With growing data privacy concerns, companies are looking for ways to mitigate risks associated with handling sensitive data in a way that’s compliant with evolving regulations. Data clean rooms (DCRs) are answering these concerns by creating a secure private data exchange where brands can combine first-party data with other trusted data sources, while maintaining control of their data. By ensuring that sensitive data is kept secure, data clean rooms help businesses avoid compliance risks, while gaining valuable insights from their customer data.
Data Clean Rooms: Why Now?
In 2020, Gartner estimated that 80 percent of all companies with media budgets of $1 billion or more annually would be using a data clean room. It’s now 2023, and the IAB reports that 64 percent of companies with privacy-preserving technology use DCRs. Most of these companies use DCRs for vital tasks, like privacy protection and control, improving match rates, and data interoperability.
While data clean rooms are not exactly new, technological advances like cloud SaaS are helping companies feel more comfortable setting up and maintaining the technology. Brands are also becoming more digitally mature, with marketing teams that are increasingly tech savvy.
Global and state-level privacy regulations, along with third-party cookie deprecation from providers like Apple and Google are requiring companies to change existing customer data practices. In turn, brands are exploring new ways to safely and securely collect and manage customer data, with a growing emphasis on first-party data strategies, data monetization, and direct brand partnerships.
Data Clean Rooms and Data Protection
Data clean rooms can help companies navigate these partnerships. During a session at MarTech Spring, Ana Milicevic, principal and co-founder, Sparrow Advisors, explained it this way:
Think of a data clean room as a vault or bank safe. Each data provider has complete control over what data is available and how it’s used. The data is anonymized or pseudonymized to remove all personally identifiable information (PII), or replace PII with a pseudonym or code that cannot be traced back to the individual.
Because data clean rooms bring together data from multiple providers, it must be standardized according to agreed-upon rules and data models. Bringing together different data sources enriches a brand’s first-party data, which identifies new ways to activate data in a privacy-compliant way.
The IAB is taking steps to provide clarity around how brands can use data clean rooms to exchange data securely. In February 2023, the organization launched its Data Clean Room Standards Portfolio, which provides guidance and recommended practices around privacy and security for DCR technology, with specifications to define interoperability between data clean rooms.
As data clean rooms mature, we could start seeing them be used to solve attribution and return-on-ad-spend challenges, along with media mix modeling, planning, predictive analytics, and propensity modeling. Data clean rooms could also operationalize advanced analytics, reducing complexity to make measurement easier.
Data Clean Room Challenges
While data clean rooms are emerging as a way to support data privacy and security, several key challenges impact a brand’s ability to do it successfully. According to Milicevic, there are three things companies need to consider when adopting a data clean room for their organization.
Level of Data Maturity
A data clean room requires a high degree of data maturity. Brands that deal with complex data assets and integrations for enrichment and activation would benefit from a data clean room, but many brands don’t have an overall data strategy. Establishing a data clean room would not be easy without one.
Cost of Implementation
Data clean rooms are not turnkey– they require substantial cost and effort to implement and maintain annually. Data clean rooms are not standalone tech, either – they’re a part of a privacy-by-design stack.
When you factor in other technology that supports a data clean room, like a customer data platform (CDP), consent management platform (CMP), data management platform (DMP), and identity systems, the cost and effort to deploy a data clean are significant. However, as technology advances, these costs will go down, Milicevic said.
Staffing and Resources
Finding the right resources is a significant challenge for companies. According to the IAB, 38 percent of businesses say they have problems finding talent that is highly skilled in privacy, including encryption technology, data security, and other privacy technology.
About half of all data clean room users currently have a dedicated team, with 49 percent having six or more employees, and 30 percent having at least eleven. These resources include data architects, data engineers, QA, DevOps, and infrastructure teams.
Interoperability with other data clean rooms is a primary use case for secure data exchange between brands, but remains challenging. The IAB reports that 39 percent of brands have found challenges with interoperability and customization during data clean room implementation. Milicevic believes that the new IAB standards will make it easier for clean rooms to talk to each other using a common language.
Getting Started with a Data Clean Room
It’s not a small decision to set up a data clean room. It requires a sizable budget, a comprehensive data strategy, and the right resources.
According to Milicevic, it’s important to consider how much investment is needed, who will own the project, and how it will fit with existing privacy-preserving vendors. It’s also critical to stay up-to-date with changing regulations to understand how to maintain the technology.
A data clean room ensures that a brand manages and uses its customer data in compliance with data privacy regulations. It also empowers marketing, sales, and support, with the right data to create the best customer experiences.