emotion measurement can identify which ads sell
TRANSCRIPT
Emotion measurement can identify which ads sell
Mihkel JäätmaCEO / FounderRealeyes@Realeyesit
#ARFannual17
Hello
*Source: Prof Gerald Zaltman, Harvard Business School, 'How Customers Think’ (p40.), 2011
Over 90% of human behaviour is driven by emotions*
Using webcams and the latest computer vision and machine-learning technologies, we measure how people feel as they watch video content online.
$9.9bnDigital spend on video content in US 2016.
Video is growing. Fast.
75mPeople in US watch
online videos everyday
3kTotal YouTube channels
owned by Top 100 brands0
5
10
15
20
25
30
2014 2015 2016 2017 2018 2019 2020
Spend $bn
Vimeo
eMarketer
Pixability.com
Brands struggle to stand out in an oversaturated environment.
“We need to avoid the ‘crap trap’ of content”– Marc Pritchard, CMO of P&G
“Great Creative is kryptonite to ad blocking”– Gayle Fuguitt, Chief of Customer Insight and Innovation Foursquare
"Empathy is the superpower of building brands right now.”- Frank Cooper: CMO, Buzzfeed
"Most of the ads today deserve to be blocked" – Jeremy (Yoram) Wind, Professor of Marketing, The Wharton School of the University of Pennsylvania
“Emotional data will eventually become much more important”– Tracey Follows, CSO and IO, The Future Laboratory.
“Emotion is the main profit driver for brands. Creativity matters”– Les Binet, Head of Effectiveness Adam & Eve DDB
“Good” starts with the creative.Creative is the most important, and most overlooked driver of marketing success.
Testing times for videoBrands go to great lengths to gain audience insight to video, but none of them are linked to real-world outcomes.
Surveys
Focus Groups
Dial Testing
EEG
Heart Rate
Click
Skip
Implicit Reaction
Prepare for sales lift!Emotion measurement that can identify ads which sell.
We partnered with Mars, Incorporated to investigate what drives video advertising success.The study was designed in collaboration with the Mars Marketing Laboratory at the Ehrenberg-Bass Institute for Marketing Science.
Objective/Identify ads with high sales potential, using emotion measurement via facial coding through webcams
Essential for Mars, Incorporated to understand how to create successful videos
Verify whether a video hits the mark before spending on media
Mars, Incorporated provided single-source sales data indicating high or low sales impact for each of the 149 ads
Realeyes collected emotion data on each of the ads
Created a predictive model to validate which emotional patterns matter
Methodology/Using World’s largest emotion database linked to sales
• Model differentiates between ads with high and low sales lift impact.
• Rigorously validated with advanced statistical methods.
• Robust model performance across product categories and countries indicates the model may be universal across product verticals.
4 Categories 6 Countries
Results75% accuracy based on emotions and behavioural signals
ResultsExample variable: Keep happiness growing
• Variable 1: time of happiness growing vs time of happiness falling
• Successful ads grow happiness for longer than having it falling, unsuccessful less so
• Absolute level of happiness matters less than the dynamics of it developing over time
Conclusion
Facial coding provided a model that enabled to separate good ads (proven in-market sales) from bad (zero/low sales) with 75% accuracy
Could guide smarter media spend decisions, at scale
Next: explore how the key success signals can inform creative processes
“People will forget what you’ve said, people will forget what you did, but people will never forget how you made them feel.”– Maya Angelou
Thank you
@realeyesitrealeyesit.com
Mihkel JäätmaRealeyes