Content discovery WITH RECOMMENDATIONS

Similar Playlist

Increase viewer retention and engagement based on viewer behavior and video metadata.

JW Player’s similar video playlists drive viewers to watch more content by presenting the most relevant and engaging videos in relation to what they’re currently watching. This playlist powers our in-player recommendations overlay and leverages viewing signals from across the entire JW Network. Get Started

How It Works

JW Player recommends similar content based on watch associations, content matching and trending content.
similar content
ranked by watch associations, content matching
backfill
trending content
ranking order
watch
associations
publish
date
publish
date
Watch Associations First, our proprietary association algorithm ranks by the frequency of paired watches across user sessions, i.e. the top associated slot will be filled by a video that viewers have watched with the current video more than any other content.
Content Matching Next, our content-based algorithm filters by term frequency and then ranks by the Trending Score, i.e. the top content video will have terms in the title and description that overlap with the current video and has the highest Trending Score.
Trending Content Finally, backfilling is ranked by the Trending Score, i.e. the top backfilled item will appear after association and content matches and will have the highest Trending Score.