“Audiences are fragmenting across time, across place and even across platforms,” says John Hoctor, Vice President of Analytics, Rovi. “This has been great for the individual consumer, but has been a challenge for the folks who measure television and for folks who buy and sell television advertising.”
With viewers consuming countless movies, television shows and user-generated content on a variety of devices, a ﬂood of raw data has been unleashed. How can advertisers and content providers navigate this increasingly complex ecosystem of platforms and content choices while ﬁltering the information overﬂow?
Today, companies are turning to predictive analytics for strategic intelligence about not just what people watch – but when and where – to target speciﬁc audiences for advertisers, media buyers and content providers. Predictive analytics harnesses advanced data collection – from smartphone and tablet viewing data to market segmentation, socioeconomic statistics and online usage patterns – to illustrate a more comprehensive user proﬁle. These enhanced viewer snapshots can help discern the likelihood of where a highly specialized demographic of viewers will be amidst the ever-expanding broadcast landscape.
Not only will predictive analytics play a key role in the future of ad targeting, it owns the potential to optimize entertainment discovery with increasingly intelligent search and recommendations capabilities. With future boosts from analytics, search and recommendations could make proactive, predictive suggestions based on your prior viewing habits and similar viewers’ choices, and even incorporate your social networks’ recommendations. Entertainment then becomes more than merely connecting with content; it will also be about connecting with people. With a more comprehensive understanding of the consumer, analytics beneﬁts networks, providers and advertisers – but it’s the consumer, fueling the predictive analytics engine, who will benefit most of all.