Introducing Wurl’s Content Intelligence Platform

Pick any weeknight. Somewhere, an episode of FBI is playing. On screen, just before the ad break, the team is gathered in the bullpen late at night, coffee mugs in hand, talking through the case.

Then an ad request goes out. Show name and channel name are obscured, and the genre attached to that request? “Entertainment.”

Technically that’s accurate. But it’s not providing enough relevant information for a brand that would value this high-anticipation scene, or a coffee brand that would love exactly this kind of product-alignment but has no way of knowing the moment exists.

This is one of the fundamental challenges with CTV advertising today. There’s an enormous amount of information on screen, but relatively little of that information makes its way to the buyer.

Wurl’s Content Intelligence Platform was built to help close that gap.

What do buyers actually see today?

The short answer, a pretty fuzzy picture. Genre may be assigned at the channel level rather than to the program actually airing. And even when it’s accurate, there’s little standardization. “Entertainment,” “general variety,” “drama,” and “crime-drama” might all describe the same program. Even more problematic, program and channel names can be obscured or missing altogether.

Why does this happen? CTV is a fragmented ecosystem. Hundreds of publishers, streamers, and intermediaries pass along metadata using different systems and standards, while some information is intentionally withheld from the programmatic bidstream. By the time an ad opportunity reaches a buyer, the signals around it can be broad, inconsistent, or missing entirely.

What makes this frustrating is that buyers aren’t asking for anything new. Linear TV has offered known programming, dayparts, and verified ratings for decades. Digital advertising brought page-level context and verification. Buyers are accustomed to knowing what they’re buying and using that information to price, measure, and defend their ad spend.

CTV has pieces of that visibility, but not consistently or at scale. And that gap has a cost. Adults now spend roughly 20% of their daily media time with CTV, but the channel captures only about 8% of ad spend. That lag is partly because it’s difficult to value a channel you can’t see into.

Better context starts upstream

Most conversations about contextual targeting focus on brand safety and suitability. While these things are obviously important, they’re only part of what good content intelligence can do.

It’s worth noting how many advertiser problems come down to the same question, which is what’s actually on screen. Is this show premium? Is this scene somewhere the brand should be? Does what’s happening right now have anything to do with what the ad is selling? An advertiser who could simply watch the content would know the answer to all three.

Think back to the FBI example. An ad matching the emotional tone and content of the scene would land differently here than the same ad appearing after an unrelated scene. The content has already helped set the stage for the creative.

We’ve seen the impact of this in our own research. Relevant moments earn 2.4 times the attention of poorly timed ads.

The problem is that the metadata available in the bidstream today doesn’t always provide an accurate or granular view of the source content. For contextual signals to be useful, they need to start upstream, with the content itself.

That’s true whether you’re authenticating program-level signals so buyers can understand and trust what they’re purchasing, or analyzing scenes and objects to understand what’s happening right now. 

Great content intelligence needs room to run

Here’s the interesting part: much of the technology required to understand CTV content already exists. KERV can identify individual objects within a frame. Peer39 provides verified suitability signals. 

The challenge is making all of that intelligence actionable across enough CTV inventory to matter.

Doing that requires three things at once:

1. Content: Visibility into what is streaming on the screen in real time.
2. Inventory: A way to identify the ad opportunities corresponding to that content.
3. Bid request enrichment: The ability to attach the signal to the bid stream before the request reaches a buyer.

Getting all three is harder than it sounds.

For companies who can enrich the bid stream with contextual signals, streaming poses scale challenges. FAST alone includes hundreds of content publishers, each potentially requiring a separate relationship and technical integration. And even after a data partner integrates with one publisher or streamer, they typically reach only about a portion of that channel’s inventory, because publishers and streamers due to the inventory split.

So we have contextual companies building increasingly sophisticated intelligence. We have DSPs investing precious resources in integrations to support it. And we have advertisers looking for better ways to understand and curate their CTV buys.

What we haven’t had is an easy way to connect those capabilities to CTV supply at scale, so that all parties can fully benefit from the opportunity.

This is where Wurl comes in

Wurl occupies a unique position in the streaming ecosystem because we’re not simply analyzing content metadata after the fact. Our technology is part of the infrastructure that puts that content on screen.

Hundreds of content owners build and operate their FAST channels using Wurl – more than 5,000 channels in total.

That upstream position changes what’s possible.

We know what is playing in the seconds before an ad break. We can associate that content with the corresponding ad opportunity. And we can enrich the bid request with contextual intelligence before it reaches the buyer.

Our partners bring their intelligence. Wurl gives that intelligence access to live content, corresponding inventory, and a path into the bidstream.

For DSPs, this means means:

• One direct oRTB connection to more than 140 billion enriched CTV impressions monthly 
• A significantly larger footprint for contextual partners they already support
• The ability to build differentiated contextual offerings using Wurl’s own scene-level taxonomy

For advertisers, it means knowing what an ad ran beside, and being able to place it next to the content it was made for.

Our goal is a better streaming ad ecosystem

FAST viewing hours jumped nearly 30% last year, and US viewership is projected to hit 131.4 million in 2026. That’s a lot of screen time riding on metadata that too often says little more than “Entertainment.”

And that matters for where ad dollars go.

Better content signals create value throughout the ecosystem. Publishers can monetize suitable inventory that broad category filters might otherwise block (including brand-safe moments within news programming, for example). Advertisers gain relevance and transparency without relying solely on identity-based data. Viewers get ad experiences that feel more connected to what they chose to watch.

At Wurl, we’ve always believed our position in the streaming ecosystem gives us an opportunity to solve some of the foundational challenges holding CTV back. Our Content intelligence Platform is another step in that direction.

Wurl’s Content Intelligence Platform is available now to partners across the programmatic ecosystem. Learn more →