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Gracenote launches Video Popularity Score
Nielsen-owned Gracenote has announced the launch of Gracenote Video Popularity Score.
The service is a new data offering which enables entertainment providers to more effectively understand the TV shows and movies that viewers broadly want to watch so that they can promote them accordingly from within their catalogs.
The new solution is part of Gracenote’s Advanced Discovery suite of metadata products designed to help pay TV providers, OTT services and CE device makers improve the digital video experience and connect viewers to TV shows and movies in innovative ways.
Video Popularity Score helps to identify and surface relevant content by considering recency of TV show airings and theatrical movie releases, viewership and awareness signals from Gracenote and Nielsen plus data from trusted external sources. Based on these inputs, Gracenote calculates a numerical score representing the general population’s recognition level of individual TV series or movies.
“Gracenote continues to help customers deliver optimal entertainment discovery experiences wherein viewers are connected to the movies and TV shows they want with the least amount of friction,” said Simon Adams, chief product officer at Gracenote.
“Our new Video Popularity Score empowers entertainment providers to identify and put the most relevant, watched and talked about TV shows and movies front and center. By enhancing content targeting, Video Popularity Score allows for sharper search results, highly topical recommendations and more relevant viewing options from cold-starts where data on user preferences or previous consumption is not available.”
Viewership is assessed through a proprietary algorithm which analyses consumption data covering linear TV, VOD and OTT from Nielsen Total Content Ratings, movie box office data from Gracenote plus additional raw data from third-party sources. Awareness is calculated based on social media conversation measurement from Nielsen Social Content Ratings combined with key engagement data from outside sources.