Turn your existing cameras into privacy-safe, high-fidelity in-store analytics to measure real shopper behavior and drive growth.
Standard AI's VISION platform uses existing security cameras to deliver privacy-safe, high-fidelity in-store analytics. It measures real shopper behavior, engagement, and conversion, enabling retailers to optimize media, promotions, layouts, and staffing. The system creates a digital twin of the store, processes video at the edge, and provides dashboards or direct data feeds. It filters out non-shopper traffic to provide verified impressions and true conversion metrics.
Key Features
check_circlePrivacy-safe AI (no facial recognition)
check_circleEdge-powered intelligence
check_circleDigital twin creation
check_circleVerified impressions
check_circleShopper behavior tracking
check_circleConversion measurement
check_circleZone and area of interest definition
check_circleCustom dashboards
check_circleDirect data delivery
check_circleA/B testing support
check_circleStaffing optimization insights
check_circleLayout performance analysis
check_circleMedia impact measurement
check_circlePromotion effectiveness tracking
check_circleReal-time analytics
Use Cases
lightbulbRetail media teams measure actual shopper engagement with in-store displays and promotions, using verified impressions to prove media ROI and optimize placement.
lightbulbStore operations managers analyze foot traffic patterns and employee-customer interactions to refine staffing schedules and improve service conversion rates.
lightbulbMerchandising directors test alternative store layouts by comparing shopper flow and engagement data, enabling data-driven decisions that boost browsing and sales.
lightbulbCPG brand managers evaluate promotion effectiveness by tracking aisle traffic and purchase behavior before, during, and after campaigns, adjusting pricing strategies accordingly.
lightbulbGlobal travel retail operators filter out pass-through traffic to get accurate shopper counts and conversion rates by zone, informing media strategy and space allocation.
lightbulbRegional retailers identify underperforming areas by analyzing zone-level engagement metrics, then redesign layouts to encourage deeper browsing and higher conversion.
lightbulbNational automotive retailers implement service metrics like 'time to first contact' and 'total time with customer' to directly connect service quality to sales conversion and labor planning.
standard.ai is used for Retail media teams measure actual shopper engagement with in-store displays and promotions, using verified impressions to prove media ROI and optimize placement.; Store operations managers analyze foot traffic patterns and employee-customer interactions to refine staffing schedules and improve service conversion rates.; Merchandising directors test alternative store layouts by comparing shopper flow and engagement data, enabling data-driven decisions that boost browsing and sales.; CPG brand managers evaluate promotion effectiveness by tracking aisle traffic and purchase behavior before, during, and after campaigns, adjusting pricing strategies accordingly.; Global travel retail operators filter out pass-through traffic to get accurate shopper counts and conversion rates by zone, informing media strategy and space allocation..
What are alternatives to standard.ai?
See the ranked list of standard.ai alternatives in the Retail Analytics category on ContentBuffer.
