How Footfall Traffic Analysis Improve your Retail Sales
As we know, people counter can offer the best data to analysis retail footfall traffic. But what footfall traffic can help our sales and marketing? Generally speaking, footfall traffic analysis can help physical stores to do two things: optimize resource allocation and predict development trend.
Optimize resource allocation
(1) Staff optimization
Through footfall traffic analysis, the store can optimize the number and layout of employees and working hours according to the peak and trough, so as to avoid meaningless man hour expenses. Operators can arrange matching guides according to the situation of the store, so as to get twice the result with half the effort. For chain stores, we can also see the number of customers in each store every day, and arrange the appropriate number of shopping guides according to the customer flow.
(2) Allocation of retail resources
Physical stores often have large and small promotional activities, so what is the effect of the activities? In addition to the sales indicators, we can also see the explosive power of the event – how many more customers than usual? What is the conversion rate? How long does the customer stay? wait. Then, it evaluates the success of the activity by integrating multiple dimensions, and provides decision-making basis for the next activity resource allocation.
According to the customer group portrait of the store, the operator can also plan different promotional activities. Assuming that the customers in the store are mainly women aged about 30, can our promotional activities be more targeted, such as the setting of interest points, the design of event materials, etc.
(3) Allocation of training resources
Through the statistical analysis of footfall traffic, in fact, it can also reflect some problems of shopping guides. For example, some store customers stay for a long time, but the conversion rate is low, which means that the shopping guide can attract customers to stay in the store and listen to the explanation and promotion, but is not good at promoting the transaction at the end.
Then the training of the shopping guide should be aimed at “promoting orders”, rather than repeatedly training “products”. Therefore, the operator can find out the time period with few customers and short residence time through the footfall traffic law of the store, and make use of it.
Forecast development trend
When the cumulative cycle of people counting and footfall traffic analysis is long enough, we can find the rules from the data, and then make a forecast for the future. For example, according to the trend of footfall traffic forecast future footfall traffic, forecast changes in consumers, forecast the attractiveness of activities and so on. Operators often have to make a lot of decisions, which are usually aimed at the future.
Therefore, it is not feasible to rely solely on feeling, following suit and limited personal experience. The footfall traffic analysis, together with sales, can be used as a scientific and effective basis to support decision-making. One of the core values of big data is to eliminate uncertainty.
Because the data itself is meaningless, it needs to be interpreted to play a role, and corresponding measures should be taken to make it fall to the ground.
