Retailers have teased and rolled out online deals for days, even weeks, but the real Black Friday is here.
New analytics software showed The Wine House the products that were not moving off the shelves. As a result, the retailer launched a promotion and refined its buying strategy.
Tracking online customer behavior on e-commerce sites is a well-known function of web analytics technology. But analytics also can dig out actionable data from both store and web operations – just ask The Wine House, a web and store retailer that discovered through analytics that it had $400,000 of inventory that hadn’t moved in a year or more.
Approximately 15% of the retailer`s $20 million in annual sales take place online and the rest in its Los Angeles store. President Bill Knight’s goal is to turn inventory at least six times a year.
However, when The Wine House recently began using analytics software from The SAS Institute – the retailer’s first-ever use of web analytics – Knight says one newly available category of inventory data “stood out like a sore thumb” –the amount of inventory that had been in stock a year or more. The Wine House purchased the software from an authorized reselelr, which then hosted it for the retailer.
The Wine House took action, holding a huge sale in August – online and in the store - that cleared about $400,000 worth of the merchandise at or below cost. Knight says he’s grateful to have moved this inventory, especially with the grim economic outlook, and that the business intelligence gleaned from the use of analytics also will benefit operations going forward.
“When I showed my buyers how much money was tied up, we are able to see why we’d had to pass on some deals,” he says. “With SAS, I can give the buyers information on inventory weekly so they know where they are open to buy and not open to buy. “
Knight adds the analytic software’s ability to identify aging inventory by supplier has further guided his buying strategy. During the holidays, The Wine House pulled back from a planned $30,000 wine purchase because analytics revealed how much of the supplier`s product already was in stock and hadn’t moved in a year. “I told him we couldn’t take any more of his inventory until we worked through what we already had,” he says. “We knew we had a problem, but other than walking the floor and recalling, we couldn`t identify this kind of information before.”