Retail media networks (RMNs) have grown rapidly, with spending representing a fifth of global advertising in 2024. Now, the rise of commerce media is shifting spend and further blurring lines between advertisers and publishers.
With over 100 RMNs in the US alone, commerce media is expanding across verticals like travel, finance and health care. This intensifies competition and elevates advertiser expectations.
While traditional publishers scramble to adapt, growth for marketers-turned-media companies isn’t guaranteed. Even giants like Walmart Connect must now actively encourage advertisers to spend more. Target Roundel and Amazon Advertising offer scale, but sheer size isn’t a differentiator anymore.
What can help retail and commerce media networks stand out? Data readiness, connectivity and access that enables standardization, transparency and results.
Boom times evolve
Retail media involves advertising within a retailer’s owned properties, sites and apps, using first-party customer data. It’s today’s version of premium shelf space, putting ads close to the point of purchase.
Commerce media expands beyond owned platforms, connecting audiences across networks and channels. It uses transactional data from various sectors, enabling companies outside retail, like banks, travel and delivery services, to monetize their first-party data across the open web.
But as the space has matured, advertiser expectations have grown.
Emarketer recently highlighted challenges beyond the “boom” period; chiefly, the lack of data standardization. Advertisers are still investing across multiple RMNs but struggle to compare performance due to inconsistent reporting.
Consolidating a unified customer view is nearly impossible when audience IDs vary across 10+ networks. As spending spreads, tracking performance becomes a major challenge.
For media networks, creating a true “secret sauce” is now essential.
Unfortunately, many RMNs and CMNs fall victim to the “checkbox mentality” – adopting tools without ensuring their data is prepared. They invest in platforms and ID solutions, yet overlook the foundation: organized, accessible, interoperable data.
Data readiness
Data readiness means having clean, structured, accessible information for analysis, decision-making and activation. It begins with strong internal data integration.
Retailers and other media networks must connect their internal data sources to identify and monetize audiences. This requires data that’s normalized, privacy-compliant and ready for activation.
Here are some best practices for retail data readiness:
- Connecting internal sources for a full audience view: Many retailers and brands have customer, loyalty and transactional data scattered across disconnected systems. Integrating these sources into a unified data environment enables a complete view of the customer journey and more accurate audience profiling.
A QSR brand that unifies mobile app orders, loyalty program activity and third-party delivery data can identify high-frequency lunch buyers who haven’t redeemed loyalty points in 30 days, then trigger a personalized push notification or email to increase incremental sales and boost retention. - Building tech stacks tailored to your business goals: There’s no one-size-fits-all solution. Your marketing and ad tech stacks should reflect your specific business and marketing objectives to achieve the desired outcomes.
A travel company with limited owned inventory might prioritize investment in clean rooms and data onboarding tools to activate audiences across external publisher networks, ensuring scale without direct media real estate. - Establishing data governance and standards: Data readiness requires discipline. Governance ensures information is accurate, consistent and privacy-compliant, building trust with consumers and enabling reliable activation across teams and systems.
A retail brand that enforces strict consent management and standardizes key customer data fields, like opt-in status, location or age group, can avoid noncompliant campaigns, reduce legal risk and maintain clean, consistent reporting across its media partners. - Orchestrating data across ecosystem platforms: To support real-time activation and measurement, data must flow efficiently between DSPs, CDPs, CRM systems and analytics tools.
A bank launching a commerce media offering can integrate transaction data from its CRM with its CDP and programmatic platforms to deliver personalized credit card or loan offers based on recent spending behavior, enabling dynamic creative optimization and more precise cross-channel attribution.
Identity resolution
Identity resolution is one of the biggest challenges in working across platforms. When the same customer appears as different identities across platforms, it leads to duplicate records, fragmented insights and a subpar customer experience.
Data fragmentation not only dilutes personalization but also results in wasted ad spend. Even the most advanced AI can’t deliver results without consistent, complete data.
Mapping customer profiles to a single, unified ID is essential for building a complete view of the customer. Resolving these duplicates improves campaign performance and ensures more efficient media spending.
Solving the “apples to oranges” reporting issue makes it easier to integrate across networks, expanding the value proposition beyond owned properties. Such cross-platform insight is vital as RMNs evolve into CMNs.
Media networks must invest in data readiness to build scalable, future-proof systems. New entrants like retailers, banks and travel firms have tremendous potential for incremental revenue. But if they get this wrong, they could potentially lose their shirts.
So don’t dive in just because others are or because retail and commerce media look like easy money. There are no shortcuts. Build your data deliberately to create real value for advertisers, partners and consumers.
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
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