8.6%
historical average shelf out-of-stock rate in Europe
An ECR synthesis of more than 50 FMCG studies.
ECR Europe / Corsten & GruenRetail economics
Make shelf execution measurable in time, sales and risk.
Start with credible sector benchmarks, replace the assumptions with your own operating data, then validate the opportunity through a focused store pilot.
Benchmarks, transparent model, pilot measurement
Business impact
The shelf is a profit surface. Blind spots cost money.
ShelfGuide connects shelf visibility to the outcomes retail leaders measure: protected sales, field productivity and controlled execution risk.
43%
of shelf out-of-stock incidents can reduce checkout value
Through abandonment, another store or a lower-value substitution.
ECR Retail Loss+0.20–0.35%
sales potential per one-point improvement in in-stock rate
An industry experience range; actual results vary by retailer.
McKinsey, 2024Up to 4h
faster stock-out correction enabled by camera vision
A sector benchmark, not a claimed ShelfGuide customer result.
McKinsey, 2020Protect revenue and margin
Find empty, low-stock or misplaced positions while teams can still act on them.
Return time to field teams
Merchandisers and regional managers work from prioritized exceptions instead of searching aisle by aisle.
Reduce execution risk
Create timestamped evidence, assign corrective work and verify that each issue is closed.
Your own assumptions
Model the opportunity in your network.
Use store count, audit volume and monthly sales to build a transparent scenario in MAD.
Open the impact simulatorIndustry benchmarks are provided for context. They are not ShelfGuide performance guarantees; results must be validated in a pilot.
Impact simulator
Turn your field activity into a business scenario.
Replace the illustrative inputs with your own data. The model keeps team capacity and sales opportunity separate so the result stays readable and honest.
Your assumptions
Illustrative starting point — replace with your data
Modeled monthly opportunity
Calculated from your assumptions
Audits analyzed
108
Team hours released
36.1 h
Capacity value
1,625 MAD
Potential sales range
10,000–17,500 MAD
Uses McKinsey’s 0.20–0.35% sales range for each one-point in-stock improvement.
View benchmark methodologyIllustrative scenario only. Released hours become savings only when capacity is reallocated or cost is avoided. Potential sales are neither profit nor guaranteed revenue. Validate the assumptions through a pilot.
Discuss this scenarioProduct vision · in development
From mobile capture today to autonomous store audits tomorrow.
The ShelfGuide robot is being developed as a new capture layer for the same AI engine: move through aisles, observe shelves and send prioritized actions to store teams.
It does not replace teams. It automates the search for anomalies so people can spend more time correcting, advising and serving shoppers.
01Available now
Mobile shelf audits
A team member captures a shelf and receives structured issues and actions.
02Next milestone
Guided multi-aisle capture
Standardize routes, coverage and recurring controls across stores.
03R&D roadmap
Autonomous robot audits
Continuous capture and synchronization with the ShelfGuide action platform.
Concept visual — design, capabilities and availability may evolve.
One intelligence layer, two capture modes
The robot extends the workflow; it does not create a separate system.
01
Computer vision analyzes the same shelf signals.
02
Exceptions enter the same prioritized action queue.
03
Managers keep one network view across mobile and autonomous audits.
ShelfGuide AI
A field question? Get an answer right away.
Describe your network, audit volume or biggest shelf challenge. The assistant covers product, impact, limitations and rollout questions.
Product, impact and roadmap knowledge
Pilot ready
Know where you're losing revenue — and fix it in real time.
From one photo, detect stock gaps and execution issues instantly. Your teams act faster, and your stores stay on track.
- Field capture without fixed cameras
- Mobile
- Centralized action management
- Multi-store
Shelf Score
Demonstration scenario · 76% · 4 priority alerts