Advanced Television

Cinedigm partners with Katch

September 9, 2022

Cinedigm, a streaming company dedicated to serving enthusiast fan bases, is partnering with Katch to integrate its unique Genomic Data into Cinedigm’s forthcoming, flagship streaming service, Cineverse. Much like how Pandora changed the way millions of people discover music, Cineverse will be among the first to enhance content discovery by utilizing an extensive metadata classification system to categorize film and television series via Katch’s proprietary set of Universal Genomic Traits that account for tone, character arcs, mood, context and thematic nature, among many other qualitative traits.

These Universal Traits help describe video content in ways that cannot be achieved via the use of a TV series or film’s typical genre classification or content synopsis. By combining Katch’s unique data with Cinedigm’s portfolio of movies and shows, the companies are paving the way towards an advanced genomic approach to streaming video that leverages taste-driven insights. Designed by Dr. Nolan Gasser, architect of the original Pandora Music Genome and author of “Why You Like It: The Science and Culture of Musical Taste”, the genome is the foundation of Katch’s analytics and content intelligence technology.

Cineverse is Cinedigm’s new, all-in-one streaming service that will feature over 20 free ad-supported streaming television (FAST) channels alongside thousands of titles available on demand. This content will span various popular genres targeting enthusiast fan bases – from anime and sci-fi/fantasy to horror and independent film.

Using Katch’s Genomic Traits, content available on Cineverse can be described “beyond” its genre, with substantially more detail, by capturing more than 2,000 unique variables that represent highly nuanced dimensions for each title, allowing Cinedigm to program collections of content that are far more accurate and thematically cohesive than those programmed by most streaming services (i.e., “New This Week” or “Top Horror Films”). For example, content across a variety of genres can be linked together via their shared Genomic Traits, enabling Cineverse users to discover new films or series that more accurately reflect their interests and tastes.

Katch’s proprietary data and analytics provide streaming platforms with actionable programming insights into why certain film and TV series are connecting with different audiences – allowing Cinedigm to refine its content programming and content acquisition strategy over time.

“Content discovery is at the heart of Cineverse, and it is our aim to redefine the user experience by improving how audiences discover television entertainment that better suits their interests and caters to their needs,” said Tony Huidor, Chief Technology & Product Officer at Cinedigm. “We are excited to lead the way in utilizing Katch’s Media Genome to enhance content discovery and look forward to rolling out other forthcoming enhancements such as an integrated loyalty program, digital rewards, and collectible NFTs. Our partnership with Katch will help us change how our viewers discover new movies in the same way that Pandora significantly changed the music industry by enabling listeners to more easily discover music that perfectly matched their music tastes.”

Katch’s Chief Commercial Officer, John Dicconson stated, “We continue to build upon our work with major streaming platforms and studios to create a more emotional connection with audiences through taste-based programming and marketing insights. We are thrilled to be working with Cinedigm to help revolutionize the video viewing experience by aiding in the discovery of fresh new content through the use of our Media Genome.”

Katch’s extensive genomic database will be integrated directly into the proprietary content recommendation engine that is part of the Matchpoint Blueprint platform that powers Cinedigm’s apps. Through this direct integration, the recommendation engine will utilize a substantially enhanced set of data to better tailor personalized content recommendations to each user.

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