• Choice of grade or trim level• Style of Lighting• Choice of location / studio• Static or Action• With or without Talent • With or without visual effects
We vary one parameter at a time to reduce ‘noise’ in data
Engagement Insights™
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Case Study 2 - Test NSX02
Engagement Insights™
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Case Study 2 - Test NSX02
Engagement Insights™
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Test Images - NSX02
NSX Front ¾
Engagement Insights™
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Test Images - NSX02
NSX Garage Look Left
Engagement Insights™
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Test Images - NSX02
NSX Rear ⅞
Engagement Insights™
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Test Images - NSX02
NSX Rear ¾ motion
Engagement Insights™
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NSX Front ¾
Visual Saliency
Heat map Fog map
Engagement Insights™
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NSX Garage Look Left
Visual Saliency
Heat map Fog map
Engagement Insights™
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Test Images - NSX02
NSX Rear ⅞
Heat map Fog map
Engagement Insights™
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Test Images - NSX02
NSX Rear ¾ motion
Heat map Fog map
Engagement Insights™
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Test Images - NSX02
NSX Rear ¾ motion
Engagement Insights™
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Change 1 visual axis - Motion
NSX Rear ¾ static
Engagement Insights™
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Test Images - NSX02
NSX Garage Look Left
Engagement Insights™
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Change 1 visual axis - Direction
NSX Garage Look Right
Engagement Insights™
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Test Images - NSX02
NSX Front ¾
Engagement Insights™
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Change 1 visual axis - Vehicle
HRV Front ¾
Engagement Insights™
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Test Images - NSX02
NSX Rear ⅞ red
Engagement Insights™
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Change 1 visual axis - Colour
NSX Rear ⅞ blue
Engagement Insights™
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NSX Full Study
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76What of the Future?
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77Key Takeaways?