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AI-Driven Shelf Management to Improve On-Shelf Availability

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A multinational retail chain operating across hypermarkets, supermarkets, and convenience stores faced recurring challenges in maintaining optimal on-shelf availability. Frequent stockouts, delayed replenishments, and poor shelf execution negatively impacted sales and customer experience.

The Challenge

The client’s traditional shelf management relied heavily on periodic manual audits and staff monitoring, which were time-consuming, inconsistent, and prone to errors.

Key challenges included:

  • Stockouts & Lost Sales: Popular SKUs frequently went out of stock, causing revenue loss and disappointing customers.

  • Inaccurate Shelf Audits: Manual checks failed to capture real-time inventory gaps or misplaced items.

  • Inefficient Replenishment: Staff restocked reactively, often missing peak demand periods and leaving shelves empty.

  • Compliance Issues: Shelf planograms were inconsistently followed, reducing product visibility and violating brand standards.

These issues highlighted the need for a real-time, intelligent, and automated shelf management system to improve inventory availability, compliance, and operational efficiency.

The retailer needed an intelligent solution to automate shelf monitoring, ensure planogram compliance, and trigger timely replenishments.

The Solution: Amantra AI-Powered Shelf Management

Amantra implemented an AI-driven shelf monitoring and management system using computer vision, RPA, and real-time analytics.
  • Computer Vision for Shelf Scanning
    • Cameras and mobile devices captured shelf images.
    • AI algorithms identified stockouts, misplaced products, and planogram compliance issues with high accuracy.
  • Real-Time Alerts & Replenishment Triggers
    • Intelligent agents analyzed shelf data in real time.
    • Automatic alerts were sent to store staff or warehouse systems for immediate replenishment.
  • Predictive Analytics for Demand Peaks
    • AI models forecasted demand surges and adjusted replenishment schedules to prevent stockouts.
    • Seasonal and promotional data were factored in for proactive stock placement.
  • Automated Compliance Reporting
    • Reports on planogram adherence, shelf space utilization, and product visibility were generated automatically.
    • Non-compliance cases were flagged for corrective action.

Business Impact

The AI-driven shelf management solution created measurable improvements across operations:
  • On-Shelf Availability: Significant reduction in stockouts ensured customers always found key products.
  • Sales Uplift: Improved availability and product visibility directly boosted sales.
  • Faster Replenishment: Real-time alerts reduced delays in shelf restocking.
  • Higher Compliance: Automated checks ensured planogram adherence across all stores.
  • Operational Efficiency: Store staff were freed from manual shelf monitoring, enabling them to focus on customer service.

Conclusion

With Amantra AI-driven shelf management, the retailer transformed how it managed product availability in stores. By combining computer vision, automation, and predictive analytics, the company not only eliminated shelf blind spots but also ensured customers had access to the right products at the right time strengthening both sales and loyalty.