Apparent Age Estimation and Dynamic Retail
Challenge
Understanding your customer is the first rule of success in the retail industry. Brick-and-mortar retailers usually rely on opt-in rewards plans to capture demographic data. Most of these programs are activated at the point of sale—after shopping is complete. That means retailers miss valuable opportunities to increase sales in real time, putting them at a disadvantage compared to online competitors.
To deliver tailored, responsive in-store experiences and to power the next generation of dynamic marketing, traditional retailers need:
Accurate, real-time demographic data
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Segmentation based on the apparent age of visitors
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Consistent and live quality data to power automated processes
VodafoneZiggo Optimizes Staff Planning with Xovis Data
Solution
A vision-based in-store analytics solution is a proven method for improving store performance in real time. When sensors that support such a solution are capable of capturing demographic data in real time, retailers can gain deeper insights.
The industry’s most advanced sensors can automatically and accurately:
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Estimate the age of visitors passing within sensor coverage area in real time
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Deliver a range of demographic statistics, including gender estimation, apparent age estimation, and adult/child differentiation
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Identify in-store objects, such as wheelchairs and shopping carts, that influence people flow and sales
In the fast-paced retail industry, data accuracy is non-negotiable. PFM Intelligence relies on Xovis' advanced 3D stereovision sensors to ensure precise analytics, enabling us to consistently deliver impactful, data-driven insights that enhance customer experiences and drive growth.
Benefits
Data about what areas or products perform best with different demographic segments helps retailers shorten costly testing periods.
Apparent Age Estimation supports processes that require accurate, real-time data, including:
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Dynamic in-store marketing displays
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Fact-based staff allocation
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Product placement targeting specific age groups
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Additional retail use cases
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Frictionless Checkout
Automation helps balance customer flow and prevent loss at self-service zones
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Measure Customer Engagement
Measuring customers’ in-store dwell times can boost sales of higher margin products
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Improving Store Layout
Accurate store traffic data helps retailers optimize layout and product placement
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View Direction
Retailers can boost revenue by measuring in-store attention
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Customer Counting
Optimal staff and layout depend on real-time customer engagement data
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Optimizing Product Positioning / Assortment
Retailers looking to support their category manager are turning to tech
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Real-Time Waiting Analytics
Retailers need a robust queue management system to eliminate friction points
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Preventing Queue Formation
Queuing up can become a costly friction point for brick-and-mortar retailers
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Expanding Sales with Demographic Data
Understanding gender-specific shopping trends helps retailers optimize resources.
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Customer Centric Staff Allocation
Retailers need a robust queue management system to eliminate friction points
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Staff Exclusion and Sales Performance
Real-time KPIs help retailers optimize performance across all locations
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Use-Based Cleaning
Smart Retail requires Smart Cleaning to enhance customer experience
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Group Shopping Analytics
Shopping habits change with company, aiding retailers in boosting sales
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Window Shopping Analytics
Tracking capture rates from window shoppers can boost store performance
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