High Accuracy Achieved for a Personal Care Company

The client is one of the pioneers in adapting Image Recognition for in-store execution. In one of the Asian markets, the client was serving 2,000+ outlets as a part of its Perfect Store Programme. It was using a market leading IR vendor for more than 3 years, but was facing some challenges:

• Accuracy for SKU-level on-shelf availability (OSA) was low
• Reporting dashboard lacked depth and flexibility
• On-field user experience of the app was not seamless
• Custom Planogram KPIs were measured with surveys rather than image recognition
• No image quality feedback from AI when new users were capturing images.
  

The client ran an on-field pilot where like-to-like comparison was done between ShelfWatch and incumbent vendor. The results convinced the client to switch to ShelfWatch.

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• ShelfWatch delivered 95%+ SKU level On-Shelf-Availability (OSA) accuracy v/s 85%+ for the old vendor
• With ShelfWatch, the client got detailed breakdown with SKU-level Share of Shelf (SoS) insights which made the reporting also useful for brand teams
• The field users found ShelfWatch faster and simpler to use, despite expectations of resistance to change
• The client achieved better audit outcomes at lower cost as compared with incumbent vendor