LLMs are far from perfect, and in the world of entertainment, they think they know more than they actually do.
Case study: Mexican beer brand Dos Equis successfully scaled a niche live sports strategy in CTV with zero waste.
In order for enterprise LLMs to provide the next-gen content experiences they have the ability to, access to trusted, industry-specific data is paramount.
GenAI has the power to connect people with the content they’re looking for, but trust is a considerable hurdle.
The way people search for information is changing, but without the right data, AI will simply confirm that it can’t be trusted.
Bad data is a real threat. LLMs are powerful tools, but they are only as good as the information they can access.
Despite their roots in the U.S., the five global SVOD services tracked in the Gracenote Data Hub offer more global content than U.S. content.
While content libraries grow and distribution channels multiply, sports have become the hottest commodity across the streaming landscape.
RAG and MCP each address the limitations of LLMs, but they approach the issue in fundamentally different ways.
FAST channels will become increasingly dependent on metadata to inform ad buys in programmatic systems.
Streaming viewers have become overwhelmed by choice and fragmentation. This sentiment is mounting, and it has a range of downstream effects.
Viewer frustrations are on the rise as streaming service congestion increases, highlighting opportunities for improved UX and content discovery.