Retail Media Networks (RMNs) are having their moment. Over the past few years, they have rapidly evolved from an emerging advertising channel into one of the most powerful forces in digital marketing. With brands pouring billions into RMNs, retailers are capitalizing on their most valuable asset—first-party shopper data—to create a highly targeted and high-intent advertising environment.
But here’s the challenge: first-party data alone isn’t enough to maximize long-term RMN success.
As more retailers launch and scale their own commerce and retail media networks, competition for ad dollars is intensifying. Advertisers now expect more than just basic transaction data and contextual targeting—they want deeper customer insights, richer audience segmentation, and, most importantly, measurable results across an increasingly complex omnichannel landscape.
The retailers and brands that will win in this space are the ones that leverage third-party data to take their RMNs to the next level. Download our complete RMN and third-party data eBook here or keep reading to learn how!
First-Party Data is Powerful—But Not Perfect
First-party data is a fantastic foundation for RMNs. It provides high-intent signals based on real purchase behavior, which makes retail media inherently more valuable than traditional digital advertising. But first-party data is also inherently limited.
Retailers can only collect what they observe directly—transactions, loyalty program interactions, and site activity. This creates blind spots, such as:
- Limited customer profiles—Retailers don’t always know who their customers are beyond basic transaction data.
- Lack of behavioral and intent insights—Retailers only see what happens within their own ecosystem, missing broader shopping behaviors that influence purchasing decisions.
- No visibility into cross-retailer interactions—Brands working across multiple RMNs struggle to connect the dots between different platforms.
This is where high-quality, predictive third-party data becomes the game-changer.
How Third-Party Data is Fueling the Next Era of Retail Media
To sustain their momentum and differentiate in a crowded space, RMNs need a broader, richer dataset—one that goes beyond their own walls and provides a more complete picture of their audiences. Third-party data can help do exactly that by providing five key advantages that are redefining the retail media landscape:
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Filling Data Gaps to Create a 360° Customer View
RMNs give brands a strong view of customer behavior inside a retailer’s ecosystem. But what about their activity before and after they visit that retailer? What influences their purchasing decisions?
Third-party data enriches first-party insights by layering in demographics, interests, lifestyle attributes, and predictive shopping behaviors.
🚀 Example: A retailer’s first-party data might show that a customer buys protein powder every two weeks. But predictive third-party data can reveal:
- Whether they’re a dedicated gym-goer or a casual dieter.
- If they also buy vitamins, sports apparel, or organic foods.
- What channels they engage with—social media, podcasts, traditional email, or CTV.
Armed with this knowledge, brands and retailers can personalize ads more effectively, ensuring higher relevance and better performance.
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Precision Targeting & Smarter Audience Modeling
The next generation of RMNs will move beyond basic transaction-based segmentation to predictive and behavioral audience modeling.
Third-party data powers predictive models, helping brands build more sophisticated audience groups, such as:
- Likely first-time buyers who haven’t purchased from a retailer before but exhibit similar behaviors to loyal shoppers.
- High-value repeat customers based on external spending patterns.
- Churn risk audiences—shoppers who have slowed their purchases but engage in related categories elsewhere.
💡 Why this matters: Instead of just reacting to past purchases, brands can anticipate consumer needs before they even start shopping—a massive competitive advantage.
- Solving RMN Measurement Gaps with Unified Data
One of the biggest pain points in retail media today is measurement and attribution.
With many brands investing across multiple RMNs, it’s increasingly difficult to track which campaigns actually drive incremental sales—and to connect engagement across different retailers.
How third-party data helps:
- Identity resolution: Ties together consumer activity across multiple touchpoints using unique identifiers.
- Attribution modeling: Measures how different channels contribute to conversions, not just the final click.
- Offline-to-online connections: Tracks how digital RMN campaigns influence in-store purchases.
📊 The result? Brands get a clearer, more unified picture of what’s working and what’s not—allowing them to optimize spend and scale their most effective campaigns.
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Activating Data Across Channels to Power Omni-Channel Campaigns
Having data is one thing. Activating it effectively across marketing channels is another.
One of the biggest challenges in RMNs today is ensuring that customer insights translate into action across multiple advertising touchpoints—search, social, video, in-store promotions, and more.
Third-party data enables omnichannel activation, helping brands:
- Match first-party RMN data with other digital identifiers to extend audience reach.
- Deliver more consistent messaging across multiple retailers by unifying data sources.
- Refine campaigns based on cross-channel behavioral trends.
🔥 Example: A beauty brand runs a campaign targeting frequent skincare buyers at a major retailer. Third-party data helps extend that campaign across relevant social channels and display ads, ensuring customers see relevant offers beyond just the retailer’s site.
Without third-party data, these cross-channel opportunities can be difficult to identify.
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Turning Retail Data Into a Revenue-Generating Asset
RMNs are evolving beyond just ad placement platforms—they are becoming full-scale data monetization engines.
By combining first-party retail data with high-quality third-party insights, RMNs can create entirely new data products that brands are willing to pay a premium for.
💰 Example: A grocery retailer enriches its first-party shopper data with third-party demographic and interest data to create custom audience segments for CPG brands. These brands can then purchase access to these exclusive segments, driving additional revenue for the retailer.
This is already happening with Amazon, Walmart, and Kroger, but as more retailers invest in RMNs, data monetization will be the next battleground.
The Future of RMNs is Data-Driven—And the Brands That Get It Right Will Win
Retail Media Networks have already changed the game for digital advertising. But as they mature, the ones that truly differentiate will be those that embrace the power of external data to enhance their offerings.
By integrating third-party data, RMNs can:
✅ Deliver richer audience insights and more personalized targeting
✅ Enable predictive modeling for better engagement
✅ Solve measurement & attribution challenges
✅ Activate data across multiple channels for full-funnel marketing
✅ Monetize data as a valuable new revenue stream
As the retail media space continues to evolve, the smartest brands and retailers won’t just rely on what they know about their customers today—they’ll use data to anticipate where they’re going next.
🚀 Want to learn more about how third-party data is transforming RMNs?
📥 Download our eBook by clicking here to explore the five ways external data is reshaping retail media success.