Revolutionising Retail With AI-Powered People Counting At Samsung Store

Samsung Electronics, a global technology leader, embarked on a transformative journey to enhance the shopping experience at their retail stores. With 48 direct management stores nationwide and plans to install two more, they sought to optimise store operations and customer engagement. To achieve this, they leveraged the power of artificial intelligence (AI) and face detection technology to accurately count and analyse customer footfall traffic.


In the rapidly evolving retail landscape, understanding customer behaviour and optimising store layouts are crucial for success. Samsung Electronics faced several challenges:

  • Accurate people counting: The need to precisely count the number of visitors entering and exiting the stores, especially in diverse and dynamic environments.
  • Customer behaviour analysis: Gaining insights into customer paths and behaviours within the stores to improve layout design.
  • Integration with ‘Big Data’: Ensuring seamless integration of data with Samsung Electronics’ extensive ‘Big Data’ system to make data-driven decisions.
Samsung Case Study


To address these challenges, Samsung Electronics implemented the RetailTrend service, a comprehensive solution offering various analytics services, including People Counting, Heatmap, Zone Traffic, Direction Map, and Gender/Age analysis. Here’s how they utilised AI and face detection technology for People Counting:

  • AI-powered people counting: AI-driven algorithms were integrated with strategically placed fisheye cameras at store entrances and exits. These cameras accurately detected and counted the number of visitors, regardless of crowd density, varying lighting conditions, or obscured lines of sight.
  • Comprehensive customer analysis: Fisheye cameras were also installed throughout the entire store space, enabling Multi-Camera Object Tracking technology. This allowed Samsung Electronics to analyse detailed customer paths and behaviours, creating a comprehensive understanding of how customers interacted with products and store layouts.
  • Data integration: All data collected by RetailTrend seamlessly integrated into Samsung Electronics’ Big Data system through APIs. This unified data repository combined customer behaviour data from video analytics with sales data from the company’s sales system, providing a holistic view of store performance.


Samsung Electronics’ implementation of AI-powered People Counting and face detection technology yielded substantial benefits:

  • Precision: Accurate and real-time People Counting ensured that Samsung Electronics had a clear understanding of store traffic.
  • Enhanced customer experience: By analysing customer paths and behaviours, the company optimised store layouts to improve the overall shopping experience.
  • Data-driven decisions: The integrated data enabled data-driven decision-making, allowing Samsung Electronics to fine-tune marketing strategies, staffing, and product placement.
Samsung Case Study
Samsung Case Study
Samsung Case Study

Future Outlook

Samsung Electronics’ commitment to innovation continues, with plans to increase the number of installation cameras to 700 in the coming year. This expansion will further enhance their ability to leverage AI and face detection technology for improved store operations and customer engagement.

In conclusion, Samsung Electronics’ ‘Samsung Store’ case study highlights the remarkable impact of AI-powered People Counting and face detection technology in the retail sector. By accurately analysing customer behaviour and integrating data seamlessly, Samsung Electronics has positioned itself at the forefront of retail innovation, ensuring a superior shopping experience for its customers and continued success in the evolving retail landscape.

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