Data Clean Room Overlap Reach Calculator

Quantify the jointly addressable audience inside a privacy-safe clean room and gauge incremental conversions with optional rate assumptions.

Total individuals or identifiers contributed by Partner A.
Total individuals or identifiers contributed by Partner B.
Percentage of Cohort A records that successfully match to Cohort B within the clean room.
Defaults to 0%. Apply the expected conversion rate for the overlapped audience if you need projected outcomes.

Use alongside platform-level privacy reviews and legal agreements that govern data collaboration and activation.

Examples

  • 600,000 vs 450,000 cohorts, 38% match, 3.5% conversion ⇒ 171,000 overlap, 879,000 unique reach, 5,985 conversions
  • 820,000 vs 1,100,000 cohorts, 52% match, no conversion rate ⇒ 426,400 overlap, 1,493,600 unique reach

FAQ

Should I use impressions or people for cohort sizes?

Wherever possible, work with deduplicated people or household counts. Using impressions inflates overlap and leads to unrealistic reach claims.

How do I reflect asymmetric match rates?

If Partner B reports a different match rate, run the calculator twice—once with A as the base and once with B—and present the range with commentary on ID graph differences.

Can I incorporate frequency caps?

Yes. After computing overlap reach, divide planned impressions by overlap size to check frequency against policy limits and adjust line items accordingly.

What if conversion rate varies by segment?

Segment the cohorts before uploading to the clean room, then run separate overlap calculations for each segment with conversion assumptions calibrated to historical performance.

Additional Information

  • Match rate is measured against Cohort A; the overlap is capped at Cohort B to avoid exceeding the smaller partner's supply.
  • Unique reach equals the union of both cohorts minus the duplicated overlap.
  • Optional conversion calculations help quantify incremental deal volume or onboarding potential.

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