Footprints AI vs Osmos
Osmos is a retail media operating system built to stand up and scale an ad business fast: an auction and ad-serving core, 19 apps across formats, operations and yield, live in about four weeks. Footprints AI profiles shopper behavior across the whole store, not just in front of a screen, then activates that shopper in-store, on-site and off-site with closed-loop SKU and store-level proof. Osmos monetizes inventory; Footprints AI monetizes the shopper, which is what scales retail media revenue.
Last reviewed July 2026 · Comparison based on publicly available information.
Footprints AI vs Osmos, capability by capability
| Capability | Osmos public positioning | Footprints AI positioning |
|---|---|---|
| Core strength | Monetization operating systemAd serving, auctions, yield management, advertiser onboarding and billing, packaged as 19 apps across three pillars and deployable in about four weeks. | Shopper data and sales proofAudiences from real purchase behavior, physical stores run as a measured channel, and SKU and store-level sales attribution. |
| In-store media | A dedicated in-store ads product: screen scheduling through any CMS, aisle and shelf targeting, self-serve slot booking and QR-based engagement tracking. In-store audiences come from Advertima computer vision at the screen, so profiling is bounded by screen coverage. | Behavioral profiling across the whole store, zones, traffic flow, dwell, catchment and basket, across 25,000+ stores, activated on screens, audio, POS, smart shelves, scan and go, carts and Wi-Fi, and reused on-site and off-site. |
| Data layer | Catalog, traffic and event data at very large scale, plus bring-your-own-traffic targeting and clean-room and CDP integrations. The retailer supplies the shopper data model. | A built-in shopper data model: 7B+ visits with transactions, loyalty, basket and store context resolved into Shopper Twin and Store Twin profiles covering 100% of shoppers, in-store and online. |
| Measurement | Full-funnel reporting and closed-loop attribution from impression to conversion, with ROAS and revenue uplift. In-store impact evidenced through QR tracking and online-to-offline analytics. | Media, shopper and sales metrics in one report: sales uplift versus baseline and forecast by SKU, category and store group, with test and control at store level. |
| Demand side | Self-serve tooling that helps a retailer onboard, activate and retain its own advertisers, including long-tail sellers, with wallet, creative and compliance workflows. | The same self-serve and managed workflows, plus an existing marketplace of 500+ global brands and 60+ media agencies already buying on the platform. |
| Published proof | Company-published ad-revenue figures: 3× ad monetization against a 0.5% of GMV benchmark, 200% ad revenue growth at Apollo 24|7 and 112% at Konvy, plus a 1,300-store rollout across five Southeast Asian markets. Ad revenue, not brand sales outcomes. | Measured brand sales outcomes in European grocery: +390% for Jack Daniel's, +55% for Persil, 10× ROAS for Mutti, and a retail media business scaled from low six figures to multi-million in 18 months at Profi. |
| Best fit | Marketplaces, e-commerce platforms and omnichannel retailers that need to launch or rebuild a monetization stack quickly, with ad revenue as the primary KPI. | Grocery and physical retail groups whose in-store data is the main asset and whose advertisers will only shift budget against proven incremental sales. |
Based on public Osmos product, FAQ and success-story pages, third-party coverage of the Osmos and Advertima integration, and public Footprints AI platform information as of July 2026. Framed by use case, not by unsupported feature claims.
Capability scorecard
| Capability | Osmos | Footprints AI |
|---|---|---|
| In-store as a first-class media channel | Partial | Full |
| Store Twin forecasting to plan & pace delivery | None | Full |
| Audiences from real shopper behavior (100% coverage) | Partial | Full |
| One campaign workflow across in-store + digital | Full | Full |
| Proof of delivery & real-time pacing (in-store & online) | Partial | Full |
| SKU + store-level attribution (uplift-ready) | Partial | Full |
| Built-in AI insights (missions, cohorts, basket shifts) | Partial | Full |
| Enterprise scale: private AI, white-label, multi-tenant | Partial | Full |
| Open APIs + integrations (DSP, CDP, retail systems) | Full | Full |
| Privacy-safe architecture for global rollouts | Full | Full |
Scorecard summarizes the comparison above. "Full" means the capability is a first-class product layer; "Partial" means it is present through a partner integration, a single evidence method or bring-your-own-data; "None" means it is not positioned as a core capability. Osmos earns full marks on unified campaign workflow, open APIs and privacy-safe architecture. The gaps are structural rather than cosmetic: no store forecasting layer, in-store audiences bounded by computer vision at the screen rather than profiling across the whole store, and no native store-level uplift measurement. Scoring as of July 2026.
What is Osmos?
Osmos, built by OnlineSales.ai, is an omnichannel retail and commerce media operating system for retailers, marketplaces and commerce platforms. Its OSMOSphere stack is organized as 19 apps across three pillars: Adscape for ad formats including product, display, video, offsite, email, story, gamified and in-store; ControlHub for advertiser onboarding, wallets, creative review and campaign operations; and StratEdge for yield management, demand generation and bring-your-own-traffic targeting. Founded in Pune and now operating from the US, its founding team includes Amazon ad-tech alumni.
Osmos is serious infrastructure and this page does not pretend otherwise. It is white-label, multi-tenant, API-first and built to coexist with an existing stack rather than replace it, with published scale of roughly 25 billion monthly auctions at 15 to 20 millisecond P95 latency. It holds SOC 2 Type 2, ISO 27001, GDPR, CCPA and DPDPA compliance and is an IAB member. It states that retailers go live in about four weeks, and it has shipped in-store work including a rollout across 1,300+ stores in five Southeast Asian markets. Those figures are company-published and are not independently verified here.
Where Osmos concentrates is monetization. Its product language, its KPIs and its case studies are about ad revenue: yield, fill, advertiser adoption, wallet share and growth against a percentage-of-GMV benchmark. Its in-store product delivers and schedules ads to screens through any CMS, targets by store, aisle and shelf, and evidences impact through QR tracking and online-to-offline analytics, with in-store audience intelligence added through a computer-vision partnership with Advertima. That is a legitimate architecture for growing ad revenue. It is a different architecture from starting at the transaction and working back to the ad, and it is why the platform reports what the network earned rather than what the brand sold.
Sources reviewed: Osmos product, in-store ads, FAQ, team and blog pages, plus the Osmos and Advertima partnership announcement and third-party coverage of it, July 2026.
What is Footprints AI?
Advertisers have changed what they are buying. In a January 2024 Association of National Advertisers survey, 71% of advertisers named incrementality the most important KPI for their retail media investments, ahead of ROAS. A retailer can run a technically excellent ad business and still lose the budget conversation without showing which sales would not have happened otherwise. That is where Footprints AI starts.
Footprints AI is a next-generation retail media platform built around shopper data and sales proof. It resolves transactions, loyalty, in-store sensors, online events and store context into Shopper Twin and Store Twin models, then uses them to build audiences, trigger delivery on live conditions such as product availability, traffic forecast and weather, and measure what the campaign changed. The platform spans five modules, Campaigns, Audiences, Sales & Shopper Insights, In-Store Measurement and Leads, so the retailer runs the whole operation in one place.
Where Osmos gives a retailer the fastest route to a working ad business, Footprints AI gives it the evidence that keeps brands renewing: sales uplift by SKU, category and store group, basket incidence, new-to-brand movement and incrementality-ready test and control at store level. It also brings demand rather than only the tools to chase it. The operating promise: buy true reach, pay per view, get real sales attribution.
It operates at scale across 30+ retailers, 25,000+ stores, 60+ media agencies, 500+ global brands and 50M+ shoppers, tracking 7B+ shopper visits with transactions and 7,000+ campaigns, deployed as a white-label, multi-tenant platform a retailer owns, in-store and online, with data and AI held inside the retailer's own infrastructure.
The differences that matter
Full-store profiling, not a sensor proving a view
Osmos adds in-store audiences through Advertima computer vision, which identifies who is standing in front of a screen and proves the view. That monetizes screen inventory. Footprints AI profiles behavior across the entire store, zones, traffic flow, dwell, catchment and the basket at POS, then activates that shopper in-store, on-site and off-site. Screen-bounded audiences can only be sold against screens.
Why that is the revenue question
A retail media business does not scale on screen impressions. It scales when one shopper profile can be sold across every channel the retailer owns and measured back to the basket, which is what opens performance, trade and non-endemic budgets. Proving a view at a screen sells the screen. Profiling the shopper sells the network.
What the platform optimizes
Osmos is engineered around ad yield: auctions, fill, CPM, advertiser adoption and revenue as a share of GMV, and it reports what the network earned. Footprints AI is engineered around incremental sales and reports what the brand sold, with uplift against baseline and forecast at SKU and store level and control stores where the design supports it.
Tools to sell versus demand to sell into
Osmos gives a retailer an excellent self-serve stack and the operations layer to run it, then the retailer fills it. Footprints AI provides the same workflows and connects the retailer to 500+ global brands and 60+ media agencies already buying, so launch demand is not built from zero.
Footprints AI proof, not promises
Footprints AI case studies include outcomes such as +390% sales uplift for Jack Daniel's, +55% sales lift for Persil, 10× ROAS for Mutti and +23.29% sales uplift for Coca-Cola. At Profi, part of Ahold Delhaize, the retail media business moved from low six figures to multi-million incremental revenue within 18 months, and Carrefour Romania scaled retail media to seven-figure revenue within three quarters. Across the platform, campaigns deliver 5 to 8× ROAS versus a roughly 2× industry average, with +25% new-to-brand buyers and +20% basket incidence among exposed shoppers.
Footprints AI campaign results, measured with closed-loop attribution. Incrementality is claimed only where the measurement design supports it. Figures as of July 2026.
Who should choose which?
Choose Osmos if
Your priority is standing up or rebuilding a monetization stack quickly and growing ad revenue, especially across marketplace or e-commerce inventory with a long tail of advertisers to onboard. Osmos is fast, modular, genuinely white-label and strong on auction performance, yield and advertiser operations.
Choose Footprints AI if
Your biggest asset is what happens in your stores, and your advertisers will only move trade and performance budget against proven incremental sales. Footprints AI builds audiences from real purchase behavior, runs the store as a measured channel, and closes the loop at SKU and store level.
The Footprints AI retail media stack
Retail Media Network Platform · build and scale a retailer-owned media business. In-Store Retail Media · turn physical stores into measurable media. Closed-Loop Measurement · connect exposure to SKU and store outcomes.
Footprints AI vs Osmos, answered
What is the main difference between Footprints AI and Osmos?
Osmos is a retail media operating system built to launch and grow an ad business fast, with an auction and ad-serving core, yield management and advertiser operations. Footprints AI is built on shopper data and sales proof, with audiences from 100% shopper behavior, physical stores as a measured channel, and closed-loop SKU and store-level attribution. Osmos optimizes ad revenue; Footprints AI proves the sales it caused.
Is Osmos a good retail media platform?
Yes, for what it is built to do. Osmos is credible, enterprise-grade infrastructure: white-label, multi-tenant, API-first, SOC 2 Type 2 and ISO 27001 certified, with company-published scale of roughly 25 billion auctions a month. Its results are reported as ad revenue growth rather than brand sales outcomes, and its in-store audience layer depends on a partner integration.
Does Osmos support in-store retail media?
Yes. Osmos has a dedicated in-store ads product with screen scheduling through any CMS, store, aisle and shelf targeting, self-serve slot booking and QR-based tracking, deployed across 1,300+ stores in Southeast Asia. Its in-store audiences come from Advertima computer vision at the screen, which proves the view. Footprints AI profiles shopper behavior across the whole store, over 25,000+ stores, then activates that shopper on-site and off-site too, and measures sales uplift at SKU and store level.
How does measurement compare between Footprints AI and Osmos?
Osmos provides full-funnel reporting and closed-loop attribution from impression to conversion, with ROAS and revenue uplift, and evidences in-store impact through QR tracking and online-to-offline analytics. Footprints AI reports media, shopper and sales metrics together, measuring sales uplift against baseline and forecast by SKU, category and store group, with incrementality-ready test and control at store level.
Why does marketplace demand matter when choosing a retail media platform?
Software does not generate budget on its own. A retailer launching with tools alone still has to find, onboard and educate advertisers before revenue arrives. Footprints AI connects a new network to 500+ global brands and 60+ media agencies already buying across 25,000+ stores, shortening the gap between going live and booking revenue.
Is Footprints AI a good Osmos alternative?
For grocery and omnichannel retailers whose value sits in physical stores and whose advertisers demand proof of incremental sales, yes. If the priority is launching a monetization stack fast across largely digital inventory and growing ad revenue as the headline KPI, Osmos is a strong, focused choice. The honest framing is fit, not ranking.
Monetization is the start. Proof is what renews.
Run retail media on shopper data, with physical stores as a measured channel and closed-loop SKU and store-level sales proof, on a platform you own.
Comparison based on publicly available information about Osmos as of July 2026. Osmos and OSMOSphere are trademarks of OnlineSales.ai. Advertima is a trademark of Advertima Vision AG. Footprints AI is not affiliated with Osmos or Advertima.
