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Use Case
Computer Vision Store Audits
Detect on-shelf availability, planogram compliance and queue lengths from camera feeds.
Value chainStore OperationsObjectiveElevate CXAI typeModelKPIOSA +7ppValue£220KFeasibilityLow
Dependencies
Camera infrastructure, Planogram data
Feasibility
Low — significant data, tooling or change effort
Recommendation
🚀 Future — requires camera rollout
AI deployment flow
How signal turns into outcome for this use case.
Insight
Detect on-shelf availability and queue length from camera feeds
Business Objective
Elevate CX
Data Required
Inventory, Product, Store, Asset & IoT
AI
Model — Computer Vision Store Audits
Decision
KPI: OSA +7pp
Action
Store ops, Tasking app
Outcome
£220K value
Business outcomes
- Primary KPIOSA +7pp
- Estimated annual value£220K
- Strategic objectiveElevate CX
- Value chain stageStore Operations
Type of AI
ModelPredictive or generative model that scores, forecasts or generates content.
Action surfaces
Store ops, Tasking app
Data sources required
Unified domains powering this use case via Xfuze.
Inventory
InventoryReal-time stock by SKU, location and state — on-hand, in-transit, reserved, damaged.
Typical sources
WMSERPPOS3PLRFID
Product
ProductMaster catalogue, attributes, hierarchies, imagery and rich content across all channels.
Typical sources
PIMDAMERPSupplier feeds
Store
Store OperationsStore master, clusters, formats, openings, footfall and operational telemetry.
Typical sources
ERPStore opsPeople countersBMS
Asset & IoT
Store OperationsFridges, ovens, robotics and sensor telemetry — uptime, energy and maintenance.
Typical sources
IoT platformCMMSBMS
Related use cases
Same value chain or business objective.