3 Critical Store Performance Metrics You’re Missing

3 Critical Metrics of Store Performance You’re Missing

Last updated: February 05, 2013Perry Kuklin

real-time queue management

Retailers have grown to rely on traditional measures of store performance, such as sales per square foot, sales per customer, conversion rate, sales per hour, etc. and traditional measures of data gathering, i.e. secret shoppers, in-store observations, point-of-sale data, and customer surveys. No doubt these performance indicators and measurement techniques can yield valuable information, but is it enough? A complete picture of customer satisfaction is crucial in today’s competitive retail environment. There are three metrics that can help managers develop a more holistic view of the factors impacting the retail environment and store performance:  

1. Drive-bys (or Walk-bys)

These customers open the door, look inside, and immediately depart. Or maybe they simply look through the window, see the line, and walk away. Yet again, they might never make it into a space in the parking lot for fear of a long line. The thought process? “There is no way I’m standing in that line.” Lines are inevitable, but customers who see that the checkout is mismanaged are less willing to wait. Imagine being able to measure these missed opportunities and how this measure of lost sales might impact your assessment of store performance.

2. Cart Abandonment Rate

E-commerce pays plenty of attention to measuring cart abandonment; it’s easy to track a visitor’s sudden desertion of their virtual shopping cart. But what about identifying the occurrences of cart abandonment in a brick-and-mortar retail environment? Cart abandonment can happen at any juncture – at the back of the store when the sudden loss of motivation occurs, or when reaching the checkout line and seeing a poorly run process, slow-moving line, or any number of other reasons. What if you could track when and where cart abandonment happens and how your waiting lines, store traffic, or staffing levels might have played a role?

3. Lost Customers

Some customers can be so upset or disgusted by their checkout experience that they never plan on coming back to the store. Perhaps they waited in line for a terribly lengthy time, or they weren’t happy with the treatment they received in the line. Think it doesn’t happen to your store? Nearly half of all customers will actively avoid the retailer or brand in the future if the wait in line was longer than five minutes. Customers become frustrated after two and a half minutes of no apparent progress in a queue. And a third of customers report they have abandoned the checkout line when forced to wait for more than five minutes. Think about the prospect of getting a better measure of these abandonments and customer losses, including where they occur, the time of day, how crowded the store was at the time, how many people were in line, and how many staff members were on hand. How would data like this improve your store performance? If you're being challenged to capture something deeper and more meaningful to help make improvements in staff allocation, managerial decision making, checkout times, and customer satisfaction, consider looking beyond the same old data and start looking at how the advancements of today’s queue management technology can give you better data from which to act. Real-time queue monitoring has come on the scene to proactively identify customer service problems before they adversely affect customer satisfaction. In addition to tracking checkout performance, such systems can monitor employee-to-customer ratios and real-time behavioral information that goes far beyond transaction data. The results are better customer service, improved perceived customer value, and, ultimately, a more profitable business. Instead of wondering what valuable customer behavior data you might be missing, learn more about the real-time queue monitoring capabilities that can be easily implemented in your retail environment. Speak with a Lavi queue management expert today.  

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