Groupon expects to roll out a revamped mobile app.
By borrowing the terms consumers use in reviews e-retailers enhance their site search and navigation.
Shoe maker Clarks may not have thought to tout its slip-on Book Pump as the perfect date night shoe, but that's how some consumers describe it in their product reviews. And recognizing that suggests other shoppers will likely search for "date night shoes," e-retailer OnlineShoes.com has added that as one of the ways visitors can sort results in product categories like men's and women's shoes.
"We realize the limitations of our taxonomy of our products and our tagging of products," says Jimmy Healey, OnlineShoes.com's senior manager of social commerce. "We wouldn't think to describe or tag something as a date night shoe, but our customers do."
OnlineShoes.com is one of a growing number of retailers whose site navigation and search features speak the language of consumers by drawing on the terms consumers themselves use in product reviews and when categorizing products they've bought.
That's a sensible strategy because consumers search using more emotional and descriptive terms than manufacturers and retailers generally employ to describe their products, says Susan Aldrich, senior vice president of research and consulting firm Patricia Seybold Group. "From a shopper's point of view, the things they are interested in are things manufacturers have a hard time adding to their product descriptions," Aldrich says.
Making use of the wealth of consumer-generated content in this way is getting easier as vendors whose systems at one time operated independently—notably providers of site search technology and ratings and reviews systems—integrate their products to help shoppers to find products using everyday language. In the latest extension of this strategy, some e-retailers are starting to enrich site search and navigation with yet another rich source of consumer insight, content from social networks like Facebook, Twitter and YouTube.
Healey of OnlineShoes.com calls this approach "social navigation," and the e-retailer implemented it four years ago at the same time as it added customer ratings and reviews, working with vendor PowerReviews Inc. PowerReviews generates an XML-based report every 24 hours that contains the latest consumer review data, which is then fed to OnlineShoes.com's site search system. PowerReviews charges a minimal processing fee to produce and distribute the XML data feed, the vendor says. The e-retailer then uses the data extracted from customer reviews, including tags consumers enter using free text and from tags OnlineShoes.com suggests.
When the e-retailer sees several consumers typing in a term to describe a product that's not one of the listed options, it adds that to the list of terms other shoppers can suggest. The retailer added the term "durable" as an option for some products after seeing several consumers use that term on their own. And it's turned out to be one many other shoppers use. Healey says that of the 300 search parameters available in OnlineShoes.com's left-hand navigation, "durable" was among the top 15 in terms of driving click-throughs and conversions in 2010.
OnlineShoes.com uses the terms consumers select, or type in on their own, to populate "favorite uses" and "why people like it" filters that appear in the left column on major category pages, such as men's, women's or kids' shoes. There is room for only seven terms to appear in the section, and the terms rotate based on popularity and season. For example, in the "favorite uses" filter, "snow" may appear as a term in the winter and "beach" in the summer. The filters appear next to the retailer's own sorting options, which include shoe size, width and color.
Healey says social navigation search is getting better as consumers add more reviews. The e-retailer also draws on the consumer-generated content to market more effectively. For example, on big summer holidays associated with barbecues like Memorial Day and the Fourth of July, OnlineShoes.com will send an e-mail to customers promoting the shoes tagged most frequently as BBQ under the "favorite uses" section.
"It would be hard for our merchandising team to know what consumers consider a good barbecue shoe, but this way we just look at the data and know what to feature," he says, noting that the merchandising team would never have thought to use BBQ as a descriptor. Other consumer-submitted terms for favorite uses include "church" and "going out."
At Boden.co.uk, "party dress" is a term consumers use in their reviews of certain fashion items, and the British apparel e-retailer makes sure a consumer searching for "party dress" sees search results that includes items so described. As a result, a keyword search for "party dress" at Boden.co.uk returns results for 10 dresses that consumers, in their reviews, indicated are good for special occasions.
"We use consumer review data as a way to provide guidance for other people to help them in their shopping choices," says Mark Batty, e-commerce manager at Boden.
Batty says Boden began incorporating consumer review data into site search last year. He says Boden approached its site search provider, SLI Systems Inc., and its former consumer review vendor, Bazaarvoice (it now uses Shopzilla Product Reviews, which is affiliated with PowerReviews), about getting the two systems to sync. "We figured that since we have this data, why not use it?" he says. "It seemed like a logical step to incorporate the reviews into search results." SLI now has a standard integration with Bazaarvoice and PowerReviews that allows sorting by consumer review data, says SLI CEO Shaun Ryan.
Boden also feeds data about reviewers into navigation so consumers can sort search results according to the characteristics of the consumers who reviewed those products. For example, a keyword search for "knee length dresses" returns 24 results. Consumers can then sort those results by the age, body shape, size and height of the reviewers that purchased those items and volunteered that data in their reviewer profiles. Batty says this can help a consumer, say a petite, hourglass-shaped woman between the ages of 35-44, find the products that are most suited to her based on the experience of others who have purchased those products and possess similar traits.