The Hybrid Advantage
The Shelftrak Triple Threat
AI + Human Verification = Data Confidence
Some retail intelligence solutions tout "zero-shot" AI, meaning no training data is required, and claim around 95% accuracy. But in stores with thousands of product facings, even a 5% error rate means hundreds of misidentified items, risking costly execution mistakes and missed sales.
Shelftrak's hybrid approach merges zero-shot AI with trained data and final human review, eliminating the 'blind spots' of purely automated systems. The result? Near 100% accuracy across thousands of SKUs so you can confidently catch errors and protect your sales.
Why 95% Accuracy Isn't Good Enough
Cumulative Errors
At 4,000 facings, a 5% miss translates to 200 incorrect or missed detections, enough to derail promotions and compromise planogram compliance.
No Human Oversight
With fully automated solutions, errors can remain undetected for days or weeks that magnify their impact on store execution and negatively impact revenue.
Missed Opportunities
If your data is only 95% accurate, you risk underestimating demand, misplacing promotions, and losing sales. Over time, those hidden gaps add up and weaken your competitive position, leaving revenue on the table.
100% Accuracy: Shelftrak's Hybrid Model
Zero-Shot Analysis
Photos initially pass through VISTA, Shelftrak's advanced AI, which can recognise new products without extensive pre-training.
Trained-Data Matching
We then cross-reference each detected item against a massive proprietary SKU database, adding a second layer of validation.
Automated QC Checks
The system flags any inconsistencies (e.g., promotional stickers, packaging variations) for further review.
Human Verification
Our experts review flagged items, ensuring near 100% accuracy while maintaining speed and scalability.
"We used Shelftrak to verify end-cap placements across multiple retailers and saw immediate improvements in brand visibility and overall store compliance."
