AI-Powered Retail Analytics Platform Using CCTV
Intelense turns existing store cameras into a live retail intelligence layer for footfall, dwell time, queue pressure, heatmaps, and conversion insights.
What is retail analytics?
Retail analytics is the process of analyzing in-store customer behavior such as footfall, dwell time, queue formation, movement paths, product engagement, and conversion signals.
Intelense uses AI-powered video analytics to convert existing CCTV footage into structured KPIs that store operations, merchandising, and marketing teams can act on in real time.
Retail analytics using CCTV enables businesses to measure customer behavior without installing additional hardware.
From camera feed to store KPIs
A simple flow designed for existing retail infrastructure.
Cameras capture video
Intelense connects to existing CCTV, IP cameras, NVR, DVR, or RTSP streams.
AI models process footage
Computer vision identifies people, movement, dwell, zones, and queue activity.
Data becomes insight
Raw scenes are converted into structured metrics and event metadata.
Dashboards show KPIs
Teams see real-time and historical KPIs across stores, zones, and time periods.
Retail analytics built around daily store decisions
Traffic counting
Measure visits, entries, exits, direction, and peak demand by store or zone.
Customer attention
Understand which products, displays, and aisles keep shoppers engaged.
Movement density
See high-traffic and low-traffic areas so layouts can be tuned with evidence.
Checkout monitoring
Detect queue buildup and trigger staffing actions before wait times rise.
Visit to engagement
Connect footfall with zone engagement and POS context to locate missed revenue.
Multi-store dashboard
Compare stores, regions, cameras, and campaigns from one operational view.
Where retail analytics creates value
Explore the Intelense retail analytics stack
Retail Analytics FAQs
What is retail analytics?
Retail analytics is the process of analyzing in-store customer behavior such as footfall, dwell time, movement patterns, queue pressure, and conversion signals to improve store performance.
How does retail analytics work with CCTV?
Cameras capture video, AI models detect customer movement and behavior, the footage is converted into structured metrics, and dashboards display KPIs for operations, merchandising, and marketing teams.
Can existing CCTV be used for retail analytics?
Yes. Intelense KenVision connects to existing CCTV, IP cameras, NVR, DVR, or RTSP streams so retailers can measure customer behavior without installing separate sensor hardware.
What retail metrics can Intelense track?
Intelense can track footfall, entry and exit direction, dwell time, zone occupancy, queue length, heatmaps, customer flow, and conversion from visits to engagement.
Does retail analytics require extra sensors?
No. Intelense is designed to use the store camera network already in place. Extra sensors can be integrated when useful, but they are not required for core video analytics.
How accurate is AI retail analytics?
Accuracy depends on camera placement, lighting, and crowd density. Intelense validates each deployment and retail case studies have shown 95 percent footfall accuracy in real store environments.
Is raw video stored in the cloud?
Deployments can be configured for edge processing so raw video remains within the customer environment while dashboards receive structured analytics and event metadata.
How quickly can a retail analytics dashboard go live?
When camera streams are available, a pilot can typically be configured quickly with store zones, KPI dashboards, and alerts tailored to the retailer's workflow.
Turn store cameras into retail intelligence
See how Intelense converts existing CCTV into live business KPIs for retail teams.