The e-retailer spends at least 50% of its monthly display ad budget on the highly targeted, data-driven—and often cheap—ad placements using programmatic platforms.
A look over the horizon at new e-retailing technology and techniques.
Smart marketers have always known that the customer is king, but a look at what’s on the drawing board and entering the marketplace at technology developers suggests online retailers will soon have even more new ways to give shoppers royal treatment.
The theme of shopper empowerment characterizes much of what’s currently on the minds and in the labs of developers and the online marketers they target. Providers are reworking technology initially deployed in other sectors or available only to site operators on the backend and rolling it out directly to the consumer web interface. They’re figuring out new ways to segment online content according to consumers’ preferences and deliver it in richer formats. It’s all geared toward an improved shopping experience-and improved sales.
In a scan of new online merchandising and marketing technology developments both within the company and across the marketplace, “It comes back to the convergence of the channels and efforts to make it easier for consumers,” says Kim Weller, principal consultant, user experience, at technology consulting firm Molecular Inc. “Some of the tools that typically have been reserved for staff, such as the ability to find products across different stores, are being made available to consumers.”
Molecular already has helped Talbots Inc. roll out such capacity to its online customers. Style Search, a feature implemented on Talbots.com last year, which lets online shoppers locate an item of apparel in a Talbots store and reserve it online for a store visit, is based on inventory data previously available only to store associates at the POS terminal.
Even that capability, which only a short time ago was on the cutting edge of technology implementations, may soon be trumped, says Don Cosseboom, director of research and development at Molecular. He sees a day in the not-distant future when the web interface will put at online shoppers’ fingertips the ability to determine where in the store an item is located. That could allow online consumers to establish not only whether an item is in their local store but where it’s actually located within the store, before they leave home to pick it up.
Cosseboom explains how such an application might work. “Most big box bookstores, for example, have consistent layouts, according to which version of the store the company is running in any location. So if a shopper is looking for the French Laundry cookbook, the system would know that in this bookstore, the cookbook section is located in this area,“ he says. If that location capacity exists within a store’s back-end system, it can be put out on the web interface, he adds.
Weller says this type of web-to-store application could find use in home improvement stores, mega bookstores, consumer electronics stores, or any large store where shoppers must spend time searching the aisles to find what they are looking for. It empowers consumers to get to the products they want more easily by cutting through the double barriers of understanding whether a product is in the store and understanding where in the store the product is shelved, Cosseboom says, adding that he would not be surprised if this type of application rolled out in retail within a year.
Price comparison-by phone
Molecular also foresees a growing number of new shopping applications for web-enabled wireless technology: for instance, applications that would allow a shopper to compare via wireless device prices on the same product at local consumer electronics stores without actually having to go to or phone the store.
Already, says Weller, Amazon’s Japan operation has gone a step beyond this concept with an application that allows customers to use camera phones to take a picture of a book’s bar code, submit it wirelessly to Amazon, and receive a text message on Amazon’s price on the book in return. In the U.S., software developer ScanBuy has launched a retail application, ScanZoom, designed for incorporation into camera phones, that allows consumers with an equipped phone to point it at a barcode and immediately access existing content related to that bar code.
“It’s something camera phones and bar codes were never intended to be used for, but they are tying these different technologies together,” Weller says. In addition to a convergence of channels, new shopping applications such as these preview a future in which technologies themselves converge. “Examples like this rely on the phone’s wireless network to connect to the Internet. In the future, your cell phone will probably use a wi-fi network as a way to connect. So the whole idea of wireless being carrier-level versus Internet will be even fuzzier than it is today,” says Cosseboom.
“Fuzzy” is a good thing at Transparensee Systems Inc., developer of product search technology. That might seem contradictory for search. But Bruce Colwin, vice president of business development, believes search could be a better experience for consumers-and capture more online conversions at merchants-if it were less sharp and a little more fuzzy.
Transparensee has developed technology it says is a next-generation, more user-friendly product search that is an alternative to guided navigation. The technology is applicable to search in any industry sector where the range of attributes attached to a product is so broad and complex that an exact match against all specified preferences is unlikely, according to Colwin.
“Two of the biggest problems in e-commerce search, as seen by the user, are that your search produces no results, in which case you have to keep changing your preferences until you find something, or you broaden your search so much that you get too many results back, with little relevance. These are the problems we’re addressing,” Colwin says.
The so-called “fuzzy” search technology delivers results that not only represent the precise value the searcher has asked for, but also whatever represents the values immediately below or above the searched-for value. On a real estate site search, for example, for a house with a specific number of rooms, square feet, construction type, and multiple other attributes, a precise match might yield no results because no house matches all of what was searched for. That leaves the searcher guessing which values he must change to produce a match. Tranparensee’s tool finds results close to what the searcher has asked for, in addition to any precise matches. The technology makes adjustments concurrently across multiple data fields to deliver results that though technically “fuzzy,” are meaningful to the search.