ShelfTrak
ShelfTrak, a retail intelligence platform, partnered with Zenzero to transform retail execution through AI-powered shelf analysis, automated compliance monitoring and advanced analytics.
ShelfTrak is a retail intelligence and execution tracking platform that helps brands and retailers monitor, measure and optimise in-store execution across global travel retail environments. Using AI-powered image recognition, field team data collection and human verification, ShelfTrak delivers insights into shelf availability, planogram compliance, pricing, promotions, stock levels and overall retail execution.
- AI-powered shelf image recognition and analysis
- Human-validated retail execution insights
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ShelfTrak’s customers needed a more effective way to measure and improve retail execution across multiple locations, including airports, ferries and other travel retail environments.
Before the platform transformation, image and fixture coding processes relied heavily on manual exchanges of photos and spreadsheets between field teams and coding teams. This resulted in slow communication, lengthy quality control cycles, inconsistent data quality and limited scalability.
At the same time, brands required accurate measurement of key retail execution KPIs. ShelfTrak needed a solution that could deliver reliable insights faster while supporting continued growth.
ShelfTrak is a retail intelligence platform that helps brands and retailers measure, monitor and optimise retail execution through AI-powered image recognition, data collection and advanced analytics.
By combining AI-powered shelf intelligence, human validation and advanced analytics, ShelfTrak delivers greater visibility, faster insights and more consistent retail execution across retail environments.
Zenzero worked with ShelfTrak to develop an end-to-end retail intelligence platform powered by Microsoft Azure and AI..AI.
Field teams use a mobile application to capture shelf images, conduct price audits and complete store visit tasks directly from their devices. Images are uploaded immediately for analysis, eliminating manual data transfer and accelerating the flow of information.
At the centre of the solution is an AI-powered processing engine that analyses store fixtures and shelf images at scale. Azure AI services identify products, detect shelf placement and assess compliance against merchandising standards. Human verification remains built into the workflow, ensuring customers retain confidence in data accuracy and quality.
The platform also includes an analytics and reporting environment that transforms retail observations into actionable business insights. Interactive dashboards provide visibility into critical retail KPIs, including:
- Share of Space
- Planogram Compliance
- SKU Availability
- Pricing Compliance
- Promotional Compliance
- Visibility and Shelf Positioning
- Out-of-Stock Detection
- Perfect Store Scoring
By combining AI, automation and reporting in a single platform, ShelfTrak enables customers to monitor execution performance consistently across global retail locations.
The solution has helped ShelfTrak modernise its operations and deliver greater value to customers by:
- Improving visibility of execution quality across global travel retail locations
- Reducing reliance on manual image coding and spreadsheet-based processes
- Enabling faster identification of compliance, pricing and promotional issues
- Improving consistency and confidence in retail execution data
- Supporting more effective retailer conversations with objective performance insights
- Creating a standardised global KPI framework for measuring execution performance
- Establishing a strong foundation for Perfect Store improvement programmes
- Providing a scalable platform capable of supporting continued growth in data volumes and customer demand
By combining AI-powered image recognition, human validation and advanced analytics, ShelfTrak has transformed how retail execution is measured and managed.
Customers can move beyond periodic audits and gain continuous visibility into performance across their retail estate. This allows them to identify execution gaps more quickly, improve compliance with merchandising standards and take data driven actions that support stronger retail performance.
