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Blurbs comparison of ShopperTrak (Sensormatic) and Celebrus
Learn about how these Data, Analytics and Insights vendors stack up against each other by checking out our blurbs, claims, and case studies.
ShopperTrak (Sensormatic)
"Enhances retail operations with data-driven insights."
Focused on Retail Performance & Commerce Attribution .
Sensormatic turns retail data into actionable insights that improve operations and decision-making. By focusing on inventory intelligence, loss prevention, and shopper traffic analytics, they help retailers streamline operations. Their tech supports better customer experiences and improved sales through smart, predictive analytics tailored to today's retail environment.
Seamless Source Tagging
Sensormatic claims that their Source Tagging solution reduces shrink and increases revenue through an integrated approach with suppliers.
Inventory Intelligence Platform
Sensormatic claims their Inventory Intelligence solutions provide item-level visibility across the retail enterprise to maximize revenue.
Traffic Analytics Insights
Sensormatic claims their ShopperTrak traffic analytics enable understanding shopper patterns to enhance customer experiences and conversions.
Celebrus
"Capture and activate digital identity data real-time"
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Celebrus simplifies capturing and activating digital identity data across channels in real-time. It stitches together insights from logged-in, anonymous, or even offline actors, ensuring marketers have a comprehensive view. The platform's no-tagging-required approach minimizes data gaps, making personalization accurate and responsive.
True live-time data activation
Celebrus claims that it captures and activates first-party data in true live-time, offering a complete one-to-one identity map.
Advanced fraud solution
Celebrus claims that it provides the world’s most advanced, comprehensive fraud solution by integrating extensive data capture and behavioral biometrics.
Scalable data infrastructures
Celebrus claims that its Cloud infrastructure modernizes systems to scale effectively, reducing data analysis burdens and enhancing real-time data access.