Case study: Mexican beer brand Dos Equis successfully scaled a niche live sports strategy in CTV with zero waste.
The way people search for information is changing, and that has the potential to help people navigate an increasingly fragmented TV landscape. Without the right data, however, artificial intelligence (AI) will simply reinforce existing perceptions: It can’t be trusted. Now that AI is incorporated into many other tools people use to search for information, usage …
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.
As streaming options proliferate, engagement with FAST channels is on the rise, with news and sports becoming top genres.
Solving the sports discovery problem doesn’t mean owning more content. It means providing better access to it.
Streaming congestion has become overwhelming for TV viewers. Publishers can help streamline their content discovery journeys.