Why in-store measurement stalls
Retail media grows faster than the evidence supporting it. These are the four gaps operators run into first.
In-store inventory is sold on estimates
Most retail media networks price screen inventory from store traffic averages rather than observed exposure at the screen itself.
Proof of delivery is thin
Brands funding in-store campaigns increasingly ask the same question digital buyers ask: did it actually run, where, and for how long?
Outcome data lives elsewhere
Commerce results sit in POS and e-commerce platforms that the media team usually cannot query, so attribution stalls at impressions.
Privacy constrains the obvious approaches
Camera-based audience analytics create consent, policy and reputational problems that many retailers will not accept.
The measurement layers Glass provides
Exposure, delivery, context and outcome — assembled from sources you already own or explicitly authorise.
Footfall and dwell sensing
Glass uses privacy-conscious mmWave sensing to count presence, passing traffic and dwell near a screen — no cameras, no facial recognition, no personally identifying data.
Campaign proof of play
Playback records from Signal establish what ran on which screen and when, giving delivery evidence that stands on its own.
Exposure-weighted reporting
Combining playback with observed presence and dwell produces opportunity-to-see reporting per screen, zone and daypart instead of a store-level average.
Permissioned third-party data
Weather, local events, traffic and other datasets you authorise help explain performance differences between sites and periods.
Aggregated commerce outcomes
With authorised access, order, product, inventory and promotion signals are analysed in aggregate to look for sales movement associated with campaign periods.
Sensor-driven context from Relay
Shelf-level sensing such as Nexmosphere presence, dwell and Lift & Learn interaction adds product-level context where those sensors are installed.
Commerce and POS data paths
What is realistically connectable, described accurately rather than as a partner logo wall.
Shopify POS
Authorised order, product, inventory and promotion signals from a Shopify merchant account, correlated with signage campaign periods.
Square
Orders, catalogue, inventory and location data accessed through Square's public API with the merchant's authorisation.
Stripe
Payment and terminal data available through Stripe's documented APIs where the merchant grants access.
Other open-API platforms
Toast, Clover, Lightspeed Retail and Oracle Simphony expose APIs, exports or middleware paths; feasibility and available fields vary by platform, plan and region.
Operational outcomes to expect
Inventory you can describe honestly
Screen-level exposure and dwell give a defensible basis for packaging and pricing in-store media.
Campaign reports brands accept
Delivery evidence plus observed exposure moves the conversation past 'the screens were on'.
Placement decisions with evidence
Dwell and traffic patterns show which zones deserve screens and which are being over-served.
Privacy scope and honest limits
- mmWave sensing measures presence, movement and dwell. It does not identify individuals, capture images, or perform facial recognition, and it produces no personally identifying data.
- Commerce analysis is aggregated and correlational. Observed movement associated with a campaign period is not proof of individual causation, and we do not claim it is.
- Every third-party data source requires the account owner's authorisation. Available fields, event coverage and history depend on the platform and plan.
- Shopify, Square, Stripe, Toast, Clover, Lightspeed Retail and Oracle Simphony are integration targets reachable through supported APIs, OAuth, webhooks, exports or scoped custom integrations — not formal partnerships, certifications or endorsements.
Retail media measurement FAQ
- What is retail media network measurement?
- It is the practice of showing what an in-store media network actually delivered: which screens played which campaign, how much audience exposure and dwell occurred near them, and whether related commerce outcomes moved during the campaign period.
- How is in-store media attribution done without cameras?
- Glass uses mmWave sensors that detect presence, movement and dwell without capturing images. Those signals are combined with proof of play and, where authorised, aggregated POS data.
- Do you identify individual shoppers?
- No. The sensing approach is deliberately non-identifying, and commerce analysis is performed on aggregated data. Individual identification is neither performed nor offered.
- Which POS platforms can be connected?
- Any platform whose merchant-authorised API or export gives access to the necessary order and catalogue signals. Shopify POS and Square are documented integration paths; Stripe, Toast, Clover, Lightspeed Retail and Oracle Simphony are open-API possibilities whose feasibility depends on the account, plan and region.
- Can this prove a campaign caused a sales lift?
- It can show correlated movement between campaign delivery, observed exposure and aggregated sales for a defined period and set of locations. We report that as evidence, not as guaranteed causation.
Related pages
Measure what your network actually delivered
Tell us how your in-store inventory is sold today and which commerce platforms you can authorise, and we will map a realistic measurement approach.
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