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What to Watch? The Range of Choices Is Staggering

Technology might provide a universal guide for TV/video shows

A staggering range of content choices threaten to overwhelm consumers.

It’s easy for consumers to feel overwhelmed by today’s TV and video environment. With millions of content choices, from YouTube videos to Netflix to a growing range of TV apps, it’s harder than ever for consumers to sort through the embarrassment of options. How do today’s consumers discover new content? And how might new technology help media companies simplify viewers’ content discovery efforts in the future?

For now, many US consumers rely on a mix of traditional and “high-tech” discovery methods to find TV and video content. According to an October 2016 survey of US internet users by the Consumer Technology Association (CTA), the two most popular content discovery methods were TV ads (56%) and word-of-mouth (54%), two sources that have been around for decades.

Ways in Which US Internet Users Discover TV/Video Content, Oct 2016 (% of respondents)

But newer digital discovery methods are growing in popularity, with internet search (32%) and digital video service recommendations (23%) mentioned by a sizable portion of respondents.

The difficulties of navigating today’s TV and video discovery environment haven’t been lost on digital content companies, many of which are experimenting with new tools and techniques to help viewers find better content.

Netflix, for example, announced that it would be replacing its star rating system in April 2017, trading it for a thumbs up/thumbs down ranking system that has earned both praise and criticism since its unveiling.

The problem of content discovery has also led to calls for creation of a “universal search” system, though it seems unlikely that popular content services like YouTube, HBO or Netflix would be willing to grant access to their private data libraries to make such a guide possible.

Despite the current difficulties, one content discovery approach that may have potential is artificial intelligence. Many believe that these algorithm-based recommendation systems could more easily sort through the vast amount of metadata (for example, lists of actors or critics ratings) associated with different content titles, helping to further personalize and scale content discovery in the process.

How will consumers find new TV and video content in the future? No one, not even the industry’s top streaming competitors, has come up with the perfect answer. But all signs suggest technology will play an important role in the eventual solution.

Jeremy Kressmann

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