CONSUMER GOODS RETAIL CASE STUDY
Cut shelf-audit workload by 80–90% for an APAC consumer-goods retailer
We built an AI vision + mobile shelf verification system for real-time planogram compliance and fraud detection.
80 90% faster reviews
95% fraud detected
25% higher compliance
Consumer Goods Retail Case Study
THE CHALLENGE
What was holding them back
Manual planogram verification was
slow and inconsistent across stores.
Fake shelf photos created
compliance, reporting, and governance risk.
No real-time insights meant
issues were found too late to fix.
CLIENT SNAPSHOT
About the client
Industry
Consumer Goods Retail
Geography
Asia-Pacific
Service
AI & Automation
Existing Tools
Manual photo checks + spreadsheets, delayed reporting
THE SOLUTION
Our Consumer Goods Retail Solution
Mobile Shelf Capture Workflow
- Store teams upload shelf images in a guided mobile flow.
- Built-in checks to reduce missing angles and low-quality photos.
SKU Detection and Shelf Understanding
- Computer vision detects SKUs, facings, and placement patterns.
- Supports high-SKU environments with frequent assortment changes.
Real-Time Shelf Scoring for Compliance
- Automatic planogram match scoring per image and per store.
- Instant feedback helps staff correct shelves on the spot.
Fraud Detection at Scale
- Trained on 18M+ store photos to spot suspicious submissions.
- Flags duplicates, mismatches, and abnormal upload patterns.
Compliance Analytics Dashboard
- Live dashboards for regions, stores, categories, and timelines.
- Action queues highlight where to intervene first.
THE IMPACT
Measurable Results
95%
fake-photo submissions detected automatically, near real time
25%
planogram compliance lift within first 90 days
3x
faster fixes via alerts and dashboards
TECH STACK
Technologies Used
AI Vision
Cloud
Mobile
