08. October 2020

Monitor the in-store customer traffic

Monitor the in-store customer traffic

Although merchants know what people buy and how often they buy it based on transactions, they cannot determine what people do in their store before making the transaction. This is where Real-time Occupancy Management comes in, providing retailers with answers to a number of key questions based on data, among other things.

  • What is the shopping route of our customers? Where do they spend the most time?
  • Are our opening hours set correctly?
  • How much time do customers spend inefficiently in the store?
  • How does queue length affect the frequency of purchases?
  • Do we have sufficient staffing relative to the current number of our customers?
  • Have we distributed our categories correctly throughout the store?
  • How does our customer demography change over time?
  • How many cashiers do we need to have in the store next week?

The situation regarding the Coronavirus epidemic has brought many constraints to the retail sector, but it has also created an opportunity for innovation. The system helps retailers in two ways: firstly, to comply with the strict hygiene standards and regulations imposed by the government, and secondly, it provides a unique view of customer movement in stores in real-time. In addition, it takes customer behaviour analysis to a whole new level thanks to the use of modern sensors.

Aa assistant in times of crisis

The system’s backbone is a cloud-based application collecting data from high-precision sensors and cameras deployed throughout the store. Together, they can analyse the customers’ movements and their gender, age, or whether they are shopping alone or in a group. Indeed, data collection starts at the front of the store because the sensors track how many people pass in front of the entrance and how many of them eventually go inside. They can then track the customer’s route through the store. The tool can analyse which shelves people spend the most time at, which zones they prefer, how often they return and, of course, how much time they spend in queues. The store manager can monitor this data in real-time, allowing them to react quickly by,for example, reinforcing staff or opening another checkout.

At times when the focus concentrates on maximising store occupancy, Real-time Occupancy Management keeps an eye on the flow of new customers. It uses visual signalling right outside the store to report whether additional people can enter or whether the quota has been reached. Using the Staff Exclusion plugin, the sensors can easily distinguish your employees from customers, which is very important to avoid skewing the measured numbers.

Main modules

  • Browsing: Shows the so-called cold and warm zones in the store, i. e., how much time the customer spends in different areas of the store. What were their routes and the distance they walked.
  • Traffic: Advanced traffic analytics analysing WiFi signals from mobile phones and optical sensors. It provides an accurate picture of the store’s population.
  • Demographics: It can analyse the age and gender of customers using biometric sensors.
  • Queue: Precise video sensors monitor queues in real-time to improve the staff organisation on the shop floor according to the current situation.
  • Buying: It allows you to compare sales data with data on customers’ actual behaviour. It provides a detailed insight into key metrics such as turnover, average purchase value or the number of items in the basket converning behavioural analytics.

In addition to fast, real-time outputs, the application can also convert all the collected data into comprehensive reports that a retailer can use to optimise their store. Because the tool is highly flexible and modular, you can set it up and select features based on exactly what the retailer needs. While the detailed in-store analytics in the form of the basic Browsing module is particularly suited to the food and fashion industry, the Traffic module, monitoring store occupancy, can be applied to virtually any type of operation: stores, showrooms and banks.

Furthermore, the sensors are tiny and almost invisible to the customer, so they do not interfere with the establishment’s overall design; this constitutes an additional advantage of the whole system. Data collection is, of course, anonymous and carefully set up to fully comply with the GDPR data protection regulation parameters.

Real-time Occupancy Management is not just a short-term solution for times of crisis. It is a robust, yet highly transparent and effective tool that can provide long-term benefits to any retailer who wants to succeed in the highly competitive retail market. Therefore, hundreds of stores across Europe already use the application in practice. The newly acquired data not only helps them to ensure a safe and convenient shopping experience, but it also leads to higher turnover, cost optimisation and hand in hand with higher customer satisfaction.

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