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Human Behaviour – Measuring Emotions To Improve Effectiveness of Online Video Ads


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Please see the keynote video here:

Video advertising avoidance and visual disengagement with TV ads has become one of the most serious problems that the modern advertising industry faces.

This, coupled with the exponential growth in video consumption online, is the main reason that advertisers are increasingly migrating TV money online. However, as performance of traditional online advertising has declined, and in a world where users are increasingly consuming content based on social recommendations and peer-to-peer networks; leading brands have increasingly adopted pull driven mechanics for delivering effective brand and product messaging

Brands are now developing “snackable” video content (usually called viral ads, branded content or branded entertainment) for online consumption. The basic idea driving this development is that while users may actively seek to avoid classic ad formats, they are showing an increasing and simultaneous willingness to connect with some brands voluntarily.

As for the recipe for success in video advertising - the multi-billion dollar question quickly arises – what are the rules of creation in this new pull driven content landscape? What works – and why?

Ekman and Friesen (1978) proposed the Facial Actions Coding System (FACS) to identify basic emotions from facial expressions. FACS has proven very useful in marketing contexts to expose users direct emotional response - but for many years it has relied on manual interpretation, which has made it error prone, slow and expensive. However with the growth of technology, we can now apply FACS testing to thousands of people across the world in 48 hours, using opt-in user panels and normal webcams.

Using this new technology platform Be On and RealEyes have tested over 300 different ads, from standard 30 second TV ads to the most successful viral ads, across a total audience of over 100,000 people from 25 countries. So come and join Be On for a world first view into what emotions have taught them about how users respond to various forms of video ads and content, at scale, and across the world.

Published in: Technology, Business

Human Behaviour – Measuring Emotions To Improve Effectiveness of Online Video Ads

  1. 1. Be Emotive 2005 Luca Bruno, 2013 Michael Sohn - AP
  2. 2. 20,000 unique videos since 2005 2005 2013 Viral Video 2005 The “Social Media” Playbook 2008 Branded Entertainment 2010 Generation Social 2012 Be Emotive 2013
  3. 3. Content Consumption Connection Choice Why emotive?
  4. 4. • Content 2005 2013 5 4 3 2 2009 Global digital content created and shared Source: KPCB, YouTube YouTube hours of video uploaded per minute 100 75 50 25 ZB Hrs 100 hrs of video uploaded to YouTube each minute 8 ZB of data per year will be created by 2015
  5. 5. • Content < 100 > 1m YouTube videos by number of views Source: Business Insider, Businessweek % 30 20 10 29.6% 11.4% 0.3% 1k – 2.5k 10k – 100k 2.7% 0.0001% probability user will view your content
  6. 6. • Choice 2000 2012 1,000 800 600 400 200 2008 Global internet connected device shipments Source: BI intelligence, Microsoft Units (millions) 2004 Smart phones Tablets Personal computers Wearables 47% multi-task on multiple screens
  7. 7. • Choice Share of device page traffic on a typical work day Mobiles brighten the commute PCs dominate working hours Tablets popular at night Source: comScore, Ericsson 60% of consumers watch video on-demand weekly
  8. 8. • Consumption 1.6bn Mobile broadband connections (43% y/y) Source: Ericsson
  9. 9. • Consumption # ## Source: Ericsson, KPCB, Microsoft 2/3 Use multiple screens 150 times per day a user checks their smart phone 1.6bn Mobile broadband connections (43% y/y)
  10. 10. • Connection Source: KPCB, YouTube, Facebook 0 100 Facebook YouTube Twitter Google+ LinkedIn Pinterest MySpace Instagram Tumblr Foursquare 80 Which social media do you use? %604020 2011 v 2012 1bn unique users visit YouTube monthly 1.1bn global active Facebook users 530m photos uploaded and shared daily
  11. 11. Choice What does this mean to advertisers? Content Consumption Connection
  12. 12. Brand Consumer The unwritten contract is breaking Agencies Publishers Distributors
  13. 13. Consumer Agencies Distributors Ad Exchanges/ Networks The new landscape Publisher Advertiser Publisher Advertiser Social Connections Brand
  14. 14. 4.5x higher purchase uplift Richer media vs simple Brand Favourability Purchase Intent 2.5 2.0 1.5 1.0 0.5 Aided Brand Awareness Delta (exposed minus control) Richer media delivers on branding goals Source: Google Doubleclick 15x higher brand favourability
  15. 15. Choice over interruption Video format preference? Premium quality feel? More intrusive format? Positive brand sentiment? Added most value? Pre-roll Positive emotion towards format? Format related to search/activity? Native Source: Be On internal research
  16. 16. 75% higher engagement amongst users who choose to watch video content vs Choice Interruption Source: YouTube, Neilsen, Reelseo Native Pre-roll 82% Higher brand lift generated by native ads, compared to pre-roll 20% higher conversion with user initiated videos
  17. 17. Source: Gunn Report 1992-1995, IPA Les Binet & Peter Field, Marketing in the Era of Accountability, 2007 Emotional advertising campaigns are more effective and more profitable than rational campaigns - even in 'rational' categories… “ ” 11x more efficient in market share growth The Gunn Report
  18. 18. Emotions?
  19. 19. 1800s Darwin The Expression of Emotions in Man and Animals
  20. 20. 1960s ! Ekman Facial Action Coding System (FACS)
  21. 21. 2010s1800s 1960s Coding Automated Facial Coding Emotions
  22. 22. Collection General global population representation Tracking Automated and frame-by-frame in real-time Reporting EmotionAll snapshot and in-depth results
  23. 23. 15” to 5’ content length 20+ categories EmotionAll 1,000+ videos tested 30+ countries
  24. 24. Attraction Hook in 8 seconds Retention Keep the audience Impact Kahneman’s Peak-End Engagement Connect via emotions EmotionAll
  25. 25. EmotionAll LG - So real it’s scary 2 This video has very good overall performance. Better than 92% of videos.
  26. 26. In-depth understanding United States (80.3%) United Kingdom (78.4%) Countries EmotionAll Gender Age Income
  27. 27. Exceptional vs Standard 54,440 YouTube views 5 Tweets 8 Facebook shares 57,659,141 YouTube views 101,572 Tweets 1,367,366 Facebook shares 9 4 80 70 60 50 40 30 20 %happiness Ad duration
  28. 28. Engagement Connect via emotions Attraction Hook in 8 seconds Retention Keep the audience Impact Kahneman’s Peak-End How do emotions help brands break through?
  29. 29. Consumers love emotional content... 3xhigher average view to end % 8xhigher click through rate 20xbetter in converting views into social actions 100xQuicker in attracting viewers Source: Be On research
  30. 30. 8%increase in Brand Recommendation 7% increase in Purchase Intent 14%increase in Brand Favourability ...and it also creates ROI
  31. 31. How to break through
  32. 32. Emotion Attraction Retention Engagement Impact Engagement Syndication Choice Sharing Effect Brand Favourability Purchase Intent Brand Awareness + = Creation Syndication Measurement Impact Model
  33. 33. 9 9 8 8 8 7 7 7 6 6 6 6 55 5 5 5 5 4 7 Introducing the Impact Score