Retail
A retail analytics solution that measures a physical store as precisely as an online one, turning footfall, dwell and demographics into higher conversion.
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Alfabeta's retail analytics solution lets a conventional store be measured with the same rigor as an e-commerce site. By applying computer vision to the cameras already on the floor, it captures how many people enter, where they go, how long they linger and who they are, then presents everything through a user-friendly dashboard. For the first time, store and district managers can see the full customer journey as data rather than guesswork, and build strategy on evidence about real shopper behavior.
The foundation is store people counting and tracking: the system automatically counts visitors entering and exiting and follows the movement of each one through the space. Layered on top, heatmap tracking calculates the density of each zone to reveal which areas are most frequently visited or passed, and dwelling measurement records the average time shoppers spend in an area so teams understand where attention concentrates and where journeys stall. Face-detection demography analysis identifies gender, age and even emotion, giving merchandisers a profile of who is actually in the store at any hour.
Those signals connect directly to commercial outcomes. Because the platform counts everyone who enters and can be integrated with the Point of Sale, it calculates the conversion rate as the ratio between visitors and the customers who actually make a purchase, exposing exactly where footfall fails to become revenue. That single metric reframes staffing, layout and promotion decisions around a number retailers previously could only estimate.
The system is built to fit an existing estate rather than replace it. The Alfabeta αPS platform integrates with systems already in place, including POS and property security systems, through an API, and streams every movement and activity in real time to one dashboard. The practical payoff is concrete: marketing strategy grounded in visitors' profile and demographic data, goods placement arranged to match the most-visited areas, and a defensible conversion figure that ties in-store traffic to sales.
Footfall Counting
Automatically counts visitors entering and exiting and tracks the movement of each one through the store, giving an accurate measure of true traffic. Paired with POS data, that count becomes the denominator for a real conversion rate rather than an estimate of how many shoppers a location actually draws.
Zone Heatmaps
Calculates and measures the density of each area to reveal which zones are most frequently visited or passed by shoppers. Managers use the heatmap to arrange goods placement in line with the busiest areas, position high-margin displays where attention is highest and diagnose cold spots the floor plan is wasting.
Loss Prevention
The same real-time vision layer that tracks movement can surface unusual activity and unattended zones for the store's security team, and because the platform integrates with existing property security systems through the API, alerts and video context reach the people who already respond to them.
Queue Management
Real-time visibility into how shoppers concentrate near checkout and service points helps managers see building pressure and move staff before wait times frustrate customers and cost sales, using the same live people-counting and density signals that drive the rest of the platform.
Demographic Insights
Face-detection demography analysis identifies the gender, age and emotion of visitors automatically, so merchandising and promotions can be tuned to the characteristics of the people actually in the store. Combined with dwelling measurement, it shows not just who visits but where different segments spend their time.
Multi-Store Benchmarking
Because every location reports the same metrics such as footfall, dwell time, heatmap density and conversion into one dashboard, head office can compare stores on a like-for-like basis, identify which layouts and staffing patterns perform best and spread those practices across the estate.
Frequently asked questions
How does the solution calculate conversion rate for a physical store?
It counts every visitor who enters using people-counting and tracking, then compares that traffic against actual transactions from the Point of Sale, which it integrates with through an API. The conversion rate is the ratio between visitors and the customers who make a purchase. This lets a conventional store be measured much like an online one, where you always know how many people arrived versus how many bought.
Will it integrate with our existing POS and security systems?
Yes. The Alfabeta αPS platform is designed to integrate with systems you already run, including Point of Sale and property security systems, through an API. That means footfall, dwell and conversion data line up with your sales records, and the vision layer can share context with the security tools your team already uses rather than becoming a separate silo.
What can the demographic analysis tell us, and does it identify individuals?
Face-detection demography analysis estimates the gender, age range and emotion of visitors so you can tailor merchandising and promotions to the profile of people actually in the store. The purpose is aggregate audience understanding for marketing strategy, not identifying named individuals; deployments are configured to respect the privacy and data-handling requirements of the operator and local regulation.
How do heatmaps and dwelling measurement help with store layout?
Heatmap tracking measures the density of each area to show which zones shoppers visit or pass most, while dwelling measurement records how long they linger. Together they reveal where attention concentrates and where journeys stall, so you can arrange goods placement around the busiest areas, position key displays where they will be seen and fix cold spots that the current layout is wasting.
How quickly is the data available to managers?
The platform provides real-time visibility: it tracks every movement and activity using the store's cameras and sensors and presents the information through a user-friendly dashboard as it happens. Managers do not wait for end-of-day reports; they can see current traffic, dwell and queue pressure and act on the same shift, while head office reviews trends across locations from the same view.