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

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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Powered by…whereis.sentientprime.com

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


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Attribute Selection


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Case Study 1: PreVis vs Final imagery


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Pre-vis - a strong indicator of attribute resonance

PreVis Final image


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PreVis - a strong indicator of attribute resonance

PreVis

Final


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Pre-vis - a strong indicator of attribute resonance

PreVis Attribute scores


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SB Post production- amplify the engagement

Final Attribute scores


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Visual Saliency

Heat map Fog map

NSX PreVis


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Visual Saliency

NSX Overhead w/ flare

Heat map Fog map

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55Asics Example


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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


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Case Study 2 - Test NSX02


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Test Images - NSX02

NSX Front ¾


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Test Images - NSX02

NSX Garage Look Left


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Test Images - NSX02

NSX Rear ⅞


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Test Images - NSX02

NSX Rear ¾ motion


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NSX Front ¾

Visual Saliency

Heat map Fog map


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Visual Saliency

Heat map Fog map


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Test Images - NSX02

NSX Rear ⅞

Heat map Fog map


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Test Images - NSX02

NSX Rear ¾ motion

Heat map Fog map


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Test Images - NSX02

NSX Rear ¾ motion


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Change 1 visual axis - Motion

NSX Rear ¾ static


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Test Images - NSX02



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Change 1 visual axis - Direction

NSX Garage Look Right


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Test Images - NSX02

NSX Front ¾


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Change 1 visual axis - Vehicle

HRV Front ¾


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Test Images - NSX02

NSX Rear ⅞ red


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Change 1 visual axis - Colour

NSX Rear ⅞ blue


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NSX Full Study

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76What of the Future?

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77Key Takeaways?

Neuro-Design Optimization for Creative Agencies

Marketing

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