As an area manager receiving daily, weekly and monthly performance reports, there can be a tendency to fall into a comfortable pattern of looking at the underperforming and top performing stores, and repeatedly having the same conversations with them. The top stores get a “congratulations,” and a challenge to keep up the good work; the underperforming stores get a “we’ll get ‘em next time” pep talk and a challenge to rise up the store rankings.
When managing multiple retail stores early in my career, I realized that many times top performing stores can have the right “magic sauce” of a great location – fabulous traffic, a great team and, of course, a store manager that puts it all together and makes it work. So, in an effort to replicate the “magic sauce” across other locations, I decided to challenge top performing stores to seize upon their opportunities, continually improve and, ultimately, achieve even more.
It was a change to the usual conversation, and it produced a surprising twist.
When asked about metrics, the manager of a top performing store identified Monday as the store’s lowest performing day of the week, when sales were lowest. Saturdays were the best performing days, driven by great traffic, and on those Saturdays, the top performing hours were 2:00 – 5:00 pm. The key managerial metric was identified as conversion (the percentage of traffic that engages in a purchase transaction).
Conversion during the peak hours on Saturday was around 15 percent, down somewhat significantly from the overall Saturday average of 19.5 percent – the peak hours on the best day of the week were trending almost five points in conversion lower than the average for the entire day. For this top performing store to perform even better, how could I help this store manager look at other key metrics to better capitalize on its high store traffic?
When we drilled down into the data more closely, we focused on the metrics of shopper yield, shopper-to-staff ratio and staff productivity.
Shopper yield is calculated by multiplying conversion with average transaction value (ATV), and it allowed us to see where gaps existed. In this case, while conversion was down during peak Saturday hours, sales associates were maintaining a very high ATV, which suggested the staff was working hard at selling.
To give context to shopper yield, we next looked at the shopper-to-staff ratio and saw – to no surprise – that it spiked during the peak hours of 2:00 – 5:00 pm. Put together, we came to the hypothesis that staff productivity was high, but that the store was understaffed. Digging even deeper yet, we discovered a trend extended over six consecutive Saturdays.
After looking at the numbers and identifying our best opportunity for improvement, the manager developed a comprehensive strategy that included:
- Adding a four-hour shift to the schedule, covering 1:00 to 5:00 pm
- Adjusting the lunch schedule to ensure peak coverage
- Instituting a contest for sales associates between 2:00 and 5:00 on Saturdays on the store hitting a 17 percent conversion
- Emphasizing personal targets on other store metrics
As a result, the top-performing store performed even better, lifting its numbers and establishing new baseline metrics as goals. More importantly, we were able to identify some of the “magic sauce” ingredients to share with all stores.
So, remember, when making those phone calls to the top performing stores, challenge them to improve. Sometimes it’s the easy metrics like conversion, shopper yield and shopper-to-staff ratio that guide store operations toward the manageable opportunities available on successful Saturdays rather than the often futile focus on the lowest performing days impacted by variables generally out of management’s direct control.
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