Facing the harsh realities of these numbers gets easier when retailers can make sound, data-driven decisions. And these can be on any number of things -- which products to stock, where to open a new location or close an old one, what sort of marketing campaign would generate the most sales, and so on.
Harris Mustafa, executive vice president of supply chain and merchandise planning and allocation at shoe retailer DSW, captured the essence of analytics as part of the short video, shot on the show floor, below. Data represents "an incredible opportunity and an incredible risk," he said. "If you don't choose the data properly and don't filter it, you're liable to make perhaps not the best decisions. What we're doing is we have analytics and analytical tools that we're using to really focus on the most relevant data."
In particular, DSW is analyzing historical sales data to predict future sales and optimize the sizes it carries at each store location. With appropriate sizes in stock, shoppers will have better selections, a greater opportunity to buy, and, therefore, increased loyalty to DSW. Its analytics tool of choice is Size Optimization from SAS, this site's sponsor.
For home-improvement retailer Leroy Merlin, smart data use falls under the campaign management umbrella. As discussed in this press release, Leroy Merlin is looking for customer analytics software to help "to increase campaign redemption levels, active customer loyalty, and new customer recruitment."
And for Macy's, it's all about understanding customer lifetime value, as Kerem Tomak, vice president of analytics, discusses in this article:
We want to understand how long our customers have been with us, how often an email from us triggers a visit to our site. This helps us better understand who our best customers are and how engaged they are with us. (With that knowledge) we can give our valuable customers the right promotions in order to serve them the best way possible. Customers share a lot of information with us -- their likes and dislikes -- and our task is to support them in return for their loyalty by providing them with what they want, instantly.
In each of these cases, these retailers understand the value of data. They may not all have proven results yet, but they'll get there. Metrics and measurements will guide them on what's working, and what's not. That's a far cry from the approach taken by a window-blind retailer that just mailed me an invite to purchase its products. Why did I receive such an invite? Who knows? I haven't bought window treatment in ages (OK, maybe that's why!). But really, a random snail-mailed pitch seems hardly an optimal use of any retailer's dollars.
Have you noticed any lame retail strategies that good use of data might help fix? Share on the message board below.