Operational Analytics
Operational Analytics
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Operational Analytics in OpenEye Web Services (OWS), powered by Wobot.ai, enables users to detect, analyze, and report on key events affecting business operations. These analytics help organizations streamline processes, improve customer experiences, and gain insights into day-to-day activity.
By leveraging AI-powered video analysis, Operational Analytics detects complex behaviors of customers, staff, vehicles, and objects—providing actionable intelligence and alerts tied to operational performance, customer engagement, and efficiency.
For a feature overview, see Advanced Camera Analytics for Business Operations.
Note: Operational analytics is currently in beta. All beta requests must be directed through your OpenEye representative. Please note that all analytics take roughly 90 days to for setup to complete.
Analytics Types
Operational Analytics supports a variety of analytic tasks designed for retail and quick service restaurant (QSR) environments. Each analytic type includes a specific detection goal (“Task Description”) and common example use cases.
Vehicle Journey Time
- Task Description: Detect when a vehicle remains within a defined region of interest (ROI) for longer than a specified duration. When the vehicle exceeds the configured wait time, a ticket or alert is generated.
- Use Case: Drive-thru operators can track total vehicle journey time to identify bottlenecks, optimize staffing, and improve overall service speed.
Queue Length Detection (Person or Vehicle)
- Task Description: Monitor the number of people or vehicles within a defined queue region. If the count exceeds the configured Maximum Queue Length for more than the set duration (e.g., 5 seconds), a ticket or alert is generated.
- Use Case: Retailers and QSRs can monitor checkout or drive-thru lines to reduce wait times and enhance customer satisfaction.
Wait Time (Person or Vehicle)
- Task Description: Track the time people or vehicles spend in a region of interest. Generate a ticket or alert when the configured wait time threshold is exceeded.
- Use Case: Businesses can monitor how long customers wait at service counters or pickup areas, using data to adjust staffing or workflows.
Customer Walk-in Count (Employee Exclusion)
- Task Description: Count customer entries into a designated region while excluding staff using defined exclusion zones or AI-based employee filtering.
- Use Case: Track customer foot traffic to analyze visitation trends, identify peak hours, and improve staffing and service planning.
Heatmapping
- Task Description: Identify and visualize high-traffic areas within a defined space using heat-based color mapping from camera data.
- Use Case: Retailers can use heatmaps to understand customer movement patterns and optimize product placement or layout design. This feature supports fisheye, 360°, and standard cameras.
Occupancy
- Task Description: Measure occupancy levels by counting the number of people entering and exiting all ingress and egress points.
- Use Case: Monitor real-time occupancy to support safety compliance, space management, and operational decision-making.