Closing persistent gaps in loyalty programs can unlock more value for Retailers

More than 80% of the top 100 US retailers now operate some form of Retail Media Network (RMN), with notable brands reporting strong results. Amazon launched the first RMN in 2012 and now reports an estimated $60 billion in revenue from this source. Walmart’s Connect platform contributed more than a quarter of the company’s total operating income in Q4 2024 and Target’s Roundel reported $649 million in revenue in 2025.

The explosion of Retail Media Networks happened because retailers had what brands desperately needed: known, consented, transaction-verified audiences. Before we dive where RMN and Customer Loyalty programs intersect, it’s important to examine the origins of Retail Media Networks.

Shopper marketing emerged in the 1990s as CPG brands sought more precise ways to influence purchase decisions at or near the point of sale. The tools were analog: end cap displays, co-op circular placements, in-store signage, loyalty program coupons, direct mail, and trade promotion funding that flowed from brands to retailers in exchange for preferred shelf positioning and promotional support.

The best tool for the moment, in retrospect, these programs were expensive and measurable only by approximation. A brand could spend millions placing its product in a retailer’s weekly circular with virtually no ability to determine whether the spend drove incremental purchases, or simply subsidized people who would have bought anyway.

The retailer held most of the power, and the model became a structurally embedded cost of doing business rather than a discretionary performance investment.

Then two things happened in rapid succession that changed the fundamentals of shopper marketing:

• E-commerce exploded – Retailers found themselves with enormous volumes of digital traffic (website visits, app sessions, search queries) comparable to major media company’s audience inventory.
• Cookie Deprecation – As Google moved directionally toward deprecating cookie-based tracking, brands found their ability to target digital audiences outside of walled gardens degrading rapidly.

What was old had become new again

Suddenly, retailer first-party data, the type collected through loyalty programs, purchase histories, and app registrations, became one of the most valuable targeting assets in the digital advertising ecosystem.

Proponents of loyalty marketing pointed out that permission-based consumers willing to allow their transaction history to be tracked, and to share personal preferences through profile building, were the most valuable asset the enterprise could possess.

The element of qualitative data, volunteered willingly by program members, was given a new moniker, “Zero-party data,” causing loyalty marketers to smile. We always understood that customer purchase preferences, learned in the trusted environment of an incentive fueled, permission based, loyalty marketing program, far exceeded the fidelity of what could be obtained through intercept studies, online surveys and even NPS surveys.

The math is compelling. While traditional retail operates on net margins of 3–4%, advertising revenue on retail media platforms produced operating margins of 70–90%. In other words, any retailer large enough to attract brand advertising budgets had the ability to create a media business structurally more profitable than the core retail business by a factor of 15 to 30 times.

At a time when retailing was under pressure due to the emergence of online competitors, DTC brands, and COVID, the financial case for building RMNs was an easy sell internally.

Despite the rapid growth of RMN, there are challenges ahead. Research shows that an overwhelming 88% of brand buyers said they feel somewhat or heavily influenced by their retail partners to purchase RMN advertising. You can conclude that the Retail Media Network is the digital reinvention of shopper marketing. And performance measurement is evolving. With improvements, the RMN model can become more powerful.

The Intersection of RMN and Loyalty

The nexus of RMN and Customer Loyalty is data, and the more complete the vision of the customer becomes, the better the ability to monetize that data by the retailer. Since many RMN’s source valuable loyalty program member data, closing cracks in loyalty program management will deliver greater value to the associated RMN.

What marketer doesn’t want to know the answer to these questions?

• How does weekly footfall in our stores correlate to unique individuals, and can we determine transactions by uniques?
• For the same individuals, how frequently do they visit competitive locations? Which competitors, and how often?
• How can I learn more about my non-loyalty customers? Which ones have behavioral profiles that look like high-value loyalty members? What would it take to enroll them?
• Which loyalty members are showing early signs of churn before the transaction data alone would flag them?
• What is the estimated share of wallet for each customer segment — loyalty, non-loyalty, and scan-gap members — across the relevant competitive set?

Loyalty programs have been able to answer some of these questions, and only for enrolled customers. Three key gaps persist.

The Non-Loyalty Population

Industry benchmarks from our Loyalty Academy show that non-loyalty customers account for approximately 55% of total retailer revenues. Many of these unidentified customers are among the most valuable customers and the retailer is forced to use inefficient methods to engage them.

The Scan Gap

Benchmarks show that 30 – 50% of loyalty members do not consistently associate their purchases with their loyalty account. They are members on paper, but their behavior is invisible in practice. This lessens the value the retailer can deliver to its brand partners.

The Wallet Share Gap

Estimates of customer wallet share, even for loyalty program members, is a matter of estimation. The most commercially important question, “how much incremental revenue could we capture if we increased our share of this customer’s wallet?”, is unanswerable with current data.

Solutions

The ability of a brand to command CPMs of $20–$50 versus $2–$10 for standard display through an effective RMN rests on closing these gaps. Most retailers revert to the same demographic approximation that characterized the circular era. Run surveys and append data to approximate the tendencies of a cohort based on geography or demographics.

The consequence is that the data gap is not merely a marketing intelligence problem. It is a revenue quality problem because the underlying audience model is incomplete.

Tightening the Bond Between Loyalty and RMN

Data quality is becoming a competitive moat. Advertisers are becoming more disciplined, and the networks with the richest data and the best measurement will capture a majority share of budgets in the future.

Mobile data is one source that could extend the precision of RMN-era targeting to the full customer universe, closing the three persistent loyalty program gaps, and extending individual-level identity, behavioral profiling, and competitive intelligence to the full customer universe.

Retailers can leverage mobile data if best practices of cohort-based or contextual targeting are followed. This is where individuals are grouped into behavioral segments and offers are served to the segment rather than to the individual in a way that reveals the tracking. The unacceptable version — “I know you drove past a competitor this morning” — is not only off-putting but may become legally fraught as privacy regulation evolves.

The evolution from shopper to digital marketing has been driven by the same underlying force: brands want to know more about who is buying, and retailers want to be paid for what they know. RMN pricing premiums are justified by data quality and targeting precision.

A retailer that can demonstrate verified behavioral profiles for its full customer universe, not just the 45% who are loyalty members, can make a qualitatively stronger claim to brand advertisers for the value of their data. If mobile data extends that precision to the full customer universe, it expands the addressable inventory (more targetable individuals) while also improving the data quality behind existing inventory (better profiles for loyalty members who previously had scan gaps).

We’ll examine how improvements in loyalty program data can push RMN to CPM rates and better advertiser performance in a subsequent article.