This article was based on the interview with Jeff Baskin, Chief Revenue Officer at Eagle Eye by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
For years, the promise of retail media networks (RMNs) has been shimmering on the horizon—a high-margin revenue stream for retailers and a direct line to the point of purchase for CPG brands. Yet, for many, the reality has felt less like a strategic revolution and more like a digital version of the in-store circular. The focus has often remained on top-line metrics and impressions, treating the RMN as just another advertising channel to be managed, measured, and ultimately, siloed from the core business. This approach, while generating revenue, leaves an immense amount of value on the table. In today’s economic climate, where every basis point of margin is scrutinized, simply driving sales volume is no longer enough. The real question is not whether a sale was made, but whether that sale was incremental, profitable, and contributed to a stronger long-term customer relationship.
This is where the conversation fundamentally shifts, moving beyond the simple mechanics of advertising and into the realm of strategic, data-driven customer engagement. The key to unlocking this potential lies in a force that is reshaping every corner of our industry: artificial intelligence. As Jeff Baskin, Chief Revenue Officer at Eagle Eye, articulates, the most advanced retailers are no longer just selling ad space; they are building intelligent ecosystems. By integrating their richest asset—first-party loyalty data—with the power of AI, they are moving from broad-stroke segmentation to true one-to-one personalization at a scale previously thought impossible. This evolution is turning retail media from a simple revenue generator into a powerful engine for profitability, customer loyalty, and sustainable growth.
Beyond the Digital Endcap: Personalization as the New Standard
The initial wave of retail media was a straightforward digitization of traditional trade marketing. A sponsored product listing on a website is, in essence, a digital endcap. While effective to a degree, this approach fails to meet the modern consumer on their own terms. Shoppers conditioned by the hyper-personalized feeds of Netflix and Instagram now carry a subconscious expectation of relevance in every digital interaction. A generic offer not only fails to convert; it can feel like noise.
Baskin emphasizes that leading retailers understand this dynamic and are leveraging their unique data assets to move far beyond basic advertising. The fusion of loyalty programs, purchase history, and AI is creating a new standard where relevance is paramount. This isn’t just about showing a customer an ad for something they’ve bought before; it’s about anticipating their next purchase, introducing them to a relevant new product, or rewarding a specific behavior in real-time.
“It’s not just sponsored product ads on a website anymore. The leaders in this space are really utilizing loyalty programs, purchase history, and AI to serve the right offers at the exact right time, whether that’s in-store, online, or via mobile… it’s really tying all of those channels together with all of the first-party data that they have to create a really great customer experience, which results in incremental sales.”
This represents a critical strategic shift. Instead of treating retail media, e-commerce, and in-store loyalty as separate channels with separate data pools, the goal is to create a unified view of the customer. When a retailer can recognize a customer and their preferences seamlessly across every touchpoint, the RMN transforms from a media channel into a customer experience engine. The result is not only more effective campaigns for CPG partners but a shopping experience that feels curated and valuable to the customer, fostering a deeper sense of loyalty that transcends price and promotion.
The Power of AI: Achieving One-to-One Engagement at Scale
The concept of one-to-one marketing is hardly new. For decades, it has been the holy grail for marketers, a theoretical ideal that was operationally impossible for any enterprise-level organization. Manually creating and deploying millions of unique offers is a logistical nightmare. This is precisely the challenge that AI is now solving, finally making true personalization achievable at scale.
Retailers are moving away from what Baskin aptly describes as “bucketizing” customers—grouping them into broad segments based on a few demographic or behavioral data points. While better than a one-size-fits-all approach, segmentation is still a blunt instrument. AI allows for a far more granular and dynamic understanding of each individual shopper, enabling the creation of millions of personalized offers or experiences in real-time.
“AI is truly getting us to that one to one personalization, which is helping retailers move beyond basic demographic targeting and segmentation and kind of what I’ll call for lack of a better term, bucketizing customers… AI also makes it possible to generate millions of personalized offers or in… Tesco’s case, challenges in real time. So something it would be virtually impossible to manually do that even for really large retailers.”
The example of Tesco’s Clubcard Challenges is a powerful illustration of this principle in action. The program, which presents personalized challenges to shoppers to earn extra loyalty points, was seamlessly scaled from three million to over ten million customers. This wasn’t just an expansion of a marketing campaign; it was a demonstration of an entirely new capability. By gamifying the shopping experience with AI-powered, individualized goals, Tesco created a platform for engagement that is far more compelling than a simple discount. It drives specific, desired behaviors while making the customer feel seen and rewarded, turning a routine shopping trip into an interactive experience. This level of sophisticated, scaled engagement is simply not possible without an AI engine working behind the scenes.
The Margin Mandate: Focusing on Incremental and Profitable Growth
In the notoriously thin-margin world of retail, particularly grocery, an obsession with top-line growth can be a dangerous game. An initiative that boosts revenue without protecting—or, ideally, enhancing—the bottom line is the proverbial hamster wheel. Baskin argues that one of the most critical shifts in evaluating retail media success is moving the focus from revenue to margin impact. The ultimate measure of a campaign’s success is not just that it drove a sale, but that it drove a profitable and incremental sale.
Incrementality is the key. Was the ad dollar spent on a customer who was already going to buy the product, or did it change their behavior? Did it encourage them to add an item to their basket, trade up to a premium product, or switch from a competitor’s brand? Answering these questions is fundamental to proving the ROI of an RMN and elevating it from a cost center to a profit center. AI-powered personalization is the mechanism that ensures this incrementality.
“Retail is such a low margin business… any initiative that only boosts top line sales without protecting margin can feel like you’re running faster on a treadmill without getting ahead… The challenge essentially guarantees incrementality in your sales. So you’re not spending your same ad dollars on the person that is already buying two, two liters of Coke. Now they’re buying four and purchasing all of them with your brand.”
By designing offers and challenges that are specifically targeted to change behavior, retailers and their CPG partners can be confident that their investments are not being wasted on cannibalizing existing sales. This creates a closed-loop attribution system where ad spend can be directly linked to profitable purchasing behavior. This level of precision allows retailers to demonstrate clear value to their brand partners and, more importantly, provides a feedback loop of data that makes the entire system smarter over time. Every campaign becomes a learning opportunity, refining the AI models to deliver even more effective, margin-accretive results in the future.
Conclusion: From Media Channel to Strategic Ecosystem
The landscape of retail media is undergoing a profound transformation. The leaders in the space are no longer thinking in terms of selling ad impressions; they are thinking in terms of building intelligent, personalized customer experiences. As Jeff Baskin’s insights reveal, the combination of rich, first-party loyalty data and the scalable power of AI is unlocking the true promise of retail media: a strategic lever that drives not just top-line revenue, but profitable growth, deeper customer loyalty, and a sustainable competitive advantage. It is about moving from transactional advertising to building meaningful, data-driven relationships that add value to every shopping journey.
For marketing leaders, the path forward is clear. It requires breaking down the organizational and data silos that have traditionally separated loyalty, marketing, and media. It demands investment in technology platforms that can unify this data and activate it with AI to deliver true personalization at scale. And finally, it requires a shift in mindset and measurement, moving the primary success metric from simple sales volume to incremental margin impact and long-term customer value. The era of the simple RMN is over. The future belongs to those who can build a fully integrated, intelligent marketing ecosystem with the customer at its very center.
