Down the hall from where I write this blog entry sits a group of data-mining professionals. This dedicated network of analysts spend their workdays interpreting incoming data from more than 70,000 devices, counting the millions of shoppers passing through the doors of the world’s largest retail chains.
For years, store-level retailers have used these counts to improve their workforce management and business operations. What many of these front-line managers do not realize, however, is that this process of using shopper data to increase profits typically began when a retail executive forged a relationship with one of ShopperTrak’s data miners. Or, as we refer to them around here, Engagement Managers.
ShopperTrak’s Engagement Managers (EMs) are arguably the beating heart that keeps this company moving. EMs work closely with retail executives to locate salient points in shopper data that these execs can later reference when making business decisions. With this information and our EMs’ perspective, ShopperTrak clients can directly drive revenue.
Given their experience working with many of the world’s largest retailers, what is the most common change EMs find themselves recommending to retail executives?
The first, and often the easiest, change EMs recommend to their clients involves staffing schedules. Though it may sound simple, minor staffing adjustments can significantly affect profits, especially when store managers have never before considered data when assigning shifts to their employees. Senior Engagement Manager, Jonathan Generous, recalls being initially surprised by “the number of retailers who base their scheduling simply off of someone’s gut instinct.”
EMs understand that increasing profitability means basing staffing schedules off of traffic data, not instincts. And— more controversially—not off of sales.
When basing staffing off of data, it’s important that one uses the appropriate metrics – like Power Hours, for example. “Power hours” show the hours during the week when a store, on average, sees the most foot traffic. Fortunately, this metric isn’t hard to determine; according to Generous, “After [only] a few weeks of collecting data for a client, we can usually see when an individual store’s Power Hours occur.”
ShopperTrak’s team of EMs note that without ShopperTrak insight, most retailers experience Power Hours directly opposite the hours during which it sees the most conversions.
Typically, the data shows that when a store has a low staff-to-associate-ratio (STAR), it makes the most sales. “A common misconception among retailers is that periods with the highest transaction volume are also the periods with the highest traffic volume,” Generous said. “Generally, we find that retailers have the highest transaction periods when the traffic count is lower—this is often due to the superior customer experience that associates can create while fewer potential customers are in the store.”
Generous and other EMs explicitly define the following to retail executives: scheduling the most staff in the store at the times of peak shopper counts – that is, during Power Hours – is the simplest and most effective way to increase conversion.
This staffing advice may seem like common sense, but the tricky part of the equation is identifying precisely when a store’s Power Hours occur. Without an effective shopper counting system, a brick-and-mortal retailer cannot hope to identify these pivotal times.
Accurate data, however, is a game changer. Any store manager with knowledge of peak shopper counts can easily take immediate action to generate sales – and ultimately – profits.