Inside the ANA’s new data framework: a marketer’s quick guide

Treat this as the short version of what the ANA thinks every marketer needs to do now that third-party cookies are on life support, along with what you should be testing before the end of the year.

The data strategy value chain

At its core, the ANA says data is only useful if it connects both sides of the value chain: the consumer and the marketer. Consumers want convenience, relevant offers and personalized experiences. Marketers want segmentation, insights, audience activation, measurement and optimization.

Every link in that chain depends on data – and on using it responsibly. That’s the context for the ANA’s new Framework, designed to help marketers deliver value to consumers and business results.

The ANA’s Data Solutions Framework at a glance

The big five data power plays

1. First-party data is the star of your stack

Collect it directly from your customers (purchases, loyalty sign-ups, feedback forms) and use it to understand behavior, create lookalike audiences and personalize at scale while keeping privacy front and center. Build trust first. Consumers share more data with brands they trust. The ANA points to consistent UX, transparency and clear privacy policies as non-negotiables.

Case in point: a beauty brand used first-party signals and Meta’s Conversions API to re-engage shoppers, driving a 20% incremental sales lift and a 173% jump in ROAS.

2. Data clean rooms aren’t just for techies

These secure environments let you match your data with partners (retailers, publishers, franchises) without actually handing it over. They’re especially useful for brands that lack direct customer relationships (think CPGs) or for precision targeting and measurement when privacy matters.

Case in point: a fintech brand used a clean room with a publisher partner to divide the target audience into exposed and not-exposed groups to determine the incremental impact, delivering an 18% boost in app downloads.

3. Cookieless IDs are the new passport

Universal IDs, built from encrypted first-party identifiers like email, allow targeting and measurement across devices without the old cookie baggage. Combine deterministic (precise) and probabilistic (scaled) approaches and expect AI-powered intelligent matching to keep pushing match rates up.

4. ID-less signals still have a place

When you do not have identifiers, you can still target and measure with aggregated or contextual signals. Examples include Google’s Privacy Sandbox Topics API, geo-contextual targeting and marketing mix modeling. These are less precise, but faster to implement and often cheaper.

5. Marketer data leadership is non-optional

The ANA wants marketers to get technical. Stop treating data leadership as hygiene and start seeing it as transformation. Know your data flows, collaborate with IT and legal, ask vendors hard questions about accuracy, sourcing and privacy and constantly hunt for new privacy-safe data sources.

Shifting gears: what to do next

• Audit your first-party data: Identify what identifiers you have, how clean it is and where it is stored.

• Pick one or two high-value use cases: Test re-engaging lapsed customers or lookalike acquisition using a cookieless solution alongside your current cookie-based approach.

• Start small, then scale: The ANA recommends a “beta mode” mindset: pilot with a sample audience before rolling out end-to-end.

• Get cross-functional buy-in early: Privacy approvals and tech integration always take longer than expected, so loop in IT and legal at the start.

• Measure against clear KPIs: Define what success looks like up front so you can prove value – or stop the effort quickly.

If you take just one thing away, it’s this: stop treating third-party cookies as your crutch. Build a portfolio of solutions now – from clean rooms to contextual signals – or risk being left behind if and when the last cookie crumbles.