Enveu Media & OTT Glossary
A practical knowledge base for OTT platforms, streaming tech, monetization, playback, analytics, DRM, FAST, and media operations. Use A–Z to browse or search to jump to a term.
A practical knowledge base for OTT platforms, streaming tech, monetization, playback, analytics, DRM, FAST, and media operations. Use A–Z to browse or search to jump to a term.
A recommendation engine suggests relevant content to users.
A recommendation engine is a system that automatically suggests video content to users based on their behavior, preferences, and content characteristics. Its goal is to help viewers discover relevant content without requiring them to actively search.
Most viewing decisions are made on the home screen. Effective recommendations increase watch time, improve retention, reduce churn, and help surface long-tail content that users may not otherwise find.
Recommendation engines analyze signals such as viewing history, watch duration, clicks, ratings, and metadata like genre or tags. Using rules, algorithms, or machine learning models, they continuously adapt recommendations based on evolving user behavior.
Recommendation engines power personalized rails such as “Recommended for You”, “Continue Watching”, and “Because You Watched”. They operate across OTT apps, web platforms, and Smart TVs, influencing discovery throughout the viewing journey.