Latest / The CMO Podcast with Fexingo: Marketing Leadership, Budgets, and Executive Strategy / How CMOs Are Using Retail Media Networks for First-Party Data
Transcript
- Lucas: Retail media networks are now the fastest-growing ad channel in the world. In 2026, spending on them is expected to hit sixty billion dollars, up from about forty billion just two years ago. Luna: That's a huge leap. What's driving that growth? Lucas: The core driver is access to purchase data. When a brand advertises on Walmart Connect or Amazon Ads, they get actual transaction data showing whether the ad led to a sale. That's the holy grail for CMOs who have lost third-party cookies. Luna: So it's not just about the eyeballs—it's about closing the loop on attribution. Lucas: Exactly. In the old world, a cereal brand might run a Facebook campaign targeting 'breakfast lovers' and then rely on panel data to guess if it worked. Now, on Walmart Connect, they can target 'people who bought a competitor's cereal in the last thirty days' and then measure the actual lift in same-week purchases. Luna: That level of precision must be forcing CMOs to rethink their media mix. Lucas: It is. A recent study from the Association of National Advertisers found that nearly sixty percent of CPG brands now allocate at least fifteen percent of their digital budget to retail media. And some are pushing past thirty percent. Luna: But isn't that risky? You're putting more eggs in one retailer's basket. Lucas: That's the tension. On one hand, the data is incredibly actionable. On the other, you're giving a retailer like Amazon or Walmart even more leverage over your brand. They control the platform, the pricing, and the rules of measurement. Luna: And I imagine the cost is going up as more advertisers pile in. Lucas: Absolutely. CPMs on retail media networks have risen roughly thirty percent year-over-year on average. So the efficiency gains from better targeting are being partially eaten by higher prices. Luna: So how are smart CMOs managing that trade-off? Lucas: They're using incrementality testing. They run controlled experiments where a test group sees the ad and a holdout group doesn't—then compare purchase rates using the retailer's own transaction data. That tells you the true incremental sales, not just the baseline. Luna: That sounds like the same principle as a randomized control trial in pharma. Lucas: Exactly. And the best CMOs are also building clean room partnerships. They're working with companies like InfoSum or Snowflake to match their own customer data with the retailer's data in a privacy-compliant way. Luna: So they can see the full funnel—from awareness to purchase—without giving away all their customer data. Lucas: Right. It's a negotiation. The retailer wants data back to improve its own algorithms. The brand wants proof the ad spend works. The clean room lets both sides get what they need without exposing raw customer identities. Luna: Are there any standout examples of a brand executing this well? Lucas: I like the case of a mid-size beverage company—let's call it Sparkling Co. They were spending about two million dollars a quarter on Amazon Ads with very little attribution. So they ran a six-month incrementality test using Amazon's own Marketing Cloud. Luna: What did they find? Lucas: They found that forty percent of their sales attributed to Amazon would have happened anyway—people who would have bought the product regardless. That meant their actual incremental return was half of what they thought. Luna: Ouch. So they were basically overpaying for sales that were already in the bag. Lucas: Exactly. They reallocated that wasted spend into upper-funnel brand campaigns on connected TV, which actually lifted overall category demand. Their total ROI went up about twenty percent after the shift. Luna: So the lesson isn't to abandon retail media, but to measure it more rigorously. Lucas: Right. And the data doesn't end with ads. Some CMOs are using retail purchase data to inform product innovation. If a retailer's data shows that a certain flavor or size is trending in a region, you can adjust your R&D pipeline accordingly. Luna: That's a pretty powerful feedback loop—from shelf to lab. Lucas: It is. But it also raises questions about data exclusivity. If only Walmart has that data, you're building your strategy around one retailer's view of the world. Luna: And that could lead to groupthink, or overfitting to a single channel. Lucas: Exactly. That's why the savviest CMOs are diversifying their retail media partners. They might work with Walmart Connect for mass, Instacart for quick-commerce, and Amazon for general e-commerce. Each gives a different slice of the picture. Luna: And they're combining that with their own first-party data from loyalty programs or email lists. Lucas: Yes. The ultimate goal is a unified view that doesn't rely entirely on any one retailer. That's the next frontier for marketing analytics. Luna: Speaking of keeping options open, it's interesting that we can have this conversation without any ads interrupting. That's a deliberate choice on our end. Lucas: It is. We don't run sponsorships or ad reads because we want the content to be focused on what's useful to you, not on selling you something. If you find value in these episodes, supporting us on buy me a coffee dot com slash fexingo helps keep it that way. Luna: And it truly goes toward production time—researching these cases and making sure we're not just repeating headlines. Lucas: So back to retail media—what do you think is the biggest risk CMOs face if they lean in too hard? Luna: I worry about losing the ability to build brand equity outside of a retailer's ecosystem. If you optimize every dollar for a conversion on Walmart, you might neglect the emotional connection that makes someone choose your brand over the store brand. Lucas: That's a valid concern. The data is seductive because it's measurable, but brand building is inherently harder to measure. The CMOs who succeed will be the ones who treat retail media as one tool in a bigger toolkit, not the whole toolbox.