3 ways TV advertisers can overcome a fractured identity framework landscape

Audience fragmentation across TV advertising, in combination with signal loss due to privacy changes, have made it harder for advertisers to scale audience targeting, activation and measurement. Advertisers are rightfully concerned they are not reaching critical audiences due to channel silos, or that they may be reaching some audiences too often due to poor frequency calibration, risking audience fatigue. 

These uncertainties are caused by the ineffective matching of identity spaces and standards, which can cause advertisers to forgo reach and performance results. On the publisher side, organizations are also losing important opportunities to demonstrate the full potential of their inventory due to identity loss in planning, activation and measurement. 

To tackle the challenges of targeting, activation and measurement in the converged TV landscape, identity must be leveraged. Multiple new frameworks are emerging to challenge or complement Nielsen, which has been TV’s traditional currency until recently. But for advertisers, the proliferation of currencies risks adding more unmanageable complexity. 

So which currency is TV’s most reliable source of truth? And how do advertisers work across multiple data platforms in each of these areas? 

Here’s the thing: The question is not which currency will dominate TV measurement. It’s how advertisers will calibrate and translate targeting, activation and measurement across currencies, channels and devices. In other words, TV advertising needs an identity framework that works across those silos. Here’s what advertisers need to understand about the interoperable identity challenge and how the TV ecosystem can overcome it. 

Identity—not audience—is the new currency 

As NBCU’s Linda Yaccarino recently stated, identity is the new currency in television. But what does that really mean? Identity and audience data are the core units exchanging hands multiple times in the industry, from planning to activation and finally measurement. The advertisers who will be most successful in this new landscape are those that can use multiple currencies and publisher data partnerships to understand who their audience is and where they spend time across channels, devices and platforms.

The key here is for advertisers to align themselves with publishers, whose first-party data has become far more valuable as cookie-based data dries up due to signal loss. Those advertisers then need to build up the technology and expertise required to understand audience identity beyond the walled garden of any one publisher. 

Major advertisers will not only tap into this intelligence but also combine it with their own first-party data. Thus, they can understand audience behaviors at scale, use third-party data to target them across the TV ecosystem, and measure the impact of exposure against business outcomes. This is the new standard marketers should be striving to meet.

Interoperability and ID translation: the bedrock of TV advertising today

As advertisers continue to be challenged by identity fragmentation, the emergence of multiple new currencies and first-party audience data platforms presents a new problem for TV ad targeting and measurement—interoperability. It’s one thing to flood an advertiser or agency with data on hundreds of millions of consumers; it’s another to organize that data into strategic, actionable insights.

There are three pillars of an interoperable identity framework for TV targeting and measurement: match rates, translation speed and accuracy. 

1. Verified match rates. Advertisers are tasked with matching as many of their first-party IDs as possible to those of their data partners, and making sure those IDs are also matched accurately to households. After that, the single most important step in achieving strong match rates is the identity graph partner. By layering multiple identity graphs, data points can be presented with multiple match-point methodologies from disparate architects, mitigating the risk of low match rates by diversifying the pool of providers. 

2. Near real-time insights. The framework should also be able to efficiently match an advertiser’s own audience to those of an array of publishers, possibly even within minutes. For years, TV advertisers have been complacent with backward-looking insights that rolled in after campaigns had concluded. With reporting now available in real-time, advertisers should be able to measure performance based on any key performance indicators and optimize continuously toward reaching their goals. Cookieless solutions are paramount to provide the scale that third-party cookies once delivered. And all of this needs to be done in a privacy-compliant clean room that supports the velocity needed to respond and optimize quickly. 

3. Loss-proof accuracy. From onboarding first- and third-party data, to sending IDs to DSPs, SSPs and ad servers, and finally sending return path data to dozens of measurement partners, there are lots of opportunities for value to get lost in translation. In fact, it’s estimated that data platforms are losing 30% to 50% of IDs with each handshake. ID translation is the area where most of the ID waste is happening, and the compounding effect of ID loss is mind blowing. Most industry experts often overlook the value of an ID graph to combat ID waste, but true accuracy cannot be achieved without taking steps to shore up that ID loss. 

All of the above is why interoperability and translation are the linchpin of today’s TV advertising. With match scale, accuracy and translation speed, advertisers can build a compelling picture of their audience—and reach the consumers who matter most.