Here are some specific examples of retailers utilizing CV across core domains:
Inventory Management:
Kroger powered by Irish vision AI startup Quaternion has driven…
Automated Stores:
Zippin‘s cashierless technology has shown at UK retailers like Tesco a 35% increase in basket size versus traditional stores by removing friction during checkout.
Security:
Lowe‘s 2018 CV security rollout across 1000+ stores provided $4.5 million in recovered product in the first year alone while also improving response times by 60% compared to human monitoring.
Layout Optimization:
Revionics together with a European grocery chain used CV-based shopper tracking coupled with optimization algorithms to boost sales by 2.3% through smarter product placement strategies tailored to buying behaviors.
Beyond household names, fledgling startups also showcase innovative use cases:
Trigo Vision – Frictionless Computer Vision Checkout
- Over $100 million funding attracted
- Rolled out at Israel‘s largest food retailer Shufersal – fastest customer adoption of new service in history
- Checkout times improved 4X versus traditional cashiers
- Blackbox algorithms optimize shelf location recommendations for 2-7% incremental sales uplift
Veeve – Instore Analytics
- Leverages existing security cameras for advanced analytics at zero hardware cost
- Heatmaps reveal precise shopper behaviors – time at shelf, dwell zones, abandonment metrics
- Cloud-based SaaS model for affordability and scalability
- $8 million Series A funding in 2021 highlights retail interest
The application of computer vision spans across categories too. Pet goods retailer PetSmart applies CV-enable robots to audit shelves identifying out of stocks in near real-time. Fashion brand Ralph Lauren deploys interactive mirrors in fitting rooms with computer vision capabilities to suggest items to pair with clothes being tried on.
With surging investment and fallings costs, computer vision innovation continues accelerating. 2022 alone has so far produced:
- 3 new cashier-less store market entrants
- $342 million in retail focused CV venture funding
- 2 recent retail-targeted computer vision acquisitions
What metrics should retailers analyze if launching initial computer vision pilots? I‘d recommend tracking:
- Accuracy rates on core capabilities like product recognition
- Impact on key operational KPIs – do inventory accuracy or loss prevention metrics improve?
- Customer satisfaction scores – does the technology deliver a frictionless experience without issues?
- Employee feedback – is CV technology intuitive or does it remain confusing after training?
Based on statistical modelling against these metrics during small scale deployments, retailers can determine which innovations show merit and warrant scaling.
My projections suggest grocery will outpace all other categories in deploying CV innovations due to bullish executive attitudes, large store networks, and thin margins that benefit greatly from optimizing operations. Fueling the trend, cashier-less players like AiFi and Grabango both kicked off 2022 by sharing plans to shift into groceries targeting hundreds of potential store retrofits each.
And while early adopters demonstrate promising results, computer vision still remains in the Emerging period on the overall Hype Cycle. This leaves ample still room for the technology to mature into even more impactful and transformative retail use cases over the decade ahead.
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