Fan TV Recommendations

Help consumers navigate seemingly infinite digital entertainment choices.

So much content; so many choices

It’s thrilling for consumers to have so many content options at their fingertips. They can watch and listen to favorites – new and old – at the touch of a button. But discovering relevant new or long-tail content is another matter, given the sheer amount of digital entertainment available from numerous unrelated sources. For service providers, device manufacturers, retailers, websites and application developers, quality recommendations can significantly improve the user experience, positively impacting sales and customer satisfaction.



Offer personalized entertainment recommendations

Fan TV Recommendations provides a variety of increasingly personalized recommendations to drive highly relevant content discovery experiences. With Fan TV Recommendations, you can offer consumers entertainment choices based on similar categories (programs, movies, albums, tracks, musicians or bands), globally or regionally trending topics, user behavior (e.g., social network activity) and contextual factors, such as time of day, day of the week, location and device. 


Help streamline decision-making and break down the barrier of choice

Built on a unique hybrid of content-based, collaborative filtering and personalized algorithms, Fan TV Recommendations helps customers break down decisions by providing fewer, more focused choices for connecting consumers to relevant, cross-platform content. Powered by our comprehensive, enhanced entertainment metadata, Fan TV Recommendations drives more engagement by leveraging specific attributes.



Supports Natural Language Understanding and Natural Language Processing

When combined with Fan TV Conversation, recommendations can be generated through natural conversation for the ultimate discovery experience. Our voice recognition technology can understand complex queries and support context-switching, pronoun use, follow-up questions, negation and ambiguous language. Fan TV Recommendations is built on the Rovi Knowledge Graph engine, a dynamic knowledge base of entertainment metadata capable of understanding trends and conversations. 



  • Offer relevant recommendations driven by user behaviors and preferences through a combination of personalized, collaborative, trending and content-based algorithms.
  • Facilitate delivery of results optimized for specific geographic markets based on local popularity and relevance. 
  • Build trust with users and convince them to interact with the system to make decisions more quickly.
  • Avoid the costs associated with creating and maintaining the infrastructure necessary for generating relevant recommendations. 
  • Provide the same robust feature set on mobile devices, the web and set-top boxes.
  • Benefit from Rovi Knowledge Graph, a true differentiator containing dynamic metadata on 100 million semantic entities and their connections. The Knowledge Graph engine yields highly accurate results, even when confronted with ambiguous, indirect terms.
  • Maximize revenue with advanced capabilities, such as offering partners opportunities to promote their content by increasing focus on a specific catalog.
  • Incorporate business requirements and advanced campaign management options to customize users’ recommendations experiences.

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