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SHOP - BUT DON'T DROP

When shoppers are separated from what they want, everybody loses.

Better data integration and Web-based tools will help consumers get the goods.

Source: Business 2.0

Posted on January 4, 2001

      Retailers and manufacturers have a problem. Their customers can't find what they want. Often there's no simple way to determine which branch of a chain store actually stocks an item. It can be even harder to know if what one manufacturer calls a size 8 sweater is equivalent to a size 8 in another label. Or how about when that maker means what you'd call "purple" when it says "plum"?

      The result of the confusion: Wasted time, angry customers, and lost sales.

      But help is at hand. Technologies under development will make it possible to build a Website that helps consumers identify exactly what they want and helps merchants know in real time what's on the shelf and what isn't. Building such a site will take a lot of behind-the-scenes integration, but the payoff could be a lucrative boost in customer service and better inventory management.

      "What stores need to do is make things easier for the working customer," says Cathy Hotka, vice president of information technology at the National Retail Federation (NRF). "Many people have things that they want to buy but don't know where [to look]."

      Several retailers, including Home Depot, JCPenney, and CompUSA are experimenting with Web and data integration tools that will let consumers skip the scavenger hunt and concentrate on serious shopping. It's a worthwhile investment, says Lisa Allen, a director at Forrester Research. Although consumers are expected to spend an estimated $269 billion online in 2005, the Web will have even more impact offline, influencing $378 billion in brick-and-mortar sales.

      Here's an explanation of how the technology would help a shopper through the stages of a typical purchase decision.

What I want to buy

Creators of shopping portals already strive to bring consumers and products closer together. But there's often a daunting gap between the words shoppers use while searching to describe what they want and the words retailers and manufacturers use to describe what they have. A data integration technique called normalization -in essence, a translator-could be the bridge.

      Consider the case of a man who wants to buy a purple sweater for his wife over the Net. Without normalization, the Website on which he types in purple would miss links to information about merchandise deemed violet , lavender , or plum . If he types in sleeveless he might miss vest.

      To prevent such confusion, ShoppingList.com, which provides the shopping services offered on Yahoo!, plans to normalize the product description data it receives from retailers and manufacturers, says CEO Jeff Greenberg. He says the site will make searches and comparison-shopping easier for customers by populating its database with all the terms consumers would use to describe key attributes of products.

      While that effort can solve the problem to some degree, it's ultimately the manufacturers and retailers who will have to supply the broadest help. Toward that end, the Retail Federation is working with those companies on an attribute normalization system, based on Extensible Markup Language. A draft vocabulary is expected to be released this month, says Hotka of the NRF.

Does it fit?

After our sweater shopper has conducted a normalized search to identify a few sweaters, he still has to know if they will fit his wife. Just taking a peek at the labels on sweaters in her closet won't help much: Different manufacturers have different ideas on what constitutes a size L or a size 8. That's such a big problem, in fact, that many people are afraid to order size-oriented gifts, says Ernesto Aguirre, CEO of TheRightSize.

      Aguirre's company performs another feat of normalization and integration: Instead of making connections between typed-in words, however, the company translates sizes. If the shopper's wife endures a somewhat lengthy registration process, TheRightSize's database will "know" the size of the Liz Clairborne sweater she already has and, therefore, the size she would need in another brand.

      JCPenney.com signed up in August as one of the first retail sites to give the service a try, although by November the company had not yet launched it. But even if the matches made by TheRightSize or competitor EZsize.com aren't perfect, shoppers at least would have a fighting chance to avoid having to return an ill-fitting item.

Where is it?

Let's say the sweater-shopping husband has used these tools to identify a sweater that's both the right color and the right size for his wife-but drives to the store and finds that the item is not in stock. Retailers including Circuit City, Home Depot, bebe stores, and Finish Line are considering Web-based antidotes to end that problem in their respective markets.

      Finish Line, a retailer of sports apparel, was expecting to test just such a technology over the holidays at 50 of its locations, says Kent Zimmerman, the company's director of ecommerce. Using middleware from San Francisco's Found, the test was expected to give Finish Line near-real-time inventory information for each location that it could share with customers.

      Retailers who use such systems will learn more about anticipating demand and managing inventory levels, says Greg Girard, vice president of retail applications for AMR Research. In the brick-and-mortar world, consumers who don't find what they want often leave without giving the retailer a clue about why. Online, however, a retailer can track the queries made by consumers. If a chain notices that 50 online shoppers have searched in vain for something at its Jacksonville, Fla., store, it will know to send more stock there.

      Of course, normalization systems can't help until all the back-end data has been integrated. Fortunately, the principle behind building a real-time, in-store inventory system is simple. Many chain stores already upload sales and shipment information to headquarters each evening, and a central inventory system determines exactly how much merchandise is on hand for the next day's business.

      But Found's middleware updates this end-of-day snapshot throughout the day. By keeping all the inventory it tracks at different chains in one huge database, Found can build a master index of product availability. So if Nike tapped the Found database (or that of a competing service planned by HybriNet) it could tell its Website visitors which retailers have their favorite sneaker in stock, says Found CEO Rich Lawson. Similarly, a mall's Website could tell visitors which of its various tenants have a given item in stock.

      Ultimately, the more that data from retailers, manufacturers, malls, portals, and technology vendors can be integrated, the happier consumers will be. Making information available from all directions helps ensure that shoppers will get the data they need.

      Forrester's Allen imagines normalization going a step further. Our hypothetical sweater shopper could simply list his criteria with a shopping agent or bot. The bot could then find a few purple sweaters, check them against his wife's size, and find where they are in stock at a price he is willing to pay. The bot could present the options by email or to the shopper's interactive television, so he can purchase the gift without having to miss a single play of the football game he's watching.

      Now that would be successful shopping.




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