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For brick and mortar stores, it is no doubt that traffic flow is one of the most important indicators for the store revenue. However, customer dwell time and conversion rate are also of great business value. In old traffic flow system, it can calculate average dwell time of all customers. The principle is to integrate the number of customers stranded in the store (obtained by calculating the number of people entering the store minus the number of people leaving the store) for time integration, and then divide it by the total number of customers entering the store. A disadvantage of this method is that it is impossible to analyze the statistical distribution of the length of stay of each customer/group. Moreover, the number of customers staying in the store is greatly affected by the cumulative errors in the statistics of the traffic flow of the store, which often leads to inaccurate calculation of the average length of stay in the store. In order to obtain specific customer stay time data, it is necessary to identify each customer’s entry and leaving time.
The latest customer traffic system based on TrueFlow technology launched by Vionvision adopts advanced ReID technology, which can analyze non-biological characteristics such as clothing, appearance based on vertical viewing angle images, and accurately match customer entry and exit records, thereby calculating the dwell time of each customer.
Dwell time distribution is a very important intermediate parameter between in-store customer flow and purchase conversion, which can be applied in many aspects.
Paco Underhill, the founder of retail anthropology, has concluded through extensive research that the time customers spend in the store (shopping time only, excluding time waiting in line) is also an important factor affecting shopping volume and the relationship differs in different segments of the retail industry. For example, in an electronics store, the average time spent by customers who did not buy goods in the store was 5 minutes and 6 seconds, while that of customers who bought goods stayed in the store was 9 minutes and 29 seconds; in a toy store, the average time spent by customers who did not buy toys is 10 minutes while customers who bought toys stayed 17 minutes on average. So the longer a customer stays, the more likely they are to buy. Chain stores can statistically analyze their own actual data, discover the relationship between the length of stay in the store and purchase conversion, and assist in formulating business strategies.
Compared with online e-commerce, brick and mortar stores are increasingly taking on more functions to satisfy customer experience.Customer dwell time can directly reflect the brand attractiveness and customer experience satisfaction. If it is combined with the product reach analysis and further refines the analysis granularity, it can also determine whether new products attract customers and whether the certain products should maintain promoted along with some other important indicators. Combined with the employee training, it can also quantitatively improve service quality and customer experience satisfaction.
Dwell time distribution function can remove the invalid passenger flow which is the customers that only pass through the hall. A typical example is that the store of a well-known mobile phone brand is located next to the movie theater on the 5th floor, and more than 80% of the customers uses the store as a path to the movie theatre.The important characteristic of these customers is that they stay in the store for less than 15 seconds and enter and exit through two different doors. With Vionvision TrueFlow technology, the flow of passing through customer can be easily removed, and combined with staff exclusion algorithm, real customer flow can be obtained.
The dwell time distribution function based on TrueFlow technology will be further applied and developed in the segmented retail industry in the future, and will provide strong data support for the efficient operation of brick and mortar stores as well as customer satisfaction improvement.
Vionvision is always on the way of building the future of smart space, and there are more innovative functions to be continued. Please stay tuned!