Last updated: What is a data clean room: Definition, benefits, use cases

What is a data clean room: Definition, benefits, use cases


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The rise of the privacy-first web is forcing marketers to find new ways to engage and attract customers. With data privacy requirements increasing and third-party tracking cookies going away, brands can no longer rely on traditional digital marketing methods.

As companies face mounting restrictions and growing consumer concern about their personal data, they also need to deliver the personalized, relevant engagement that gets results.

In order to balance these competing demands, some brands are turning to a data clean room, a software environment designed for secure data sharing. DCRs are getting a lot of attention as marketers transition to a new era.

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What is a data clean room? Defining DCR

A data clean room is a secure digital environment where multiple parties can share user data and collaborate while maintaining strict privacy safeguards.

It allows different parties such as brands, media publishers, and advertisers to share first-party and other customer data in a protected, controlled way. They can compare data and analyze it for aggregated results, but can’t see raw data. Personally identifiable data is stripped out or hidden.

A data clean room allows brands to collaborate and gather deeper insight into customers from the collective data sets. Anonymized data is matched and enriched, providing companies with information they can use to launch marketing campaigns for targeted audiences and measure their performance.

These environments help companies comply with data privacy regulations such as GDPR and CCPA. They also help marketers overcome Apple’s heightened IOS privacy and the loss of third-party cookies. Google expects to complete its phase-out of third-party cookies in the second half of this year.

A survey by the Interactive Advertising Bureau and Ipsos found that two-thirds of companies using privacy-preserving technologies in 2022 used DCRs, with another 21% considering the technology.

According to a Deloitte Digital survey of 500 global executives across 11 industries, one out of three use data clean rooms extensively. Nine out of ten expected to ramp up their use of the technology.

How does a DCR work?

While data clean room technology varies depending on the provider, it generally has a basic operational framework with four steps:

  1. Data loading – Companies load their first-party data into the clean room
  2. Security and privacy controls — Safeguards such as encryption and anonymization are applied
  3. Connection – Data sets are matched and sorted into cohorts 
  4. Application – Companies participating in the data clean room can use the data for marketing research and campaigns 

The end result is a richer set of data for DCR participants, which enables them to conduct deeper audience research to create targeted marketing and advertising. They can optimize their strategies, evaluate their marketing performance, and run more efficiently and effectively.

Throughout the DCR operation, contractual agreements enforce controls on how data is loaded, used, and applied, with data privacy the top priority.

Benefits of data clean rooms

DCR technology is gaining traction as companies look for ways to modernize their marketing for a privacy-first digital world.

The IAB survey found that data privacy protection is the top use case for companies using DCR technology, especially when they’re sharing data with external parties.

The privacy-focused technology offers a number of benefits, including:

  1. Collaborative data sets can be used for targeting without third-party cookies, which are being deprecated
  2. The ability to gain deeper customer insights. In-depth analytics were the top driver for DCR strategies, according to a survey of North American marketers by the CMO Council
  3. Improved ability to measure campaign performance and effectiveness (cited by 5% of CMO survey respondents)
  4. Maintain security and privacy compliance as requirements continue to evolve
  5. Discover new market opportunities

Data clean room contain detailed advertising impression data, but don’t store personally identifiable information, enabling marketers to build custom audiences without the risk of privacy violations, according to a Gartner report.

“Data clean rooms serve as a crack in the wall that marketers can peer through,” Gartner analysts said.

Drawbacks to watch out for

While data clean rooms offer a lot of benefits, they also pose plenty of challenges. Namely, they aren’t turnkey; they require a big investment of money, time, and talent, which puts smaller companies without extensive resources at a disadvantage, according to the IAB report.

The survey found that nearly two-thirds of respondents spent at least $250,000 on their DCR initiatives in 2022; a quarter spent up to a half million. Nearly half of DCR users count six or more workers assigned to the technology and 30% have at least 11 dedicated to it.

Set-up is complex, involving governance settings, data onboarding procedures, and establishing connections with multiple partners. Companies reported that it took months to get the tech running with some saying it took a couple years, IAB said.

The average amount spent on DCR tech by a company in 2022 was $879,000, according to the Deloitte Digital survey.

Other challenges include:

  • Interoperability with existing technology
  • Privacy regulations continue to evolve; controls must be constantly monitored for compliance
  • Collaboration and agreement with partners on DCR tech and rules

Providers and types of DCR solutions

As data clean room technology continues to evolve, more players are entering the space, from digital giants and media companies to identity and data platform providers and pure-play specialists. Many vendors in this space team up with partners to extend their solutions.

Enterprises have three main types of DCR to choose from:

  1. Data clean rooms from walled gardens such as Google and Amazon. Google’s Ads Data Hub joins a user’s first-party data with its event-level ad campaign data. Amazon Marketing Cloud allows users to create reports over event-level Amazon Ads inputs  and purchase events from Amazon stores. Media companies like Disney also fall into this category; Disney’s Clean Room Solution uses the company’s proprietary Audience Graph.
  2. DCRs operated by data warehouse operators such as Databricks. Other examples include Google, which last year released BigQuery data clean rooms, and Snowflake. These solutions often incorporate third-party DCR tech and are designed to help customers build their own DCRs.
  3. DCR technology offered by pure-play providers, including InfoSum, which launched its decentralized data collaboration platform in 2019, and LiveRamp and Habu, which are both Google Cloud partners.

Data clean room use cases

Just as there are many different types of DCRs, there are a lot of ways enterprises can use them to improve their marketing while protecting consumer privacy.

Here are four use cases:

  • Consumer products company and retailer: While CPG brands may have some marketing insight into demographics and consumer preferences, retailers selling their products are the ones with most of the valuable first-party, transactional data. A DCR enables them to combine their data securely and gain additional insights, which they can use for more segmentation and targeting.
  • Financial institutions, payment companies, and insurance firms: Data sharing and collaboration through a data clean room can help them improve fraud detection, credit scoring, and underwriting.
  • Media company and advertiser: DCR collaboration provides these companies with deeper customer insight to create personalized campaigns and measure performance. For example, a media company’s impression data combined with an advertiser’s conversion data helps gauge performance.
  • Healthcare providers and pharmaceutical researchers: Through a DCR, hospitals and researchers can share data while maintaining HIPAA compliance to monitor and develop treatments to improve patient outcomes.


Of course, there are other types of solutions that enterprises can use for targeted advertising and measurement in the cookie-less future, including:

  • Data management platforms (DMPs) gather, store, and organize data from multiple sources for the purposes of developing ads and marketing campaigns. DMP technology, which has been around for a number of years, generally relied heavily on third-party data to build profiles for anonymous users, rather than known customers.
  • Customer data platforms (CDPs) collects, organizes, and centralizes a company’s customer data from various systems and sources, which they can use to create a single view of the customer and build comprehensive customer profiles that focus on first-party data. Unified customer profiles enable personalized CX and help companies abide by customer privacy preferences for regulatory compliance.
  • Identity solutions such as customer identity and access management, which provide customers with a unified login experience and help companies build profiles and securely manage customer identities.

These technologies can be used together to build a comprehensive database for painting a better picture of customers and prospects in a privacy-safe manner.

In the IAB survey 84% of DCR users also use CDPs, 81% use DMPs, and half use identity solutions.

Future of data clean rooms

DCRs are becoming an integral part of marketing and advertising strategies for major brands and are creating opportunities for new business models, Deloitte Digital analysts said in their report.

Gartner recommends that companies that spend more than $1 billion in advertising per year should invest in DCR technology now. Those that spend less than $100 million on ads should look for ways to use data clean rooms as self-service point, the firm advises.

Despite the cost and other challenges, the market for data clean rooms will grow and evolve– along with other privacy technologies — as marketers find ways to address constantly changing privacy regulations, market trends, and customer needs.

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