A data clean room is a piece of software that allows organizations to bring data together for joint analysis under defined guidelines and restrictions.

The process involves two entities – such as an advertiser and a publisher – who upload their first-party data to the data clean room. Then, the data undergoes security and privacy-protection measures, such as pseudonymization, restricted access, or noise injections, that remain in place to ensure none of the parties can access personal data or data of the other party. Both parties get information in the form of cohorts and aggregated reports. The data can then be activated for various advertising and marketing efforts. For example, it can be applied for targeting a specific demographic, audience measurement, and analysis.

Data clean rooms contain aggregated, anonymized user information considered non-personally identifiable information (non-PII). The involved contributors can benefit from the information in the joint data set from two or more parties without gaining access to specific data about individual users. At the same time, they cannot export or copy the data set of the other contributors, and no one outside the data clean room can access the user-level data.

The demand for data clean rooms is growing due to privacy regulations, the deprecation of third-party cookies, and the need for advertisers to better target users.

Read more about privacy-friendly solutions to marketing:


  • Five things every marketer should know about web analytics in 2026

    Web analytics is changing fast. AI is moving from buzzword to actual business impact, privacy rules keep shifting on both sides of the Atlantic, and marketing teams are rethinking their tool stacks. What does this mean for analytics strategy in 2026? We asked industry experts to share their predictions.

  • first party data

    First-party analytics without consent: Your Digital Omnibus compliance guide

    The Digital Omnibus is the European Commission’s simplification initiative to modernize the EU’s digital rulebook and reduce consent fatigue. The framework would enable first-party analytics without consent when specific criteria are met, ending years of uncertainty about the use of legitimate interest for web statistics.