From Probabilistic to Proven: The Deterministic Turn in Audience Data Strategy
Over the last several years, the TV industry has taken big strides to become more data-driven. There is no question that technology has improved and innovations have made the video advertising workflow smarter, giving advertisers the ability to buy audiences across screens, then measure campaign success in a more unified manner. But underneath all that sophistication lies an uncomfortable truth: much of audience targeting is still built on probabilistic guesses of who is on the other side of the screen.
In a reality where media budgets are scrutinized and advertisers are under immense pressure to prove performance, guessing is no longer good enough, especially as we head into a 2026 upfront cycle defined by accountability and transparency.
If the identity signals used to build and target audiences are wrong, then you may not be reaching your audience at all. Not only is audience reach broken, but if the data used for targeting is inaccurate, you’ll never achieve accurate measurement, either. On the other side of the coin, publishers may find that a large percentage of accurately delivered ads are appearing out-of-target due to flawed identity resolution. In both cases, the reality is the same: you can’t prove media exposure drove real business outcomes, because you don’t actually know who saw what.
As an industry, we must make 2026 the year we shift away from probabilistic signals of audience identity, like IP addresses, to more deterministic and higher-fidelity signals that can reliably connect impressions to households, and ultimately, to the business outcomes that CMOs are on the hook to deliver.
The problem with probabilistic
At the dawn of data-driven advertising, when using any data to determine audience identity was a novelty, probabilistic signals were a reasonable starting point. Then, as streaming took off and devices multiplied, IP addresses became the convenient way to approximate who might be watching. They’re used to infer that multiple devices under the same roof belong to the same household or that certain patterns of activity indicated a likely viewer.
But IP addresses are not a perfect proxy for audience identity. Mobile devices move. Home networks change. The same IP can be associated with a family of five one month and a single occupant the next. When those shaky signals become the source of truth for household identity, all of the sophisticated targeting built on top of them becomes misaligned, and makes tying exposures to outcomes impossible.
In fact, based on a recent study by CIMM and GoAddressable, IP addresses typically fail to accurately link to a household’s postal address about 87% of the time. Performing a similar graph analysis, OpenAP also discovered that when top data providers have the same IP in their graphs, they only agree on which postal address to link to roughly 10% of the time.
The result is data-driven campaigns that are based entirely on a misinformed collection of data points which ultimately miss the target. Probabilistic identity will always have a role in audience modeling and expansion. But as the basis of cross-platform targeting and attribution, it has hit its limit, and 2026 will be the year those limits materially impact planning and performance if left unaddressed.
It’s time for advertising’s deterministic era to begin
The good news: alternatives to probabilistic signals exist now, and are already in use across much of the premium video ecosystem.
Deterministic identity signals, such as authenticated subscriber data from ISPs and premium publishers, can provide a far more accurate view of which household is behind a given impression. In these cases, a direct relationship with the consumer allows for secure and accurate data collection, and opens the door for precise campaign measurement on outcomes.
When those signals are used as the core spine for audience construction and targeting, identity becomes the center of gravity for the entire workflow. For brand marketers, that’s the difference between broad guesses that a campaign drove business results, and being able to confidently say, “we know these households were exposed and we know what they did next.”
A source of truth for audience identity is the common denominator to overcome fragmentation
Simply swapping IP addresses for better signals is not enough, because the way identity signals are mapped to households is often inconsistent across providers and platforms. Different rules for when to link or unlink IDs, divergent definitions of what constitutes a household, and opaque matching logic all add up to a familiar problem: misalignment.
When one partner builds and targets an audience using one set of identity rules, and another measures the performance against the same audience but using a different set of rules, the numbers don’t match. To publishers, campaigns look under-delivered when they’re not. To buyers, deduplicated reach is impossible to calculate reliably. Trust erodes, not because anyone is acting in bad faith, but because everyone is counting the same audience differently.
With 2026 upfront commitments locking in billions of dollars, this misalignment becomes more than an operational disadvantage, it becomes a financial liability.
If deterministic identity is going to fulfill its promise, we need more than just better data. We need an audience of record as a roadmap for how that audience data is resolved and used.
Key questions for advertisers to ask in 2026
If you’re an advertiser, it’s time to ask harder questions about the identity methodology of the data vendors and measurement companies you work with, especially in the lead up to BY26-27 upfront conversations.
How much of your audience’s identity is guided by probabilistic signals like IP address, and how much is anchored in deterministic, household-level identity? What percentage of your original target audience is consistent across platforms? If you don’t know, you should.
The goal here isn’t perfection, it’s progress. Moving from a world where misaligned, probabilistic signals quietly undermine your strategy, to one where deterministic, standardized audience identity makes every dollar more accountable and every outcome metric more reliable.
Let’s make this the year we stop guessing, and begin proving campaign performance, and ultimately, outcomes.
[Editor's note: This is a contributed article from OpenAP. Streaming Media accepts vendor bylines based solely on their value to our readers.]
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