ACR data is invaluable, but only if it lives within DSPs

TV advertising has more signal than it knows what to do with. The problem isn't the data — it's where the data sits when it's time to actually buy.

Written by Grant Hollis · Bureau Media · Jun 1, 2026

The data is there. The plumbing isn't.

TV advertising has never had more information to work with. Identity graphs, contextual signals, outcome measurement, viewership data — the stack is deep. And yet campaigns still underperform, frequency caps still fail, and advertisers still reach the same household six times with the same spot in a single evening.

Oscar Rondon, vice president of data and measurement solutions at Nexxen, puts the diagnosis directly: today's TV advertising doesn't have a data problem. It has an execution problem.

That framing matters, because it shifts the conversation away from acquiring more signals and toward asking whether the signals you already have are actually usable at the moment of purchase.

What ACR actually does

Automatic content recognition is the technology embedded in smart TVs that identifies what's playing on screen — whether that's a streaming show, a linear broadcast, or a gaming session. It works by matching audio or video fingerprints against a reference library, and it does so at the device level, which means it captures viewing behavior regardless of which app or input source is active.

For advertisers, that's significant. ACR data tells you not just that a household owns a connected TV, but what that household has actually watched — and crucially, what ads it has already seen. That makes it useful for three things that are genuinely hard to do well in CTV: deduplication across streaming services, frequency management across publishers, and competitive conquesting based on verified exposure.

The problem is that most ACR data doesn't live where buying decisions get made.

The gap between insight and activation

When ACR data sits in a separate measurement platform or data clean room and has to be exported, matched, and uploaded before it can inform a campaign, several things go wrong. Match rates degrade. Latency builds in. By the time the audience segment reaches the DSP, the viewing behavior it's based on may be days old — which in a fast-moving content environment is a meaningful problem.

More fundamentally, a data asset that requires manual intervention to activate isn't really part of the buying workflow. It's a report that someone has to act on, which means it depends on someone acting on it correctly and quickly. That's a fragile system.

The alternative — integrating ACR data natively within a DSP — means the signal is present at bid time. Suppression lists update in near real-time. Sequential messaging can be triggered based on verified exposure rather than probabilistic inference. Outcome measurement can be tied directly to the impression that drove it.

Why this is a structural issue, not a vendor problem

It would be easy to read this as a pitch for any single platform's integrated stack, and to some extent that's what sponsored content in this space tends to be. But the underlying point holds regardless of who's making it.

The CTV ecosystem has fragmented in ways that created genuine measurement complexity — multiple walled gardens, inconsistent identifiers, no universal currency. ACR data emerged as one of the more reliable ways to see across that fragmentation, because it operates at the device level rather than the app level. But that advantage only materializes if the data can be operationalized.

Right now, too much of the industry's measurement sophistication exists in a layer that's adjacent to buying rather than embedded in it. Dashboards that inform strategy after the fact are useful. Data that shapes decisions in the moment is what actually moves outcomes.

What integration looks like in practice

For a DSP to make genuine use of ACR data, the integration needs to go beyond a one-time data import. It requires a live connection that updates audience segments as viewing behavior changes, the ability to apply ACR-derived suppression at the impression level, and attribution logic that can tie a specific exposure — not just a campaign — to a downstream action.

That's a higher bar than most current setups meet. But it's also the bar that makes ACR data worth paying for. Without it, buyers are essentially purchasing a research product and hoping someone translates it into media decisions accurately and on time.

The TV advertising industry has spent years building richer and richer data assets. The next phase of maturity is making those assets executable — not just reportable.

Key takeaways

TV advertising's core problem in 2025 is execution, not data volume — the industry is awash in signals that never make it to the buying interface.
ACR data, which tracks what content has actually played on a TV screen, is among the most precise audience signals available for CTV targeting and frequency management.
When ACR data lives outside a DSP, buyers face manual exports, latency, and match-rate decay that erode its practical value before a single impression is purchased.
Integrating ACR directly into DSP infrastructure allows for real-time suppression, sequential messaging, and outcome measurement without the friction of third-party data handoffs.
Nexxen's Oscar Rondon frames the challenge plainly: the industry isn't short on dashboards or identity graphs — it's short on systems that connect those assets to actual media execution.

FAQ

What is ACR data and why does it matter for TV advertising?

Automatic content recognition (ACR) is technology built into smart TVs that identifies what content is playing on screen by matching audio or video fingerprints. For advertisers, it provides verified, device-level viewing data — including ad exposure history — that can be used for audience targeting, frequency capping, and cross-publisher deduplication in connected TV campaigns.

What is a DSP and why does ACR data need to live inside one?

A demand-side platform (DSP) is the software advertisers and agencies use to purchase digital and streaming ad inventory programmatically. When ACR data is integrated directly into a DSP rather than sitting in a separate measurement tool, it can influence buying decisions in real time — enabling live suppression, sequential messaging, and impression-level attribution rather than after-the-fact reporting.

What goes wrong when ACR data isn't integrated into the buying workflow?

When ACR data has to be exported from a measurement platform and manually uploaded into a DSP, match rates degrade, latency accumulates, and the audience segments that reach the buying interface may be based on viewing behavior that's days old. The result is that a high-quality signal loses most of its practical value before a single impression is purchased.

Is this problem unique to CTV, or does it affect linear TV advertising too?

The execution gap is most acute in connected TV, where programmatic buying infrastructure exists but data integration standards are still maturing. Linear TV has historically operated on panel-based measurement with less real-time data infrastructure, so the gap between signal and activation is different in nature — but the CTV environment is where the mismatch between data richness and execution capability is most visible and most costly.

Who is Oscar Rondon and what is Nexxen?

Oscar Rondon is vice president of data and measurement solutions at Nexxen, an advertising technology company that operates a DSP and supply-side platform with a focus on connected TV and streaming. Rondon's argument — that TV advertising has an execution problem rather than a data problem — frames the case for embedding ACR data natively within programmatic buying infrastructure.

Citations

ACR data is invaluable, but only if it lives within DSPsToday's TV advertising doesn't have a data problem; it has an execution problem, according to Oscar Rondon, VP of data and measurement solutions at Nexxen.
ACR data is invaluable, but only if it lives within DSPs — DigidayThe industry has never been richer in signals, ranging from contextual intelligence to identity graphs, outcome measurement to an overload of dashboards, yet TV strategies still break down at execution.
Digiday Media feedBureau research source: Digiday