The Role of Data Clean Rooms and Privacy Tech in Retail Media and Personalization

In today’s rapidly evolving retail landscape, the ability to deliver personalized experiences and measure media effectiveness is more critical—and more complex—than ever before. As retailers and brands face mounting regulatory pressures, the deprecation of third-party cookies, and rising consumer expectations for privacy, the industry is turning to data clean rooms and privacy-enhancing technologies to unlock new value from data collaboration while safeguarding consumer trust.

Understanding Signal Loss and the Shift to First-Party Data

The digital advertising ecosystem is undergoing a seismic shift. The deprecation of third-party cookies by major browsers, coupled with privacy regulations like GDPR and CCPA, has led to what industry leaders now call “signal loss.” This loss of traditional tracking signals makes it increasingly difficult for retailers and brands to recognize customers across channels, activate audiences, and measure the true impact of their media investments.

As a result, the focus has shifted to first-party data—information that retailers collect directly from their customers through owned channels such as e-commerce sites, loyalty programs, and mobile apps. First-party data is now the foundation for building rich customer profiles, enabling personalized experiences, and driving more effective marketing. However, leveraging this data at scale, especially in collaboration with partners, requires new approaches to privacy and data governance.

What Are Data Clean Rooms?

Data clean rooms are secure, privacy-protecting environments that allow retailers, brands, and their partners to collaborate on data without exposing raw, personally identifiable information. In a clean room, each party can contribute their own first-party data, and advanced privacy techniques—such as encryption, differential privacy, and permission-based queries—ensure that only aggregated, anonymized insights are shared.

This approach enables a range of high-value use cases:

The Rise of Privacy Tech in Retail Media

Retail media networks (RMNs) have become a cornerstone of modern retail strategy, offering brands the ability to reach shoppers at the point of purchase with highly targeted advertising. However, the effectiveness of these networks depends on the ability to activate and measure audiences in a privacy-compliant way.

Privacy-enhancing technologies (PETs) such as data clean rooms, advanced consent management, and automated policy enforcement are now essential components of the retail media tech stack. These tools enable:

Unlocking New Insights While Respecting Privacy

The true power of clean rooms and privacy tech lies in their ability to bridge the gap between data utility and privacy. For example, a retailer and a CPG brand can use a clean room to analyze the impact of a joint campaign—identifying which customer segments responded best, measuring incremental sales, and refining future targeting strategies. All of this is done without exposing individual-level data, ensuring that consumer privacy is never compromised.

Moreover, clean rooms support advanced measurement techniques such as incrementality testing and A/B experiments, allowing retailers and brands to understand the true lift generated by their media investments. This level of insight is increasingly critical as marketing budgets come under greater scrutiny and the need for demonstrable ROI grows.

Publicis Sapient’s Leadership and Partnerships

At Publicis Sapient, we recognize that the convergence of retail media, data privacy, and technology is reshaping the industry. Our teams have been at the forefront of helping retailers and brands navigate this new landscape—partnering with leading technology providers like AWS and Salesforce to deliver secure, scalable clean room solutions.

We have developed accelerators and best practices that enable:

Our experience shows that successful adoption of clean rooms and privacy tech requires not just the right tools, but also the right organizational mindset—one that prioritizes transparency, trust, and a relentless focus on customer value.

Guidance for Retailers Navigating the Privacy Landscape

For retailers looking to harness the power of data clean rooms and privacy tech, we recommend the following steps:

  1. Prioritize First-Party Data: Invest in strategies to collect, unify, and enrich your own customer data. This is the foundation for all future personalization and measurement efforts.
  2. Evaluate Clean Room Solutions: Assess your current data collaboration needs and explore clean room platforms that align with your privacy, security, and business objectives.
  3. Build Cross-Functional Teams: Bring together stakeholders from marketing, IT, legal, and analytics to ensure alignment on privacy policies, data governance, and measurement goals.
  4. Embrace a Test-and-Learn Culture: Use clean rooms to run controlled experiments, measure incrementality, and continuously refine your approach to personalization and media activation.
  5. Stay Ahead of Regulation: Monitor evolving privacy laws and invest in automated compliance tools to ensure your data practices remain future-proof.

The Future: Personalization at Scale, Powered by Privacy

As the retail industry continues to evolve, the ability to deliver personalized, measurable experiences—while respecting consumer privacy—will be a key differentiator. Data clean rooms and privacy-enhancing technologies are not just technical solutions; they are strategic enablers that empower retailers and brands to build deeper, more trusted relationships with their customers.

At Publicis Sapient, we are committed to helping our clients unlock the full potential of their data in a privacy-first world. By combining deep industry expertise, leading technology partnerships, and a relentless focus on customer outcomes, we help retailers turn privacy challenges into opportunities for growth and innovation.

Ready to take the next step? Connect with our team to learn how Publicis Sapient can help you design and implement a privacy-first data strategy that drives results in retail media and personalization.