How retail media networks use data clean rooms to win brand partnerships and prove ROI

Global retail media ad spend is on track to reach nearly $197 billion in 2026. That growth is real, but so is the competitive pressure that comes with it. As the number of retail media networks multiplies, brands are becoming more selective about where they commit budget. 

The deciding factor is increasingly measurement: Can your network show, credibly and repeatedly, that your data drives results for the brands that buy it? Yet fewer than half of retail media networks currently offer data clean room capabilities, according to Mars United Commerce's Q2 2025 State of Retail Media report. That gap represents a meaningful opportunity for networks willing to invest in the infrastructure that closes it.

This guide is for retailers building or scaling a retail media network (RMN): how to structure brand data partnerships, why clean rooms have become the infrastructure layer that makes those partnerships work, and what the full potential looks like when your first-party data activates not just on your own channels but across a connected media ecosystem. 

If you're newer to retail media fundamentals, start with our retail media overview first.

The brand partnership problem retailers keep running into

For brands, retail media offers something most channels can't: targeting built on real purchase behavior, and the ability to measure directly against sales. The combination of high-intent audiences and closed-loop attribution is why brand budgets have been shifting toward RMNs. What keeps those budgets from growing further is the inability to prove the collaboration is working consistently across partners 

The blockers are structural:

• No standardized measurement. Every RMN uses its own attribution methodology. Brands managing campaigns across multiple retail partners can't meaningfully compare performance, which makes it hard to justify increasing spend with any individual network.
• No closed-loop visibility without raw data exchange. Connecting ad exposure to actual sales requires combining retailer transaction data with brand campaign data. Without a secure way to do that, the measurement gap stays open.
• No scalable path to premium offsite activation. Most RMNs can push audiences to Google, Meta, and open web inventory through standard DSP integrations. The gap is in activating against premium, brand-safe environments (particularly CTV) where direct first-party data uploads aren't accepted and clean room-based identity resolution is what gets you in the door. That's also where the targeting quality and measurement credibility brands are willing to pay a premium for actually lives. 

Retailers with genuinely valuable first-party data are leaving revenue on the table because they can't give brand partners the proof they need. A data clean room addresses this directly, serving as the collaboration infrastructure that makes meaningful measurement possible.

What a data clean room enables: four retail media use cases

A data clean room is a secure environment where multiple parties can run analysis on combined datasets without either side ever seeing the other's raw data. For a deeper primer on the mechanics, see what is a data clean room. For the purposes of this article, we focus on what that enables in a retail media context: the four use cases that matter most for monetizing your first-party data at scale.

1. Consumer insights

Brands bring CRM or campaign data into the clean room alongside your transaction data. One of the most common starting points is DTC overlap analysis: a brand wants to understand whether their direct customers are also shopping with you, or whether your audience represents a genuinely incremental opportunity. That distinction between cannibalisation and complementarity shapes how a brand thinks about the partnership and where they want to invest. 

From there, the analysis can extend further: which of the brand's customer segments are underperforming with your shoppers, where there are net-new audiences worth targeting, and where the most valuable collaboration opportunities lie. Neither side shares raw data; the clean room runs the query and returns aggregated insights both parties can act on. 

For more on how this dynamic works, see our article on how retailers can use customer data to add value to brand partnerships or check out the platform demo for this use case.

2. Offsite activation

Once audience segments are built inside the clean room, they can be activated beyond your owned channels: across premium publishers, connected TV, and programmatic inventory, via lookalike modeling or direct audience matching. The activation happens through privacy-safe identity resolution that passes only encrypted audience signals to media partners.

This is what transforms your RMN from a walled-garden play into a full media business. For a deeper look at the offsite opportunity, see our guide on offsite retail media.

3. Sales lift measurement

Closed-loop attribution (connecting a brand's campaign impressions to actual purchase behavior) is retail media's biggest proof point. The clean room makes this possible without either party exposing individual-level data: campaign exposure records are matched against transaction records inside the secure environment, and the result is an aggregated lift report the brand can take back to their CFO.

Brands that can see a clear line from ad spend to incremental sales will keep coming back and keep growing their investment. Sales lift measurement is the output that turns a one-time campaign into a recurring budget allocation. See how sales lift works in Decentriq’s data clean rooms.

4. Brand first-party data onboarding

In more advanced collaborations, brands upload their own CRM or first-party data alongside yours. This enables richer custom use cases: exclusion targeting (don't show acquisition ads to existing customers), high-value customer lookalikes built from the brand's own audience, or joint segmentation models that neither party could build alone. See our article on first-party data activation for more on how this works in practice.

Closing the offline measurement gap

Many clean room conversations assume a digital-native retailer, one where the majority of transactions happen online and campaign exposure data is relatively straightforward to track. For most retailers, the reality is more complex. A significant share of sales happen in-store, and that data has historically been difficult or even impossible to connect to digital campaign outcomes.

This is one of the most underdiscussed limitations in retail media measurement, and one of the highest-value problems a clean room can solve.

Swiss wholesaler TopCC worked with agency partner Converto to use in-store purchase data as a targeting signal for digital campaigns, feeding real transaction behavior into audience building through Decentriq's clean room. The result was a tenfold increase in attributed conversions, achieved without any exchange of raw data between the parties. Offline transactions that would previously have been invisible in digital attribution became part of a measurable closed loop.

For retailers with substantial brick-and-mortar operations, this changes the measurement conversation with brand partners entirely. Rather than asking brands to accept an attribution model that ignores most of where your shoppers actually buy, you can offer them something far more compelling: proof that spans the full purchase journey.

Beyond your own inventory: activating across a media ecosystem

The full value of retail media data is rarely realized on owned channels alone. Your shoppers are watching TV, scrolling social media, reading news. The question is whether you have the infrastructure to reach them there using your data, and whether brands can trust that the targeting is reliable and the results are measurable.

OBI's retail media arm, OBI First Media Group, demonstrated exactly this. Working with Ad Alliance, whose publisher network includes premium German-language TV and digital inventory, OBI combined its CRM and retail transaction data with Ad Alliance's media reach inside a Decentriq data clean room. Through overlap analysis and AI-powered lookalike modeling, they identified high-performing audience segments for GARDENA's robotic lawnmower campaign and activated those segments across connected TV, in-stream video, and display, with no third-party identifiers and full GDPR compliance.

The results for an already well-established brand:

• +8% uplift in ad recall
• +3% uplift in purchase intent

Following this campaign, OBI established data clean rooms as a fixed component of future data-driven, cross-channel advertising strategies. A proof of concept becomes standard operating procedure when the results are this clear.

From campaign to platform: building a persistent audience infrastructure

The OBI example shows what's possible when retailer data activates across a premium media ecosystem. But running individual clean room collaborations, each set up from scratch with each brand partner, doesn't scale. The retailers building the most durable media businesses are moving from project-based collaboration to persistent audience infrastructure.

Decentriq's Collaborative Audience Platform is built for exactly this. Rather than treating each brand collaboration as a discrete integration, it gives retailers a unified environment to collect, segment, enrich, and activate audiences across channels — combining the capabilities of a DMP, CDP, and clean room in a single platform. Audience segments built from your transaction and loyalty data can be activated across onsite inventory, premium publishers, CTV, and walled gardens like Meta and Google simultaneously, with closed-loop measurement running in the background. Brand partners can access insights and activate campaigns through a governed environment without ever touching your raw data.

The three monetization paths this opens up (consumer insights for brand partners, boosted media targeting across channels, and clean-room-powered measurement) can all run in parallel rather than sequentially. That's what turns ad hoc brand partnerships into a scalable, repeatable revenue stream. 

What to look for in a retail media collaboration platform

Not all platforms are built for the retail media use case. And if your evaluation started with a retail media clean room platform, it's worth thinking bigger. These are the capabilities that determine whether the investment pays off:

• Cross-inventory activation in one platform. The ability to activate your data across walled gardens, premium publishers, and CTV from a single environment matters. Fragmented activation across separate integrations creates fragmented reporting, which undermines the closed-loop story brands need.
• Unified audience infrastructure. Look for a platform that combines segmentation, identity resolution, and enrichment in one place, rather than a DMP, a CDP, and a separate clean room bolted together. The ability to build segments from transaction, loyalty, and behavioral data and activate them without moving raw data between systems is what makes the whole stack work at scale.
• Ease of brand onboarding. Every brand partner you work with will need to go through a setup process. If that requires weeks of custom technical work, you'll hit a scalability ceiling fast. Look for platforms with standardized onboarding flows and self-serve collaboration templates.
• Access to media exposure data across walled gardens . Most platforms can ingest your offline transaction data; that's table stakes. What's harder, and more valuable, is closing the loop from the other direction: getting campaign exposure data back from walled gardens and CTV platforms into a shared environment where it can be matched against your purchase data. Decentriq's integrations make this possible today across an expanding set of media partners. That's what turns your first-party data from a targeting input into a full measurement asset.  
• Privacy-safe data collaboration. The platform should be architecturally designed so that neither party can ever access the other's raw data — for compliance, but also for brand partner confidence. That assurance is what makes brands willing to bring their own CRM data into the collaboration.
• A connected media ecosystem. The platform's network of media partners determines what you can actually activate against. A platform that only connects to one or two DSPs limits your offsite opportunity significantly.

Decentriq's retail data collaboration platform is built specifically for this set of requirements, including a partner network spanning premium publishers, CTV platforms, and walled gardens across Europe and beyond.

The retailers building this infrastructure now are the ones brands keep coming back to

Retail media's growth story is well established. The next chapter is about which networks win the lion's share of brand budgets, and that comes down to measurement credibility, partnership depth, and the ability to activate beyond owned inventory.

For this reason, building this infrastructure now is still a differentiator. The retailers that move first will have a compounding advantage: better measurement leads to stronger brand relationships, which leads to more data flowing through the clean room, which leads to better targeting and attribution. See how Decentriq enables this for retailers →

Ready to build? Download our guide to building a retail media network, or request a demo to see Decentriq's clean room in action.