Illustrative framework connecting in-store media exposure, attribution, sales data, and optimization. Metrics shown are illustrative and do not represent the Coca-Cola/Profi campaign results.
In-store and near-store media have become some of the most consequential touchpoints in the commerce media ecosystem. They reach shoppers close to the point of decision, connect brand messaging to physical availability, and can influence behavior within minutes of purchase. For media owners, however, placement count and quality alone no longer win the argument. Proving measurable value does.
An In-Store Media ROI Toolkit is a repeatable operating framework that connects media delivery, audience exposure, shopper behavior, sales outcomes, and commercial decision-making. Media owners use it to quantify performance, prove value to advertisers, and price inventory with more confidence.
The distinction matters. Historically, in-store media was often sold on qualitative strengths such as visibility, proximity, dwell time, or enhancement of the shopping experience. Those qualities remain important, but advertisers now expect evidence of incremental outcomes: increased conversion, higher basket value, greater household penetration, stronger brand or category sales, or measurable changes in visitation and purchase behavior.
From measurement framework to commercial operating system
A strong toolkit should do more than produce a post-campaign report. It should create a common measurement language among the media owner, retailer, advertiser, agency, and technology partners. It should define what was delivered, how exposure was established, which business outcome was evaluated, how incrementality was tested, and how the findings will improve the next campaign.
It is also important to distinguish return on ad spend from return on investment. Incremental ROAS measures the incremental revenue generated for each dollar of media spend. ROI should go further by accounting for margin, production, technology, data, labor, and other program costs. Conflating the two is one of the more common mistakes in a vendor’s pitch deck.
A well-built toolkit enables media owners to:
- Measure reach, frequency, exposure quality, and audience composition
- Link exposure to behavioral and sales outcomes
- Separate correlation from true incrementality
- Identify high-performing inventory, formats, times, and creative
- Support performance-informed pricing and packaging
- Increase advertiser confidence, renewal rates, and long-term value
The five foundational pillars
1. Audience and Exposure Measurement
The first requirement is to establish who had a reasonable opportunity to see the media, where the exposure occurred, and how often. Depending on the environment, this may include traffic counts, sensor-based audience estimates, dwell time, screen or placement viewability, campaign playback verification, and privacy-preserving audience composition estimates where lawful and appropriate.
This pillar should distinguish between media delivery and human exposure. A screen log confirms that an ad played; it does not, by itself, confirm that a shopper was present, attentive, or able to act. The strongest systems reconcile playback, location traffic, dwell patterns, and store conditions to create a defensible exposure estimate.
2. Incrementality and Attribution
Attribution tracks what happened after exposure. Incrementality asks whether it happened because of the campaign — a harder, more useful question. A credible ROI toolkit therefore needs more than before-and-after comparisons or simple correlations.
Depending on scale and data availability, measurement may use randomized holdouts, matched test-and-control stores, household-level exposed and unexposed groups, matched markets, or carefully constructed baselines. Outcomes can include incremental sales lift, household penetration, category conversion, basket expansion, visit frequency, new-to-brand purchase, and halo effects across related products.
Every report should make the methodology visible. Advertisers should understand the comparison group, measurement window, confidence level, exclusions, and limitations. Transparency is essential to trust.
3. Data Integration
In-store media does not operate in isolation. Closed-loop measurement typically depends on connecting campaign delivery with point-of-sale data, loyalty or CRM records, inventory and pricing systems, product hierarchies, store attributes, and—when needed—privacy-safe clean-room environments.
Inventory data is especially important. A campaign cannot generate a fair sales test when the promoted SKU is unavailable, incorrectly priced, or poorly distributed. Integrating media and operational data allows the media owner to distinguish a media problem from an availability or execution problem.
4. Analytics, Insights, and Decisioning
Raw data becomes valuable only when it improves a decision. Dashboards and reports should therefore move beyond impressions to show reach and frequency, exposure by location and time, sales or behavioral lift, incremental ROAS, performance by format or audience, and the relationship between creative, placement, inventory, and outcome.
The most useful tools also support scenario planning. Media owners should be able to ask what would happen if they shifted weight to a different daypart, expanded to higher-performing stores, changed creative, altered frequency, or combined in-store media with mobile, on-site, off-site, or out-of-home activation.
5. Optimization and Commercial Activation
The final pillar turns learning into action. Optimization tools help media owners refine placements, adjust campaign pacing, update creative, respond to product availability, prioritize high-value inventory, and forecast future revenue. Over time, the toolkit should create a learning loop in which every campaign improves audience planning, measurement design, inventory strategy, and advertiser outcomes.
At this point, measurement stops being a reporting exercise and starts shaping the business itself: media owners can package inventory around demonstrated value, build outcome-oriented products, and price locations and formats according to how they actually perform, rather than treating every exposure as interchangeable.
Real-world case study: Coca-Cola at Profi
A recent campaign illustrates how the five pillars can work together. In February 2025, Coca-Cola used Footprints AI to promote a new 1.5-liter package across Profi stores. The two-week activation combined AI-based shopper targeting, in-store digital screens, in-store radio, mobile-app placements, and a dynamic store rollout that responded to product availability and shopper behavior.
According to the published case study, the campaign produced a 23.29% sales uplift versus a 250-store control group, increased the SKU’s volume share within the cold-drinks subcategory by 28%, and generated 3.84x incremental ROAS. The value of the example is not simply the headline result. It is the operating model: audience targeting, omnichannel activation, inventory-aware optimization, a control group, and sales-based attribution were designed as one system.
Vendor-reported acknowledgment: These results were reported by Footprints AI, the campaign technology provider, and have not been independently audited.
What media owners gain
A robust ROI toolkit changes the media owner’s value proposition. Instead of selling undifferentiated impressions, the organization can demonstrate which environments, formats, and activation strategies create measurable outcomes. That evidence can support stronger pricing, more effective inventory utilization, and more productive conversations with advertisers and agencies.
Measurement also builds trust. When buyers understand the methodology, receive consistent reporting, and see how insights are used to improve performance, they are more likely to renew campaigns, expand commitments, and treat the media owner as a strategic partner rather than a placement vendor.
Implementation challenges
Building the toolkit requires discipline. Privacy and consent practices must be designed into audience measurement and data matching. Legacy POS, CRM, and inventory systems may require middleware or API development. Retail operations teams need clear workflows so that campaign, product, pricing, and availability data remain accurate. Measurement definitions must also be standardized across teams and partners so that metrics are comparable rather than merely convenient.
Media owners should begin with a small number of clearly defined outcomes, document the methodology, and build repeatable test designs before expanding into more complex predictive or personalized use cases. The objective is not to collect the most data. It is to produce the most decision-useful evidence.
The next generation of the toolkit
Artificial intelligence will make these systems faster and more adaptive. Predictive audience planning, contextual creative selection, inventory-aware campaign pacing, automated anomaly detection, and real-time optimization will increasingly connect the physical store to the broader commerce media ecosystem. But technology will not replace sound measurement design. AI can amplify a strong methodology; it can also accelerate weak assumptions.
Put the five pillars together and in-store media stops being sold on visibility alone. It gets priced, packaged, and defended the way any other accountable media channel is. Media owners who build that discipline now will have an easier time holding advertiser budgets when the next round of scrutiny arrives.
Source for the case study
Footprints AI, “Coca-Cola Retail Media Case Study: +23.29% Sales Uplift.” Campaign conducted February 2025; Vendor reported case study.
Published: September 10, 2026