Even if business can continue as normal in light of these changes, it’s still time for advertisers to make some adjustments. According to a report by Deloitte, consumers believe that trustworthiness (83%), integrity (79%) and honesty (77%) are closely aligned with their favorite brands. And none of those attributes can be attained by tracking consumers surreptitiously or taking their data without their knowledge.

If advertisers want to evolve and keep up not only with the many evolving privacy policies but, more importantly, the privacy concerns of consumers, they’ll need a platform that can meet their needs without tracking off-site behavior — a platform that instead cultivates trust and integrity with the ability for consumers to opt-in or opt-out. And while users’ diverse basket of interests creates opportunities for advertisers, successful campaigns are more effectively connecting with audiences by focusing on context, not user data. Video categorization is one area where context can be hugely helpful toward this goal.

Embrace relevance and respect privacy with contextual data from video

Unlike ads based on viewers’ browser history, contextually relevant ads serve up promotions inspired by the video currently being watched. For example, it might make sense to pair an NBA highlights video with an ad for a sporting goods store or an ad for a basketball video game.

And with the right technology, contextual relevance can be taken a step further. Advanced machine learning models can better interpret what a video is about by using a combination of video and textual classifiers. This opens up a near-endless list of opportunities for hyper-contextual targeting, allowing advertisers to reach the right consumers at the right moment without infringing on their privacy.

A closer look at video-related contextual data 

One type of contextual data extracted from video categorization is textual classifiers. Every video has a title and a description, and both can be used to help categorize the video for future ad placement.

For example, if the title is “Best new cars from the auto show,” an algorithm could determine that there are two keywords — “cars” and “auto” — that indicate how this video should be categorized. This would enable the video to be paired with ads for automobiles, car dealers and used car lots.  

If the video is about prehistoric creatures — with a title of “Exciting dinosaur discoveries of the 21st century” —  then “dinosaurs” would serve as a solid textual classifier. This video might pair well with an ad for an upcoming movie about creatures from the Jurassic period. 

But what if the video was a bit of a joke, like a clip of kids playing with dinosaur toys or a chef making cakes and …read more

Source:: Digiday

Author: Aaron