Cookieless Approach For Audience And Outcomes Measurement In The U.S.

Nielsen announced its approach to eliminate its reliance on digital identifiers and ensure that advertisers and publishers can continue to measure confidently in a dynamic, privacy-first media environment. 

Third-party cookie deprecation is fundamentally changing the advertising ecosystem. Combined with the deterioration of other digital identifiers, there’s greater emphasis on first party data, which provides a good understanding of online users’ unique habits, from website browsing to app usage. As a result, every publisher and brand has been challenged to develop its own first party data strategy and leverage other data signals when identity is not directly attributable to an ad impression.

“If the industry has learned anything since the rise of cookies, it’s that digital media measurement must remain scalable, flexible and useful,” said Mainak Mazumdar, Chief Data Officer at Nielsen. “Nielsen’s new cookieless measurement approach will further position the company to deliver deduplication across linear and digital as part of Nielsen ONE. Our new approach to measuring authenticated and unauthenticated digital traffic will enable us to scale across channels and platforms to ensure a comprehensive view of success and uncover areas for optimization.”

In the new world order, digital traffic will ultimately move into two distinct categories for measurement following the deprecation of digital identifiers:

•     Authenticated: Traffic with identifiers on properties which have logged in environments or consented devices. To measure authenticated traffic, Nielsen will leverage all available identifiers and first-party data from participating clients, such as hashed email addresses, Unified ID 2.0 and select, verified self-reported demographic labels. This will ensure interoperability in the ad ecosystem, including with walled gardens, and simplify measurement for clients by reducing reliance on third parties.
•     Unauthenticated: Logged out traffic or traffic on properties that do not have logged in environments or where no alternative identifiers can be provided. To measure anonymous traffic, Nielsen has developed a machine learning technique with additional contextual data signals including time, browser, content and device information, as well as FLoC groups. The model is validated against the panel for accuracy. Demographics of unauthenticated behavior are also modeled and validated with panel observations for both representation and accuracy.

Late last year, Nielsen announced its ID Resolution System which will further position the company to deliver deduplication across linear and digital platforms as part of Nielsen ONE, the single, cross-media currency that will span Nielsen’s global outcomes and cross-media measurement solutions.  The Nielsen ID System serves to unify the identity data that Nielsen receives in an interoperable way across the media ecosystem.  As part of the Nielsen ID System, the Nielsen ID Graph is calibrated against and validated by Nielsen’s people-based panels, making it the only ID graph validated by a truth set informed by real-life media consumption, demographics and cross-device usage.

As Nielsen continues to evolve its technologies and methodologies for independent measurement of audiences and outcomes, it has identified a five-pronged approach to measuring authenticated and unauthenticated web traffic.

•     Interoperability: As digital identity continues to fragment, Nielsen’s use of a diverse set of identifiers and first-party data provided by clients, such as hashed email addresses, Unified ID 2.0 and verified self-reported demographic labels will ensure interoperability in the ad ecosystem to manage future changes with agility and to simplify measurement for clients.
•     Comparability: In the absence of alternate identifiers or first party data, Nielsen is able to provide comparability with its common measurement framework and data science across platforms and publishers, calibrated by Nielsen Panels. For instance, Nielsen will use time, browser and other metadata within its people-based panel to determine demographic assignments for unauthenticated audience and outcomes measurement.
•     Persistence: Nielsen is transitioning from an identity backbone supported by brittle identifiers to the Nielsen ID System, which leverages stable identifiers that remains consistent over time, offering measurement that is tied to actual people and households.
•     Confidentiality: With new, confidential computing technologies embedded into Nielsen ID System methodologies, Nielsen is bringing even more assurances of data confidentiality to audience and outcomes measurement. Proprietary confidential computing technologies enable Nielsen to run a wide variety of analytics applications, delivering faster and more flexible custom analytics capabilities to clients.
•     Measurement-Built: The Nielsen ID System’s Measurement Graph is the only ID graph calibrated against Nielsen’s panels and validated by real-life media consumption, demographics and cross-device usage to ensure precision and representativeness.