Ebuzzing Social, the global specialist in social video advertising, has today unveiled a new partnership with Affectiva, the market leader in the measurement of online consumer emotion. For the first time ever, brands will be able to understand and react in real-time to users’ emotional responses to their online advertising.
Affdex uses Computer Vision and Machine Learning algorithms, developed in partnership with MIT, to detect facial expressions and head gestures obtained from webcams or mobile cameras. It assesses, analyses and interprets the user’s reactions to content to detect the full range of emotions from joy, discomfort and indifference to rapt engagement.
Affdex is embedded in Ebuzzing Social’s player, so brands can implement this technology with any web-connected and webcam enabled audience, without the need for captive test-subjects or a research lab.gy will be used to scientifically measure users’ emotions as they view video ads from a client base including the likes of Heineken and Red Bull.
The partnership marks the beginning of new, more human era in brand metrics, going beyond simple arithmetical values such as page views and dwell time, to incorporate consumers’ emotional response across all social media channels. Brands will be able to assess not just whether their content engaged the target audience, but whether it moved them. This ground-breaking form of analysis will still work hand in hand with, and enhance, the full range of current social media metrics, leading to a more meaningful interpretation of everything from conversation sentiment to share of voice.
Ebuzzing Social has combined traditional key measures of campaign success from awareness, advocacy, interactions and shares to completion rates and click-throughs with Affdex-enabled emotion insights to give brands a deeper evaluation of the true engagement of their video campaigns. By combining the power of quantitative metrics with genuine insight into the emotional response of the consumer, brands now have the potential to deliver true ‘return on emotion’.
“Our work with world-class brands has enabled us to further enhance our science and technology – extending usability across various platforms and making it relevant for real-word applications” stated Nick Langeveld, VP of Business Development at Affectiva “By partnering with Ebuzzing Social, we continue to solidify our position as the global leader in delivering emotion insights.”
Rebecca Mahony, Ebuzzing Social’s VP of Global Marketing commented, “We are delighted to offer this powerful new technology to our clients, which will provide brands with real insight into the emotional experience of their branded videos. By integrating this into our campaign dashboard, we will be able to assess the true engagement of social video based on actual user emotion allowing brands to plug this into their video execution and optimisation for increased campaign performances.”
About Ebuzzing Social
Ebuzzing Social is the global expert in social video advertising. Our network of social publishers includes over 40,000 influential blogs, social networks, social games, mobile applications and Facebook. Through our social video offering we have produced campaigns for many of the world’s leading brands, delivering an explosive mix of influence, reach and engagement.
Based in the UK, US, France, Italy, Spain, Germany and Luxembourg, Ebuzzing Social consists of 200 digital experts, of whom 50 are dedicated to R&D. This team has built the most comprehensive social media and general media database in existence over the past 5 years, which crawls and analyses over 2 million data points in 5 European countries daily.
Affectiva, an MIT Media Lab spin-off, is a global leader and industry expert in emotion measurement technology. Through Affdex™ Facial Coding software, Affectiva delivers cost-effective, scalable emotion analytics to Fortune 500 companies and leading market research agencies. Based on the world’s largest repository of naturally occurring emotional response, their technology has become the global standard for real-world accuracy and relevance in emotion analytics.