Every retailer with a fleet of stores is sitting on an advertising business. The math is hard to argue with: Amazon generated $68.6 billion in advertising revenue in 2025. Walmart Connect brought in $6.4 billion the same year, up 46% year over year. Target’s Roundel now generates nearly $2 billion in combined advertising value for the company.

Those numbers explain the land rush. They do not explain why so many CPG brands and advertising teams still cannot answer a basic question: did the in-store campaign actually drive incremental visits?

The online side of retail media is mature. Click-through rates, conversion tracking, and closed-loop attribution have been solved for years. The in-store side — which still accounts for the majority of grocery, pharmacy, home improvement, and department store sales — has a measurement gap that makes it difficult to justify budget allocation, optimize placements, or prove ROAS. It is the same data accuracy challenge that has plagued physical retail analytics for years, now amplified by the scale of RMN budgets.

This guide covers how retail media networks work from both the retailer and advertiser side, where the market stands today, and how foot traffic data is closing the attribution gap that has held in-store retail media back.

What is a retail media network?

A retail media network (RMN) is an advertising platform operated by a retailer that lets brands promote products and services across the retailer’s owned channels — websites, apps, email, in-store displays, self-checkout screens, and digital signage.

The concept is straightforward: retailers have audiences, transaction data, and physical or digital touchpoints. An RMN packages those assets into advertising products that brands can buy.

What separates retail media from traditional advertising is proximity to the purchase decision. A sponsored listing on a grocery retailer’s website reaches a shopper who is building a cart. A digital sign in the snack aisle reaches someone standing in front of the shelf. That proximity is why retail media commands premium CPMs relative to open-web display.

There are two important distinctions within retail media:

Endemic vs. non-endemic advertising. Endemic campaigns promote products the retailer already carries — a cereal brand running sponsored product ads on Walmart.com. Non-endemic campaigns promote products or services from outside the retailer’s assortment — a gym running in-store signage at a health food chain or an insurance company advertising on a retailer’s checkout screens. Non-endemic is the growth frontier, but it introduces measurement challenges because the conversion happens outside the retailer’s ecosystem.

Online vs. in-store (and omnichannel). Online RMN advertising in the form of sponsored product listings and display ads on retailer websites is well established with clear attribution. In-store retail media through digital signage, audio ads, checkout screens, and sampling is growing fast but lacks equivalent measurement infrastructure. Omnichannel campaigns that combine both are where the industry is heading, but few networks can measure the full journey today.

The market today: who is operating and who is winning

Retail media ad spend is projected to exceed $100 billion globally by 2027, according to BCG and eMarketer forecasts. In the US alone, retail media already represents more than $60 billion in annual spend — making it the fastest-growing advertising channel ahead of social, search, and connected TV.

The landscape breaks down into three tiers:

The scaled leaders

Amazon Ads dominates with $68.6 billion in 2025 ad revenue. Amazon’s advantage is data completeness: they own the search query, the product listing, the click, and the purchase. Attribution is a closed loop. For CPG brands, Amazon is table stakes.

Walmart Connect is the strongest omnichannel play at $6.4 billion in ad revenue (FY2026). Walmart reaches an estimated 90% of US households, and their RMN spans Walmart.com, the Walmart app, in-store TV walls, self-checkout screens, and in-store radio. They’re investing heavily in in-store measurement capability.

Target Roundel generates nearly $2 billion in total value for Target. Roundel is positioned as a premium network focused on higher-income demographics. Target reports that 76% of its shoppers use the website or app while physically in-store — an omnichannel behavior that creates natural attribution bridges.

The grocery and specialty players

Kroger Precision Marketing (KPM) leverages Kroger’s loyalty card data covering 60 million households. KPM can tie ad exposure to actual in-store purchase through its 84.51° data science division, giving it one of the strongest closed-loop attribution stories in grocery.

Instacart Ads occupies a unique position as a marketplace RMN for grocery. Brands can sponsor products across multiple grocery retail partners simultaneously — useful for CPG companies that sell through dozens of banners.

Albertsons Media Collective, Dollar General Media Network, Ulta Beauty’s UB Media, Best Buy Ads — nearly every retailer with scale is launching or expanding an RMN. The long tail of retail media networks is growing fastest.

The non-traditional entrants

The RMN concept is expanding beyond traditional retail. Marriott International launched a travel-focused media network letting brands advertise across hotel properties. Casey’s General Store launched Casey’s Access featuring at-pump, in-store, and digital advertising across 2,400 convenience store locations. Chase and other financial services companies are launching commerce media networks powered by transaction data.

How retail media networks work for each team

The value chain behind retail media involves three distinct teams with different priorities. Most guides treat this as a retailer vs. advertiser binary, but reality is more nuanced.

For the retail media team (the sell side)

If you operate a retail media network, your challenge is packaging your audience and touchpoints into products that advertisers will pay for — and pay for repeatedly. That requires:

Reach quantification. How many unique visitors does each store see per month? How does that vary by daypart, day of week, and season? Online, you report unique users and page views. In-store, you need equivalent metrics. Foot traffic analytics provides exactly this — unique visitor counts, visit frequency, dwell time, and trade area reach for every location in your fleet.

[PASSBY DATA NEEDED: Monthly unique visitor counts for a major grocery or big-box retailer, broken down by daypart, showing the scale of in-store audience that an RMN can monetize]

Audience profile definition. Advertisers want to know who your shoppers are. Demographics, psychographics, cross-shopping behavior, and spending patterns all matter. The more granular you can describe your audience — down to customer profile segments — the higher CPMs you can command. PassBy’s Almanac platform provides visitor demographics, household income distributions, lifestyle segmentation, and cross-visitation data — the kind of audience profile that turns a pitch deck into a media plan.

Pricing optimization. Not all locations and time slots are equal. A pharmacy location that sees 3,200 daily visitors on Saturday mornings commands a different rate than one that sees 800 on Tuesday evenings. Traffic-based pricing requires reliable, granular visitor counting. Without it, you’re selling impressions you cannot verify.

For CPG and brand advertisers (the buy side)

If you buy retail media, your challenge is allocating budget across an overwhelming number of networks and proving that the spend drove incremental outcomes.

Network selection. You need to decide which networks give you the best audience overlap with your target customer. If you are a premium natural foods brand, you need to know whether Kroger or Whole Foods shoppers are a better match for your ideal customer profile. Cross-visitation data reveals where your target consumer already shops, helping you pick the right network before you spend a dollar.

[SCREENSHOT: Almanac cross-visitation report showing audience overlap between two retail chains — demonstrating how brands can evaluate RMN audience fit]

Market-level optimization. National RMN buys are common but inefficient. A sunscreen brand does not need the same in-store media weight in Phoenix and Seattle. Foot traffic data at the market and store level lets you focus spend on the locations and regions where your audience is concentrated.

Attribution and incrementality. This is the big one. For online RMN campaigns, the retailer can typically report whether an ad view led to a purchase. For in-store campaigns — especially non-endemic — the conversion usually happens somewhere else. Did the gym ad in the grocery store drive new gym memberships? Did the auto insurance ad on the checkout screen generate quote requests? Foot traffic data provides incrementality signals: did visits to the advertiser’s locations increase among the retailer’s shoppers after the campaign started?

PassBy’s platform can measure cross-visitation trends before, during, and after campaign windows — giving advertisers an incrementality signal that in-store media has historically lacked. The 94% correlation between PassBy’s foot traffic measurements and ground truth data means the signal is credible enough to inform budget decisions.

For the measurement and analytics team

Whether you sit on the retailer or advertiser side, the analytics team needs standardized metrics that both parties trust.

Impression equivalents. Online impressions have a clear definition. In-store impressions do not. How do you count the audience for a digital sign in the cereal aisle? Foot traffic measurement offers a defensible starting point: unique visitors to the zone or store during the campaign period, filtered by dwell time and daypart.

Lift measurement. Did the campaign change behavior? The clearest signal is a change in visitation patterns — either to the advertiser’s locations (for non-endemic campaigns) or within the retailer’s stores (for endemic campaigns). PassBy’s Benchmarking Reports can compare visit trends for exposed vs. control locations, giving measurement teams a rigorous lift framework.

Audience verification. Is the retailer’s stated audience profile accurate? Third-party foot traffic data serves as validation. If a retailer claims their shoppers are predominantly high-income families, visitor demographic data should confirm or challenge that claim. This matters for negotiation on both sides.

The in-store measurement problem — and why it matters now

In-store retail media is the fastest-growing segment of the RMN market, but it also has the biggest measurement gap. That gap has real consequences:

For retailers: it suppresses CPMs. If you cannot prove impressions, you cannot charge what the audience is worth. In-store RMN CPMs are typically 30–50% lower than equivalent online placements — not because the audience is less valuable, but because measurement is less mature.

For advertisers: it prevents budget allocation. Most CPGs have spent years building sophisticated digital attribution models. When the in-store media team cannot provide equivalent metrics, budget flows to the channels that can prove ROI — even if in-store reach is significantly larger.

For the industry: it slows standardization. The IAB and MRC are working toward in-store media measurement standards, but the industry needs data infrastructure to implement those standards. Foot traffic analytics platforms provide the foundation — unique visitor counts, audience profiles, dwell time, and pre/post campaign visitation patterns.

The gap is not insurmountable. The same foot traffic data that retail teams use for site selection and competitive intelligence can power in-store media measurement. The data already exists — it just has not been widely applied to the RMN use case. In fact, geofencing technology already enables location-triggered digital ads; extending that measurement to in-store media is the natural next step.

Five RMN strategies that work with foot traffic data

1. Trade area-based targeting

Rather than buying an entire network, select locations where the store’s trade area overlaps with your target customer’s geography. A fitness brand advertising in grocery stores should focus on locations where trade area demographics show high incidence of gym membership and health-conscious spending patterns. PassBy’s Markets view can map trade area demographics and psychographics for every store in a retailer’s fleet, turning a blunt national buy into a precision placement strategy.

2. Daypart and visit pattern optimization

Foot traffic data reveals when different customer segments visit. Weekday morning shoppers at a grocery store skew differently from Saturday afternoon families. Schedule your in-store media by daypart to match high-value audience windows. This is equivalent to dayparting in TV advertising but applied to physical stores.

3. Cross-visitation-based network selection

Use cross-visitation data to identify which retailer’s shoppers already visit your locations or competitors’ locations. If 18% of Retailer A’s shoppers also visit your category, but only 6% of Retailer B’s do, Retailer A is the better RMN investment. This replaces gut-feel network selection with data-driven portfolio decisions.

[PASSBY DATA NEEDED: Cross-visitation analysis between a major grocery chain and a QSR or fitness brand, showing the percentage of shared shoppers — this demonstrates how brands can evaluate RMN audience quality]

4. Incrementality measurement through visitation lift

Run your in-store campaign in a subset of locations and hold others as controls. Measure whether the campaign locations show increased cross-visitation from the retailer’s stores to your locations relative to controls. This gives you a clean incrementality read without requiring the retailer to share transaction-level data. It is the same A/B testing logic that store ops teams already apply to promotional campaigns — just measured with visitation data instead of POS receipts.

5. Competitive conquest campaigns

Identify stores where your competitor’s customers over-index. If foot traffic intelligence shows that Retailer A’s shoppers visit your competitor’s brand at 2x the rate of your brand, that retailer’s in-store media is a conquest opportunity. Target those specific locations with competitive messaging. For broader frameworks on tracking competitor performance, see our competitive intelligence guide.

Challenges ahead for retail media

Retail media is growing fast, but the industry faces structural challenges that will shape the next phase of maturity:

Measurement standardization. Every network defines impressions, reach, and attribution differently. The lack of cross-network standards makes it almost impossible for advertisers to compare performance across RMNs. Industry bodies are making progress, but adoption is uneven.

Ad fatigue and customer experience. The incentive to monetize every surface — self-checkout screens, shopping cart handles, parking lot digital signs, store radio, app push notifications — risks overwhelming shoppers. Retailers that over-monetize will erode the shopping experience that makes their audience valuable in the first place.

Walled garden dynamics. Most RMNs operate as closed ecosystems. Advertisers cannot easily move data, creative, or learnings across networks. This creates operational complexity for CPG brands that advertise across dozens of retailers and increases dependence on each network’s self-reported metrics.

In-store inventory scaling. Physical retail media inventory — screens, signage, audio — requires capital expenditure. Unlike digital ads, you cannot programmatically create more inventory when demand increases. Retailers need to be strategic about where and how they deploy in-store media infrastructure.

Non-endemic expansion. The biggest growth opportunity is non-endemic advertising (brands that the retailer does not carry), but it also introduces the hardest attribution challenge. When the conversion happens outside the retailer’s ecosystem, both sides need third-party data sources to close the loop. Foot traffic platforms like PassBy provide the cross-visitation and incrementality signals that make non-endemic RMN spend measurable.

If you are evaluating in-store retail media — whether you are building a network or buying media on one — reach out to PassBy to see how foot traffic and cross-visitation data can quantify your audience, sharpen your targeting, and close the attribution gap.

Frequently asked questions

What is a retail media network? A retail media network is an advertising platform run by a retailer that lets brands promote products across the retailer’s digital properties (website, app) and physical stores (in-store screens, signage, audio). Major examples include Amazon Ads, Walmart Connect, and Target Roundel. Retailers earn advertising revenue while brands reach shoppers close to the point of purchase.

How big is the retail media market? US retail media ad spend exceeds $60 billion annually in 2025 and is projected to surpass $100 billion globally by 2027. Amazon accounts for roughly a third of the market. Walmart Connect ($6.4B), Target Roundel (~$2B), and Kroger Precision Marketing represent the next tier, with hundreds of smaller networks launching across grocery, convenience, pharmacy, and specialty retail.

How do you measure in-store retail media? In-store retail media measurement is less mature than online. Key metrics include unique visitor counts (impression equivalents), dwell time in specific zones, and post-campaign visitation lift. Foot traffic data from platforms like PassBy provides third-party measurement for audience verification, incrementality analysis, and campaign attribution — filling the gap that retailer first-party data cannot cover on its own.

What is the difference between endemic and non-endemic retail media? Endemic advertising promotes products the retailer already sells — for example, a cereal brand running sponsored listings on a grocery website. Non-endemic advertising promotes products or services from outside the retailer’s assortment, such as a financial services company advertising on pharmacy digital screens. Non-endemic is the growth frontier but requires third-party attribution because the conversion happens off the retailer’s platform.

How can foot traffic data improve retail media targeting? Foot traffic data tells you how many people visit a store, when they visit, where they come from, and where else they shop. For retail media, this enables trade area-based targeting (choosing stores where your audience is concentrated), daypart optimization (scheduling ads during high-value windows), and cross-visitation-based network selection (picking networks whose shoppers already visit your category).

How do you prove ROI on in-store retail media campaigns? The strongest approach is visitation-based incrementality measurement. Run campaigns in a subset of locations with holdout controls. Use foot traffic data to measure whether exposed locations show higher cross-visitation to the advertiser’s stores relative to controls. This provides a clean incrementality signal without requiring transaction-level data sharing between retailer and advertiser.