RMNs' $100B Blindspot: Solving Attribution in Physical Stores

Retail media networks (RMNs) have become one of the fastest-growing segments in advertising. In the United States alone, brands are expected to spend $62 billion on retail media in 2025, according to eMarketer. This includes all advertising sold by retailers across their online platforms, mobile apps, and in-store digital screens. Yet according to Oliver Wyman, nearly 90 percent of this revenue comes from online ads, with in-store digital media accounting for less than 10 percent. In the U.S., in-store digital media spending is projected to exceed $1 billion by 2028, according to Advertising Week, but that figure underscores how underpenetrated the physical store environment remains.

Missing entirely from these figures is spending on static in-store signage. Brands invest tens of billions of dollars annually on printed signs, branded displays, endcaps, and pallet setups within stores. In North America alone, spending on static in-store signage is estimated between $12 billion and $16 billion, far surpassing the projected $1 billion for in-store digital media. RMNs generally focus on retailer-owned ad placements like online ads, mobile app promotions, and in-store digital content, excluding traditional signage paid for directly by consumer goods companies. This exclusion creates a skewed picture. There's massive investment in influencing in-store shopper behavior that is not counted in RMN totals.

The reason for this underinvestment in digital in-store media is not a lack of interest from brands. It's about one unresolved issue: attribution. Retail media is built on performance. Brands want to know not just who saw the ad, but who acted on it. Online channels provide this with cookies and event-based analytics. Physical retail offers none of that, only point-of-sale lift in sales. Once a shopper enters a store, they effectively disappear from the data stream. What did they see? What did they pick up? What did they purchase? How do I connect that back to what shoppers do online, completing the omnichannel loop?

That is where spatial artificial intelligence changes the game. Using only cameras overhead, these systems digitize the physical space, creating a real-time behavioral dataset of shopper interactions. It can detect who saw a screen or display; what products were seen, picked up or ignored; and what ultimately converted to a sale. It offers the physical world equivalent of digital ad tracking, without requiring RFID, apps, or shopper input.

The irony is that retail’s most valuable ad moment is the one we measure the least: the point of purchase. A shopper sees an ad in-aisle, decides in seconds, and places a product in their cart. That moment is high intent, high conversion, and yet remains a black box for most brands. According to Coresight Research, U.S. retailers lose 5.5 percent of gross sales annually to in-store inefficiencies. Store intelligence technologies are expected to grow from $8.4 billion in 2025 to $12.6 billion by 2029. Meanwhile, retailers like Walmart and Albertsons are publicly emphasizing the importance of AI and store-level analytics in their investor communications.

There is no shortage of attention. Nearly 90 percent of U.S. retailers report challenges with price and promotion execution. Two-thirds are actively investing in store intelligence tools, yet only 20 percent have fully scaled them. The gap between strategic importance and operational implementation is real.

Brands are hungry for measurement. Retailers are hungry for media revenue. The only thing standing between them is infrastructure that connects media exposure to shopper behavior. That's why in-store media hasn't taken off like online RMNs. Brands will not spend big without the data to prove it works.

And yet, the eyeballs are there. Roughly 240 million unique shoppers visit U.S. retailers each week, according to Oliver Wyman. These are not passive digital impressions; these are real people in real stores making real purchase decisions.

In-store retail media should be the most valuable advertising channel in the market. It happens at the first moment of truth — when a shopper can pick up a product and make a purchase. What has been missing is a way to connect that moment to advertising prompts in a measurable way through attribution.

Today, most in-store shopper attention still goes to traditional signage and displays funded by consumer goods brands. This untracked investment far exceeds what's spent on in-store digital media. Without clear, data-backed attribution linking in-store ads to shopper actions, brands will keep favoring static formats over digital alternatives. Retailers are leaving substantial revenue on the table. Closing this gap isn't just a technology upgrade; it's essential to unlocking untapped advertising dollars and realizing the full value of omnichannel retail media. By linking in-store behavior data with the e-commerce insights they already collect, retailers can finally complete the omnichannel loop and give brands a unified, end-to-end view of shopper engagement and conversion.

If retailers could provide attribution for in-store media, including static print signage, they could unlock a powerful new revenue stream. Total offline advertising in the United States is projected at $191 billion in 2024. Capturing just 10 percent of that spend by shifting dollars into measurable in-store channels would generate $19 billion in new annual media revenue, fully incremental to existing RMN allocations. For a typical national retailer with $50 billion in annual revenue and a 3 percent net margin, adding just $100 million in high-margin in-store media revenue at 50 percent margin would contribute $50 million directly to pre-tax earnings. To match that same $50 million in profit, the retailer would need to generate approximately $1.7 billion in new store sales, cut $2.5 billion to $5 billion in costs, or add $250 million to $500 million in private-label sales. Compared to these alternatives, capturing incremental retail media revenue is one of the most financially efficient levers available, offering outsized impact on EBITDA and earnings per share without the capital investment, risk, or operational disruption tied to other growth initiatives.

Steve Carlin is the CEO of AiFi, a spatial intelligence platform.