What is a data clean room?
A data clean room is a secure environment where two or more companies bring their data together for analysis without handing over the underlying customer records. Each side keeps control of its data, and rules decide what can be matched, queried, and taken out.
A typical pairing is an advertiser and a media owner, such as a publisher, a retailer with an ad network, or a large platform. The advertiser wants to know how the media owner's audience overlaps with its customers, or how ads influenced sales, without either party exposing personal data.
How does a data clean room work?
- Bring the data in. Each party loads its first-party data, usually with identifiers protected, such as by hashing.
- Match records. The clean room links overlapping records across the data sets using agreed keys.
- Run approved analysis. Only permitted queries run, often with minimum audience sizes so no individual can be singled out.
- Export aggregates. Partners receive summarized results, such as overlap, reach, or lift, not raw records.
What is an example of a data clean room?
Measuring retail media against sales
A consumer brand advertises on a retailer's media network and wants to know whether the ads drove purchases.
In a clean room, the retailer's ad exposure data is matched with purchase data, and the brand sees aggregated results, such as sales among exposed versus unexposed shoppers, without seeing any individual shopper's records.
Data clean room vs. CDP vs. data warehouse
| Data clean room | Customer data platform (CDP) | Data warehouse | |
|---|---|---|---|
| Main job | Privacy-safe analysis across companies | Unify one company's customer profiles | Store and query data at scale |
| Whose data | Two or more parties | One company | Usually one company |
| Access to raw records | Restricted by design | Full, for the owner | Full, for permitted users |
| Typical outputs | Aggregated overlap, reach, lift | Audiences and profiles | Reports and models |
Why do data clean rooms matter?
As privacy rules tighten and third-party tracking weakens, companies need ways to collaborate on data without moving personal information around. Clean rooms make that possible, especially in retail media and on large ad platforms.
- Privacy-safe collaboration. Partners share insight, not raw data.
- Better measurement. Media exposure can be connected to outcomes the advertiser cares about.
- Clearer audience planning. Brands see how a partner's audience overlaps with their own customers.
- Garbage in, garbage out. Results are only as good as the first-party data each side brings.
How does Alli do this?
Alli isn't a data clean room. Its role is the first-party foundation that clean room work and other privacy-safe measurement depend on.
Alli Audience Gateway captures first-party conversion signals once and sends them server-to-server to ad platforms from one managed implementation, built to support regional privacy requirements. Alli Datasources brings first-party systems in next to media data, so results from partners can be read alongside everything else in Alli.
Explore Alli Audience GatewayData clean room FAQ
What is a clean room in advertising?
A secure environment where an advertiser and a media owner match and analyze their data together, getting aggregated insights such as reach or sales lift without sharing raw customer records.
Are data clean rooms privacy compliant?
They're designed to reduce privacy risk by restricting access to raw records and limiting outputs to aggregates. Compliance still depends on consent, contracts, and how each party uses the results.
Who uses data clean rooms?
Advertisers, publishers, retailers with media networks, and large ad platforms, most often for audience planning and measurement.
What is the difference between a clean room and a CDP?
A CDP unifies one company's customer data into profiles it can use directly. A clean room lets several companies analyze combined data without any of them seeing the others' raw records.
Last updated ‹ Back to the glossary