Technologies
In-Store Analytics with Computer Vision
Retail analytics for physical stores: understand how shoppers move, wait, engage and buy, and turn that data into decisions.
What is computer vision in retail?
Computer vision in retail uses cameras and AI models to turn what happens on the shop floor into structured data. Instead of guessing, retailers measure footfall, dwell time, queues, zone performance and conversion in each store, and compare stores, periods and campaigns from a single retail analytics dashboard.
What our retail analytics measures
Footfall and capture rate
Count passersby and entries to understand how well the store front converts street traffic into visitors.
Dwell time
Measure how long shoppers stay in the store and in each zone, and spot areas that hold or lose attention.
Heatmaps
Visualise where shoppers walk and stop, so layout and merchandising decisions are based on behaviour, not intuition.
Queues
Monitor waiting at checkouts and fitting rooms and trigger alerts before queues affect service.
Conversion
Relate traffic to transactions to measure store conversion and its evolution over time.
Engagement with content
Measure attention in front of screens and displays to evaluate in-store content and retail media.
How in-store analytics works
1. Capture
Cameras or sensors are positioned at entrances, zones, checkouts and screens according to the questions the retailer wants to answer. Each deployment is designed store by store.
2. AI processing
Computer vision models detect and classify movement to produce metrics such as counts, direction, dwell time and occupancy, so the output is data rather than footage to review.
3. Dashboard
Metrics are consolidated in a retail analytics dashboard where teams compare stores, days, hours and zones, and connect them with sales data when available.
4. Alerts and action
Real-time alerts notify store teams about queues or other events so they can act while the shopper is still in the store.
How we work
- STEP 1
Consulting
We analyse your stores, goals and existing infrastructure.
- STEP 2
Design
We design the combination of technologies for each location.
- STEP 3
Installation
On-site installation and integration with your systems.
- STEP 4
Content & analytics
We set up the CMS, content and dashboards.
- STEP 5
Support
Own technical support and maintenance.
Solutions
People Counting 4.0
AI footfall counters for stores, malls and outlets.
Customer Journey
Understand every step of the shopper journey in-store.
Employee Journey
Empower store teams with data on reception and productivity.
Product Journey
From shelf to checkout: out-of-stock detection and product conversion.
Loss Prevention
Retail loss prevention with video analytics and RFID.
Gondola Endcaps 4.0
Digital, measurable gondola endcaps.
DOOH & Offline Retail Media Analytics
Measure in-store retail media audiences, impressions and attention.
Heatmap Without Staff
Automatic store heatmaps without manual observation.
Sales Area Correlations
Connect zone traffic with sales performance.
Malls and Outlets Traffic Monitoring
Footfall monitoring for shopping centres and outlets.
Offline Content Optimization and A/B Testing
A/B test in-store screen content and measure its real impact.
Industries
Fashion & Fast Fashion
Fitting rooms, window displays, RFID and store analytics.
Luxury Retail
Immersive LED experiences, reception analysis and clienteling.
Grocery & Supermarkets
Out-of-stock detection, endcaps, queues and retail media.
FMCG Brands
Measured in-store retail media and trade marketing.
Telecommunications
Queues, reception and interactive kiosks for telecom stores.
Automotive Dealerships
Showroom LED screens, reception and footfall analytics.
Travel Retail & Airports
Airport retail analytics, LED and retail media.
Shopping Centers & Outlets
Footfall analytics, heatmaps and mall digital signage.
Frequently asked questions
How does computer vision work in retail?
Cameras capture what happens on the shop floor and AI models convert it into metrics such as footfall, dwell time, queues and conversion, which are shown in a dashboard.
What KPIs can I track with in-store analytics?
Typical KPIs include footfall, capture rate, dwell time, zone performance, queue length and waiting time, engagement with screens and store conversion.
Which solutions are built on this technology?
People Counting 4.0, Customer Journey, Employee Journey, Product Journey, Loss Prevention, heatmaps, sales area correlations, mall traffic monitoring, DOOH analytics and offline A/B testing.
Is it suitable for chains with many stores?
Yes. The approach is designed to compare stores and regions from one dashboard, and deployments are planned store by store.
Next step
Talk to an expert
Tell us about your stores and what you want to measure or communicate. We'll design the right combination of analytics, screens and content for your points of sale.