The retail industry is fraught with challenges, from curtailed consumer spending to increasing product costs, as widely discussed last week at the National Retail Federation's annual conference and exposition. With issues such as these, the NRF is forecasting a slight growth in sales, at 3.4 percent, for 2012. The good news: that expected uptick will likely best growth in other industries. The bad: it's down from the retail industry's 4.7 percent sales growth in 2011.
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.
On the one hand, this isn't much of anything new. Figure out what sells the best, and stock more of it. That's how retail has been done for ages.
On the other hand, I wonder how much these analytics may actually be poisoning the well for DSW. If DSW does not carry much for, say, a size 10, but has a lot of would-be customers who are a size 10, what will wind up happening is that the size 10 customers get dissatisifed with what DSW has available for variety in their size, and most will take their business elsewhere. In this regard, the analytics efforts, if not properly undertaken, may merely perpetuate DSW as a niche provider of the sizes it was already biased towards providing -- particular sizes that may or may not be in the most demand.
(Similarly, I wonder how much the converse is true -- that is, whether "too much variety" may turn off certain types of customers).
To combat this, participating DSW locations would have to strive to maintain an equal stock of all sizes in all shoes for a given period of time, to ensure that the variables of variety, availability, and customer frustration are eliminated (or, at least, minimized).
Yep, video analytics is yet another way retailers are seeking a better sense of customer needs. As we've reported previously, "retail winners" already see the value of analytics across the board and retailers throughout the industry are seeking to deploy solutions. It's probably worth another look in the future.
Hi Kicheko, if you're interested in more of what retailers are doing in-store to better understand purchase patterns and stocking issues, you might want to check out some of our earlier blogs on video analytics. Blogger Tom Davenport introduced the topic here, and we ran several additional pieces, including this Point/Counterpoint.
Its interesting to see companies use customer feedback to make business decisions such as stocking. However this too can be quite challenging when it comes to actually mapping customer feedback and suggestions to sales. Either way though, it does bring the retailer closer to the market situation. even if they won't necessarily be accurate, they will find their stocking is relevant.
"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"
Customer feedbacks can help them to cater their needs in future. Tastes are different for different peoples and most of the things which are in common can be analyzed and sort it out for an end result.
@Broadway, perhaps what's need is some sort of predictive modeling applied during the hiring process. Knowing you're building up an analytics strategy, what type of worker is most likely to embrace data-driven processes/decisions at the store level? Or, some way of measuring and analyzing the negative effect for employees' failure to follow through on BI learnings at the store level, etc.!
Shawn/Broadway -- sounds like the CEO and other top execs need to step in and make sure everybody, from the lowliest store clerk on up, understands the importance of the efforts to gather, analyze, and act on data. I remember John Lucas, who had been director of park operations at Cincinnati Zoo (but has since left to become a consultant) writing about how management made sure even the summertime college-aged workers understand the value of what the attraction was trying to do with analytics and why their role in helping collect data -- say at the point of sale -- was critical. The same would apply to retail.
Aye, there's the rub! Among challenges listed by retailers in terms of using analytics is amazingly being able to react to what they know. One way of interpreting this is that the knowledge gathered does not necessarily filter down fast enough to operations level.