TMCnet News
New Study From MAGNA Reveals Impact Of Human-In-The-Loop Contextual Targeting On Solving Brand Suitability And Driving More Effective OutcomesLOS ANGELES, Oct. 21, 2019 /PRNewswire/ -- "Human in the loop" contextual targeting – which uses brand preferences to power machine learning that is overseen by humans – is dramatically more effective than traditional modes of ad targeting, according to "Solving Brand Suitability," a new study by MAGNA and the IPG Media Lab conducted with Zefr, the Contextual DMP™ for brands and agencies.
The study aimed to provide a foundational understanding of how brands can better achieve "brand suitability," defined by advertisers as their unique positive and negative contextual preferences. Advertisers are increasingly focused on how different targeting methods fare in achieving it. The study found that just 25% of consumers think brands are doing a good job of advertising on YouTube and only 18% of those who expect relevance between the ads and the video said that the ads are typically aligned with the videos they are watching. The study then explored different methods marketers could employ to improve "Brand Suitability." Nearly 4,000 consumers were surveyed on their reactions to ads from three brands across verticals – Nationwide (insurance), Ubisoft (gaming) and Scotts Miracle Grow (paper/manufacturing). Ads were delivered to consumers via different forms of targeting: demographic; channel; keyword; and "human in the loop contextual targeting" (where a team consistently reviews videos in order to train machine learning models). The study revealed that ads delivered through "human in the loop" contextual targeting outperformed all other methodologies in a number of key metrics:
A somewhat unexpected insight revealed in the study is the considerable opportunity for advertisers to reach audiences by expanding their definitions of "quality" video. 44% of content machines identify as low-quality is perceived as high-quality by consumers who view it as enjoyable and interesting. The study shows that in video, quality is often in the eye of the beholder, and brands can succeed by tapping into this significant pool of largely uncharted, brand-suitable ad inventory. UM's Chief Digital and Innovation Officer, Joshua Lowcock said, "This is a firm reminder context matters as much as the data used to find an audience. The more aligned the ad is with content, the more likely consumers are to view the brand as innovative, savvy, trustworthy and one for which they will pay more. Using human-supervised machine learning to help find suitable content is one way of finding that balance." The full study, including other key insights and details on the methodology, can be found here. About Zefr About IPG Media Lab About MAGNA MAGNA harnesses the aggregate power of all IPG media investments to drive maximum value for its clients through preferred pricing and premium inventory. The agency's Investment and Innovation teams architect go-to-market media strategies across all channels including linear television, print, digital, programmatic and emerging media. MAGNA is a leader in generating data and technology-enabled solutions that drive optimal client performance and business results. The agency's Intelligence unit has been a coveted source of crucial industry information, including media value predictions, for more than 60 years. It produces more than 40 annual reports on audience trends, media spend and market demand as well as ad effectiveness. For more information, please visit https://magnaglobal.com/. Media Contact Andrew Serby
SOURCE Zefr 
|
View original content to download multimedia: