In-store analytics, also known as audience analysis, applies the methods and concepts of web analytics to physical stores. It involves observing and analyzing visitor behavior in a store, either in real time or later, to produce customized analyses and detailed reports. The data gathered through in-store analytics allows businesses to improve product placement, optimize store layout, identify and respond to peak traffic periods, adjust staff schedules to meet busy times, study and anticipate market trends, measure customer loyalty, manage and optimize wait times, and much more.

To conduct in-store analytics, it is common to use devices placed throughout the store that detect Wi-Fi or Bluetooth signals emitted by visitors’ mobile phones, enabling them to track their movements with an accuracy of a few meters. It is estimated that between 30 and 50% of visitors can be tracked within the store. Furthermore, some in-store analytics methods can also rely on the use of surveillance cameras.

A concrete example of video-based in-store analytics was presented during a demonstration. Another demonstration highlighted the use of other technologies in the context of a large retail store. In addition, a roundtable discussion on data analytics in the retail sector was held, highlighting the advancements and challenges in the field. Finally, a sample report prepared for a shopping center provided a concrete visualization of the results and recommendations stemming from in-store analytics.