Traffic Counting Technology And How It Helps Retail Businesses
Is your retail store struggling to attract visitors? Or struggling to convert the prospects that visit? Perhaps your store receives many visitors during rush hour, but most of them leave without buying anything? If your retail business is not performing optimally, and you want to understand why traffic counting technology provides some answers.
With the traffic counting technology, retailers can measure customer traffic in their stores and physical locations. Ordinarily, there are many benefits to collecting traffic data e.g., to improve staffing, optimize restocking, and ensure that supplies never run out. However, when traffic data is analyzed further, important retail metrics can be developed. Metrics like draw-in rate, conversion rate, customer/staff ratio, dwell time, occupancy rate, lost sales, cart abandonment rate, and so on.
If you own/manage a retail business, these metrics track how customers behave in your store(s), how smoothly your stores operate, and how your business is generally performing. If your store is underperforming in certain areas, the metrics will point it out. Subsequently, you can implement strategies to improve performance, tracking your progress over time.
Here is an in-depth look into how retail businesses stand to benefit from traffic counting technology:
To measure and improve store footfall
Data from retail traffic counters tell you how many people visit your store. You can further measure how many visitors you received per hour, helping you identify your peak and off-peak periods. The busiest periods hold the most potential for sales; by predicting them, you can prepare accordingly. Footfall data can also be used to measure conversion rate, i.e., the percentage of visitors that made purchases. This shows how well your store is maximizing traffic.
While it is essential to improve the conversion rate, you still need to attract a lot of visitors for these two reasons. One, prospects can only be converted when they visit your store. Secondly, the average conversion rate for brick-and-mortar retail stores is 22.5%. So, even if you attract 100 visitors, only 20/25 of them may end up purchasing something.
As a result, if data from traffic counting technology shows that you are not attracting enough visitors, improving footfall has to be made a priority. No metric is as important as visitor traffic, and all other retail parameters depend on it.
To analyze in-store shopping behavior
The next step after attracting visitors is understanding how they behave in the store. If you know how they behave, you can predict what they like and how to make them happy. Providing your visitors with personalized shopping experiences leads to higher satisfaction levels, and satisfied customers mean more sales. This report estimates that by 2020, customer experience will be the major distinguishing feature between brands, overtaking product quality, and price.
So, how does traffic counting technology measure in-store shopping behavior? Simple, through those metrics mentioned earlier. Consider this illustration: dwell time measures how many people visit a store (or a store section) and how much time visitors spent there on average. If the data shows that customers don’t spend a lot of time in your store, many factors may be responsible. Perhaps they don’t find the products they want, or there are no sales associates to help them along. Your customer/staff ratio tells you if the store is understaffed during specific periods, and you may improve dwell time by employing/deploying staff more effectively.
To improve store operations
When you combine traffic counting technology with other retail analytics software like Heatmap and Queue Management Technology, you can develop metrics to track and optimize store operations. Heatmap, for example, plots customer journey through the store. The Queue System monitors checkout queues and wait lines in the store.
Long queues at checkout lead to cart abandonment and lost sales. You can prevent these with a little preparation and proactive management. For example, when you identify your peak periods via traffic data, you can set up temporary checkout counters to handle the surge in traffic. The Queue system notifies you if wait lines are still forming, and you can either create more emergency counters or divert customers to a less busy section.
Heatmap helps you outline how visitors move around your store, which sections they spend the most time in, and the products your visitors love. From this, you can improve store layout to ease visitors’ journeys, optimize product listing, and place new products in high-traffic sections to boost exposure.
Store operation should be modelled to fit customers’ in-store behavior. This ensures that regular customers enjoy tailored shopping experiences all the time, incentivizing them to return and make more purchases.