One pipeline, four things you get out of it.
Grade your 1P data
Resolve your file 1:1 against 302M validated Person IDs and 129M households. Every linkage comes back scored into Data Ratings tiers (AAA–B), so you know which records are real people before you spend against them.
Segment and model it
25+ validated demographic attributes on the matched file, cross-validated across the Collective. Build segments and models on attributes that have been checked rather than attributes you inherited.
Grow it with Data Rated Audiences
Extend from your validated seed using the Is-alike model, a demographic similarity model with no behavioural propensity guesswork inside it. Every added record carries the same grading as your seed.
Send it 1:1 to your destination
Activate through direct 1:1 PII integrations into the destination you choose, with no device-ID bridge in the path. The match rate you verified is the match rate that runs.
Your match rate is counting guesses as reach.
Your file holds one email per customer, usually the one they typed at checkout. People run on several. Checkout against login, personal against work, purpose-specific inboxes, and churn under all of them.
Status-quo matching finds the one string you collected, or nothing. ID Max resolves that string to the person, returns every validated email that person uses, then every validated ID for the adults in the household where the purchase decision gets made. That is the arithmetic behind a 40–200% lift in validated matches.
typical validated match-rate lift
validated emails per person and per household
Data Ratings tiers on every match
Segment and model on attributes that survived a check.
The State of Data Accuracy 2026 found error rates reaching 60% on common demographic attributes. Those are the attributes campaigns get targeted, priced and measured against. Modelling on them compounds the error rather than correcting it.
Every audience ID Max resolves carries 25+ demographic attributes cross-validated across the Data Collective, with the distribution visible before you build a segment. The audience you activate is the audience you can describe to a client and defend to a measurement partner.
Grow past your file without diluting it.
Data Rated Audiences extends your validated seed with multi-sourced records from the Data Collective, 24+ providers covering roughly 95% of the U.S. Census, with each incremental record scored and filtered before it joins the audience.
Expansion is configurable. Include or suppress your originals, expand toward census-representative targets, and keep the same Data Ratings grading on every added record that your matched file carries.
One hop to the destination you choose.
The IP-to-email and IP-to-postal bridges that most CTV identity quietly rides on are 13–16% accurate. That is how premium budgets deliver roughly $0.12 of on-target value per dollar through the traditional multi-hop chain.
A direct 1:1 PII match puts roughly $0.93 of every dollar on the people you intended. Data Rated Audiences sit inside FreeWheel’s ad-buying platform today, and the same audiences activate across The Trade Desk, Yahoo, Magnite, Roku and Paramount, or into a destination of your choice.
One integration lifts every client file that flows through it.
Embed ID Max as the native match utility in your stack. Inbound files stitch into the first-party profile store at higher validated rates, producing a better golden record. Outbound audiences activate with the maximum validated ID set, graded and configurable per client.
The free Match Test gives your teams a proof point on each client’s own data before anyone commits a dollar.