Sensormatic Solutions' next-generation people-counting devices use Re-Identification (Re-ID) technology and advanced deep learning artificial intelligence (AI) computing capabilities to enhance business performance in retail environments. Discover more about Re-ID and how Sensormatic Solutions is changing the way retailers think about their people-counting technologies.
Re-ID’s new retail footfall-counting technology delivers more accurate traffic data than ever. Inside, outside, across floors and zones, while delivering more comprehensive and actionable data sets.
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People-counting has evolved beyond simple entry and exit metrics to include advanced technologies like Re-ID, which uses AI and deep learning capabilities. This innovation opens up a range of new possibilities, all from one device.
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Car dealerships operate with a unique selling model where employees and customers often leave and re-enter the retail space multiple times throughout the sales cycle. Re-ID technology addresses this by excluding employees and duplicate customer entries, ensuring accurate foot traffic counts and providing actionable insights.
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Re-ID provides shopping centres with precise foot traffic data by removing duplicate counts as shoppers move throughout the property. This technology offers insights into shopper behaviour, dwell time, cross-visits, and zone popularity, helping shopping centres optimise operations, improve leasing strategies, and better understand footfall patterns and visitor intent.
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Re-ID offers department stores a more accurate footfall-counting solution by excluding passers-through and employees. It reveals where shoppers are spending their time, enabling better understanding of footfall patterns and shopper journeys, while helping stores optimise operations and improve performance.
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Footfall-counting isn’t just for traditional retailers. Learn how Re-ID can deliver accurate footfall-counting data and more for cultural and entertainment venues today.
Read the blog nowThis technology enables retailers to unlock innovative use cases – including employee and non-shopper exclusion, path analysis, shopper demographics and more – helping drive key performance metrics and strategies to achieve greater business outcomes.
