Streaming has been popular for awhile, but with the social distancing and self-quarantining it has increased exponentially. Consumers have thousands of movies and shows at their fingertips, available anywhere at any time across multiple various services such as Apple TV+, Netflix, Hulu and Wavo. This interesting information came to us from Broadcast Pro in their article, “AI will drive recommendation and personalisation.“
However, despite high-quality content, one major complaint viewers have is the challenge of findability. They find themselves scrolling endlessly through vast libraries, unable to find anything they want to watch. Recent research found that today’s TV audiences spend almost an hour a day just searching for content. Sound familiar? Is that any different from users searching for content on a database or platform?
How do we utilize the benefits of a taxonomy in recommendation systems that are not nuanced enough for the complexity of human nature? Viewers are often served recommendations based on highly generic metadata, which is often simplistic and inaccurate.
Harnessing the power of artificial intelligence (AI), improving the filtering options and using metadata at it’s highest potential are all good starts.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
