Clean Room Measurement: private joins without walled gardens
How enterprise buyers run privacy-safe match tests and outcome measurement using clean rooms and controlled joins, without exposing raw identifiers.
Since 2018
Privacy-safe enterprise data
VOSB & SDVOSB
U.S. Veteran-Owned, Service-Disabled
SCC Transfers
EU/UK/CH per privacy policy
GDPR · CCPA · CPRA
Consent-first data sourcing
What clean rooms are actually for
Clean rooms are procurement tooling: they let buyers test match rates and measure outcomes while keeping identifiers protected. The goal is not “a clean room” : it’s a governed join that supports a decision.
Match testing (pre-license)
- Seed match (10K-100K hashed identifiers) to measure usable resolution.
- Fill-rate measurement by field and confidence tier.
- Geography and exclusion scoping baked into the evaluation.
Outcome measurement (post-activation)
- Exposure → outcome joins with defined attribution windows.
- Dedupe logic across channels (CTV, mobile, web) where applicable.
- Segment-level lift rather than user-level export.
Privacy controls
- Hashed identifiers only; no raw PII movement required.
- Aggregation floors and k-anonymity style protections where required.
- Retention/deletion SLAs defined in contract.
Governance and audit readiness
- Permitted uses and downstream sharing rules documented up front.
- Sensitive-category exclusions (where applicable) enforced in joins.
- Provenance artifacts available via methodology documentation.
Next step: run a seed match
The clean-room version of “show me coverage” is a seed match against your first-party CRM. We’ll scope join keys, exclusions, and a success metric, then return match counts and fill rates, no raw identifiers exposed.
What you get back from a clean-room run
Clean rooms are most useful when the output is decision-ready. The right deliverable is a small set of tables and counts that answer “should we license this?” or “did this campaign move outcomes?”: without exporting raw identifiers.
Match testing outputs
- Matched counts + match rate by cohort and geography.
- Fill rate by field (what’s actually usable downstream).
- Confidence tiers where applicable (so buyers can choose strict vs broad).
Measurement outputs
- Exposed vs control lift at segment level.
- Dedupe logic applied across channels (CTV/mobile/web) when in scope.
- Windowing and sensitivity reads (1/7/14 days or custom).
Governance outputs
- Join spec: keys used, exclusions enforced, and retention window.
- Audit-ready notes for procurement and privacy teams.
- Delivery plan for production (Snowflake share, S3, SFTP).