New York Times Validates Dealer Tools
The following article from the New York Times was recently forwarded to me. I think that there is a lot of correlation and validation here as to what we’re doing today in the retail automotive industry with new software tools. What do you think?
A Data Explosion Remakes Retailing
MOST people think of the grand challenges in computing as big science projects, like simulating nuclear explosions or protein folding. But with the holiday shopping season just ended, consider another: retail marketing.
Retailing is emerging as a real-world incubator for testing how computer firepower and smart software can be applied to social science — in this case, how variables like household economics and human behavior affect shopping.
To be sure, major retailers like Wal-Mart Stores have long been sifting through in-store sales and demographic information to aim goods at different stores and to tightly manage supplies.
But what is changing, experts say, is the rapid surge in the amount and types of digital data that retailers can now tap, and the improved computing tools to try to make sense of it. The data explosion spans internal sources including point-of-sale and shipment-tracking information, as well as census data and syndicated services. Companies also track online visitors to Web commerce sites, members of social networks like Facebook and browsers using smartphones.
The better tools, they say, are ever cheaper and faster computers and so-called business intelligence or analytic software for finding useful information and patterns in that data.
Retailers are increasingly mining vast troves of digital information to improve the decisions they make about pricing, shelf-stocking and product offerings. “This huge and growing ecosystem of data is an asset that some retailers are really beginning to exploit for competitive advantage,” said Thomas H. Davenport, a professor of information technology and management at Babson College. “It brings more science into the business. Relying on gut feel is yesterday’s strategy in retailing.”
Mountains of data and whiz-bang technology are no cure for tight-fisted shoppers, of course. And this was a challenging holiday season for most retailers. Even computing enthusiasts acknowledge that the technology is far better at fine-tuning decisions on pricing, product assortments and shipments than the basic merchandising judgments about what goods to make and buy from suppliers.
“In the world of retail merchandising, there will always be a mix of art and science,” said Lori J. Schafer, a retail expert at SAS Institute, which specializes in analytic software. “But the more you can get into customers’ heads, the better off you are.”
That is certainly the strategy at Wet Seal, a 500-store specialty retailer of clothing, mainly for teenage girls. Wet Seal is a so-called fast-fashion retailer, meaning that trends in its market change quickly and the company needs little time — as few as three weeks — to put its clothes, shoes and accessories into stores after its buyers make their decisions. Staying in tune with the shifting tastes among young women is crucial, said Edmond S. Thomas, the C.E.O.
Its stores account for more than 80 percent of Wet Seal’s sales, but the company’s presence on the Web is growing, using its site as a source of market insights as well as revenue. Last year, Wet Seal introduced a Web feature called Outfitter, which allows users to put together their own outfits online.
The virtual outfits are posted, and users can browse through them, comment and exchange recommendations. So far, more than 300,000 user-generated outfits have been designed, generating millions of page views.
“We can get a read on where our customer is headed faster than ever before,” Mr. Thomas said. The user designs, he said, helped the company see early signs of a recent trend toward more informal outfits — dressy tops, but casual bottoms, usually jeans.
In October, Wet Seal created its own iPhone application, called iRunway. With it, a customer in a store can tap in an item’s ticket number — bar code recognition comes later this year — and see how it has been used in outfits that other customers have created online.
The user-generated product selections and recommendations, combined with mobile phone access, build a community of customers that should increase sales, Mr. Thomas predicts. “We’re at the very initial stages, but that will be the wave of the future in fashion retailing,” he said.
At 1-800-Flowers.com, Christopher G. McCann, the president, agrees that “social mobile” retailing will be a major venue for sales and marketing. The company also has apps for the iPhone, the BlackBerry and phones using Android software.
Most of the company’s more than $700 million in sales of flowers and gift baskets are online, so it can quickly change prices and offerings on its Web site — often hourly. The company has used analytics software for years to tweak its online store and marketing. In the last six months, Mr. McCann said, 1-800-Flowers.com has improved the conversion rate — browsers to buyers — on its Web site by 20 percent, with more finely targeted pages and e-mail promotions.
The company also uses analytics software to optimize operations — including marketing, shipping, distribution and manufacturing.
The technology, Mr. McCann says, helped cut costs by $50 million last year.
Nihad Aytaman, a senior technology manager at Elie Tahari, a private $500 million-a-year maker of designer clothes for women and men, is an enthusiastic proponent of analytics technology. The information housed in the company’s data warehouse has grown fivefold in the last three years, and is constantly mined for sales trends and to orchestrate supplies and shipping.
“It takes all this data and makes it visible and meaningful, so you can make sense of it and act on it,” said Mr. Aytaman, an engineer with an M.B.A. “But you’re not creating something that wasn’t there. Designers and merchandisers have to go with their gut if they are making something new.
“No computer can mimic human intuition,” he said.