By Ashley Bailey, Product Marketing Manager, M&E, Veritone –
Consumer demand for all types of content, available on all platforms, has never been greater. For M&E companies, it’s a good problem to have. While being challenged like never before to capture and hold ever-broader audiences by delivering the content viewers crave, these companies are looking at a potential gold mine of new opportunities to develop lucrative new revenue streams.
Content, at its very core, is data. And, just as companies often undervalue and underutilize their data, they do the same with their critical content assets — often resulting in loss of information, incomplete understandings, missed insights and potential loss of revenue. But there’s good news: advanced digital asset management technologies are coming to the rescue by applying cutting-edge, AI-powered cognitive processing.
The best way to think about the asset management challenge is to break it down into key phases in the content lifecycle: creation, management, delivery, monetization and analysis. Let’s take a look at the roles digital asset management and cognitive processing play in each one.
Effective asset management starts at creation. Right at content ingest and transcoding, cognitive processing is used to extract comprehensive and intelligent metadata from each asset. Veritone’s aiWARE, for instance, unlocks access to hundreds of cognitive engines across 16 classes, including facial recognition, object recognition, audio fingerprinting, OCR, translation and more. Tagging each asset with such attributes smooths the way for the content to be licensed for a variety of projects — documentaries, films, commercials, or TV shows — for rights holders who desire to monetize their content through licensing.
A subset of creation is the ability to repurpose archival footage to create a program. If the archived assets were previously ingested with rich metadata, it’s that much faster and more efficient to find the relevant clips.
When stored in a built-for-purpose, centralized and permission-based repository, vital content assets can be easily managed throughout their lifecycle. Augmented by AI, digital asset management helps organizations analyze, share and index media offerings automatically, which leads to streamlined workflows and enhanced discovery experiences. The key is an advanced cognitive engine that integrates seamlessly with digital media archives.
With the proper digital asset management foundation, media enterprises deliver the right content to the right audience, at the right time. That’s a critical capability in today’s increasingly fragmented media environment, in which broadcasters need to tailor their content to new audiences, rights holders need to get their content into the right hands, and content licensees need access to the assets they will turn into creative projects. With AI-powered digital asset management, stakeholders download assets rapidly and securely in the desired file format. Likewise, organizations can easily share assets with specific internal or external recipients, protected by explicit permission controls.
The stage is set for content monetization right back at the early creation stage, when—as we’ve said—advanced AI cognition technologies extract a rich set of metadata out of each asset at ingest. With intelligent metadata built into every asset, it’s seamless for media organizations to access and monetize the asset continuously through licensing, digital publishing on social platforms, content claiming strategies, and other consistent revenue streams.
For rights holders, a key element is the ability to make content available for easy purchase (licensing), either with a system that enables them to manage their own licensing contracts, rights and clearances, or a third-party service that allows them to outsource these functions. In either case, the easier these key business functions are for rights holders to manage, the more monetization opportunities they can pursue. At the same time, these systems can help them enforce their rights and ensure that their content is not being accessed illegally or monetized without authorization.
Finally, the ability to perform ongoing analysis on the content further enhances an organization’s ability to take full advantage of its valuable assets. Since each asset has been automatically tagged with metadata using facial recognition; object and logo detection; voice, location, and sentiment recognition; or other cognitive processing, it’s simple to analyze content and glean valuable insights.
Rights holders, broadcasters, sponsors and producers can leverage the abundance of AI-enriched content to analyze broadcasts for product placements, in-venue sponsorship inclusions, and feedback for talent on specific scenes.
In the end, it’s all about content — how to manage it, how to sell it, how to make it easy for licensees to buy and how to understand the mine of data buried within. With sophisticated AI technologies driving digital asset management, media enterprises improve operational efficiencies, keep their content in their control, optimize advertising and sponsorship opportunities, and continuously grow their revenue streams.