Guess is stepping up its digital marketing in hopes of connecting with a younger audience.
The retail chain’s new research lab launches its first Facebook application.
Wal-Mart Stores Inc.’s newly formed research lab @WalMartLabs today launched Shopycat, a Facebook application that, with the permission of a Facebook user, culls the posts and Likes of that consumer’s friends on the social network to present gift recommendations from Walmart.com, as well as from about 20 other online retail sites, including BarnesandNoble.com.
Ravi Raj, vice president of product at @WalMartLabs, says the application aims to combine two key elements of gift giving: knowing the recipient and her likes. “Sometimes it doesn’t always occur to you what someone is interested in, or sometimes you know what they like but not what to buy them,” he says. “Shopycat can make gift-giving less stressful.”
After a consumer grants permission for Shopycat to access her Facebook information, the application shows the consumer what it believes are her closest connections on the social network, such as her husband, brother-in-law or close friends with whom the user regularly interacts on Facebook.
Clicking on one of those connections takes the user to a page that displays that user’s birthday, as well as interests that are both stated via the consumer clicking the Like button as well as inferred based on the sentiment of her posts. For instance, if a consumer posted a status update, “On our way to cheer on the Sox at Fenway,” Shopycat infers that the user is a fan of the Boston Red Sox and presents Red Sox-specific gift ideas, such as a Red Sox-themed Monopoly board game. The application can also determine that a consumer who posts that he hates the Red Sox won’t receive Red Sox-themed gift suggestions, says Anand Rajaraman, senior vice president of Wal-Mart global e-commerce and co-founder of @WalMartLabs.
Shoppers can also use the application’s search box to find gift ideas for someone with a particular interest—even if the potential recipient isn’t on Facebook or doesn’t share enough on the social network for Shopycat to ascertain his interests. For instance, when a shopper types in “Radiohead” he is presented with several of the band’s albums, a book featuring the tablature to play the band’s music, as well as a DVD of the Glastonbury music festival in the United Kingdom, where the band performed.
Not every recommendation will be ideal, but Rajaraman says @WalMartLabs hopes at least one item resonates for each recipient a user clicks on. Showing a diverse array of items is important, because what one consumer considers a great gift may differ from another shopper’s notion, he says.
To present those gift ideas, the site culls through more than 600,000 SKUs from Walmart.com, as well as retailers such as BarnesandNoble.com Inc., No. 41 in the Internet Retailer Top 500 Guide, and ThinkGeek (No. 197).
Offering recommendations for other retailers is about presenting shoppers with the best possible user experience, says Rajaraman. Wal-Mart—for now—is not collecting an affiliate fee or any other cut of revenue generated from consumers’ clicks from the application to the retailers’ sites. “We have a big catalog at Walmart.com, but we realize that sometimes the perfect gift requires consumers to go beyond our catalog,” he says.
The application is built on what Raj calls “social genome” technology that Wal-Mart acquired in April when it bought Kosmix, a Silicon Valley company that specialized in mining data from social networks in order to make targeted offers to consumers. While Wal-Mart has not said what it paid for Kosmix, it’s been widely reported that the purchase price was $300 million.