With cookie deprecation and privacy laws looming, data clean room usage is on the rise as marketers look for ways to bring together their data and insights without exposing the raw data to other parties. However, the cost of the tech, along with the knowledge needed to implement it, is sometimes a barrier. 

What is a data clean room? 

A data clean room is a secure digital environment where multiple parties can commingle their first-party data to produce audience and campaign insights. 

In its initial guidelines for data clean rooms, the Interactive Advertising Bureau (IAB) Tech Lab defined a data clean room as a “secure collaboration environment which allows two or more participants to leverage data assets for specific, mutually agreed upon uses, while guaranteeing enforcement of strict data access limitations.” 

Benefits of data clean rooms for marketers

The top three drivers of data clean room use among North American marketers are in-depth analytics, the ability to measure campaign results, and the ease of data integration, according to data from a Q4 2022 survey by the CMO Council. 

  • In-depth analytics (attribution) help marketers track attribution more effectively, which can improve ROI and inform future investments.
  • Stitching together data from multiple sources (measurement) also enables marketers to measure campaign effectiveness across channels and create a more complete picture of the customer journey. 
  • Privacy compliance is also an important benefit of data clean rooms. Many states are enacting privacy regulations that limit how brands can collect and use consumer data. But data clean rooms help to keep that data safe and anonymous, which will help companies stay compliant. 

Types of data clean rooms (with examples)

There are two types of data clean room solutions: 

  • Some are owned and operated by walled gardens. 
    • Examples of clean rooms operated by walled gardens include Amazon Marketing Cloud, AWS Clean Rooms, Google’s Ads Data Hub, The Walt Disney Co.’s data clean room, Pinterest’s data clean room (in partnership with LiveRamp), and NBCUniversal’s data clean room. 
  • Others are provided by independent third-party clean room platforms or vendors. 
    • Examples of third-party data clean room providers include Snowflake, Habu, LiveRamp, InfoSum, and AppsFlyer.

Both groups are robust, but the former is growing more quickly as sellers jump on the bandwagon, often partnering with third-parties on data clean room initiatives. 

What marketers need to know about data clean rooms

Only 20% of North American marketers had a data clean room as of Q4 2022, according to CMO Council research. However, another 24% said they were planning on using one. As marketers explore the new technology, there are a few things they should know about the role it plays in identity resolution, how it differs from data management platforms (DMPs) and customer data platforms (CDPs), and what barriers there are to adoption. 

How do data clean room solutions fit into the larger identity resolution picture? 

ID resolution—identifying individual users across digital touchpoints—is critical for marketing success, especially as legacy identifiers like third-party cookies deprecate. Data clean rooms are just one solution to help marketers in a post-cookie world. Other solutions include universal IDs, a heavier reliance on first-party data, probabilistic solutions, and contextual targeting. 

How do data clean rooms differ from DMPs or CDPs?

The biggest difference between data clean room solutions and DMPs/CDPs is privacy. All three technologies analyze data in order to provide richer customer insights. But data clean rooms have a deeper focus on privacy than DMPs or CDPs. 

  • DMPs collect and house relevant first-, second-, and third-party data inputs, generating insights that can inform real-time decision-making and overarching optimization strategies. They can be used by both advertisers and publishers and are usually integrated with demand-side or supply-side platforms.
  • CDPs are like DMPs in that they gather and store data, but CDPs focus exclusively on an advertiser’s or publisher’s first-party data about their own customers. CDPs allow businesses to create a single, holistic view of each customer, which can be used to supercharge personalized marketing, among other use cases.

Data clean room solutions, on the other hand, exist solely to create a safe, anonymized way to share first-party data between several companies. 

What are the barriers to data clean room adoption?

As with any new technology, there are a few challenges marketers face in trying to build or adopt a new clean room, including cost and talent. 

  • Data clean rooms come with a hefty price tag. A quarter of data clean room users spent $200,000 or less on the tech in 2022, according to the IAB and Ipsos, which means smaller brands and publishers are at a disadvantage. 
  • Data clean rooms also require data science know-how—for now. Querying is not yet straightforward, and advertisers often need a small team to use the tech to its full potential. Less than a third of data clean room users are leveraging measurement-related use cases, per November 2022 data from the IAB. 

Looking forward, there are three things that will be essential for data clean room adoption: interoperability, standardization, and data security. Providers will need to come up with ways to ensure clients can easily work with multiple data clean room partners and still get consistent, privacy-safe results.