A Practical Guide to Data Clean Rooms
Environments where two parties analyze combined data without either seeing the other's raw records.
Samir Haddad
What is at stake
They let advertisers and platforms measure together under privacy constraints, but they need clear questions to be worth the cost.
The playbook
- Define the questions before building
- Agree governance and output rules with partners
- Start with a narrow measurement question
- Check legal basis for data use
- Evaluate whether simpler methods suffice
Where it goes wrong
Avoid:
- Clean rooms adopted without a clear question
- Assuming privacy technology removes legal obligations
- Outputs specific enough to identify individuals
- Projects with no internal analyst capacity
The numbers behind it
| Measure | Figure |
|---|---|
| Privacy controls | raw records are not exposed to either side |
| Aggregation | outputs are aggregated to protect individuals |
| Cost | clean rooms require investment and expertise |
| Use cases | overlap analysis and measurement are common |
Getting outside help
When to hand it over: Bring in help when partners want joint measurement.
Where this comes from
- California Privacy Protection Agency — CCPA regulations
- IAB Tech Lab — Data clean rooms
The figures and practices above come from the sources listed.
Working on something like this?
We take on Digital Marketing & CRO work for teams who want it done once, properly. Tell us what you are building and we will tell you honestly whether we are the right studio for it. Start a project.
Where to go next
Spotted something wrong? Report an error on this page. We correct on the page and say what changed.
