Media and entertainment metadata provider Gracenote has launched its next-generation descriptive metadata solution designed to make possible more contextually-relevant and satisfying TV and movie discovery experiences.
Gracenote Video Descriptors, the first of the company’s new Advanced Discovery products, will enable pay-TV providers, OTT services and connected device manufacturers to unlock deeper user engagement and loyalty in a hyper-competitive marketplace.
According to Gracenote, TV providers are dedicating increasingly large budgets to build sizable on-demand catalogues of both originally produced content and licensed TV shows and movies. At the same time, they are developing smarter search, discovery and recommendation capabilities, including voice and image-based search, to expose viewers to all available content, from big budget blockbusters to the most niche TV programmes. As content catalogues continue to expand and discovery systems grow more intuitive, they require sophisticated metadata that goes beyond traditional genre information, to fuel targeted recommendations and personalisation.
“Major streaming providers average around 40,000 TV episodes and movies in their catalogues but put the onus on their viewers to sort through and find relevant programming,” notes Simon Adams, Chief Product Officer at Gracenote. “By diving deeper into storylines and characters and assigning much more granular metadata to content, Gracenote Video Descriptors give TV providers powerful datasets enabling fresher discovery, recommendation and voice experiences that satisfy the full spectrum of viewer tastes or moods.”
According to Gracenote, its Video Descriptors take entertainment metadata to the next level, enabling clearer understanding of content and subsequently, more personalised video picks, suggesting that the new Gracenote dataset goes far beyond traditional genres to include descriptors such as Mood, Theme, Scenario and Characters. In addition, Gracenote Video Descriptors features structured keyword sets for individual TV shows and movies which describe content in progressively more granular terms.
Using Game of Thrones as an example, Gracenote pinpoints ‘Themes’ such as ‘Greed ‘and ‘Betrayal’, describes ‘Scenarios’ including ‘Power Struggle’ and ‘Manipulation’, assigns ‘Mood’ elements such as ‘Dark’ and ‘Gripping’ and classifies the programme’s ‘Characters’ from ‘Royalty’ to ‘Dragons’. Focusing on ‘Scenarios’, Gracenote data can be used to identify similar programmes based on related descriptors such as ‘Sweet Revenge’ or ‘Good vs Evil’. By better understanding what Game of Thrones is about and relating those attributes to other programmes, Gracenote Video Descriptors enable deeply-nuanced discovery that surface the content that will best resonate with individual viewers.
To generate its descriptive metadata, Gracenote relies on a balance of expert data scientists, editorial teams and advanced machine learning technologies to describe TV shows and movies from every possible perspective. Delving deeply into the storylines, characters and settings, Video Descriptors better connect viewers to the full range of available content they might like based on moods, preferences, tastes and past viewing behaviour.
Further releases from the Advanced Discovery suite will be rolled out in 2019.