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Facebook Users Hit 'like,' Stores Jump Into Action

The company, which has more than 9 million "likes" on Facebook, followed up with another poll in July on whether it should carry a "Kensie" brand dress in a bird or floral print. About 4,000 people issued their verdicts within 48 hours, and the department store plans to carry the floral print this February.

Rather than simply using social media to tout promotions and new products, companies are just now realizing the value of making customers feel as though they're part of the decision making process, said Jennifer Kasper, who heads digital media at Macy's. In addition to making customers feel like insiders, she said it helps businesses better tailor their offers as well.

Matt Cronin, a founding partner of Web Liquid Group, a digital marketing agency, agreed that companies are still in the early stages of figuring out how to put their social media profiles to use. Until now, he noted that social media strategies have primarily been about capturing as many followers or fans as possible without really knowing where to go from there.

One hurdle for major retailers is that it's difficult to take the information they learn online and put it to use while the trends are still relevant, said Nicolas Franchet, head of retail e-commerce at Facebook.

That's one of the trickier aspects of Wal-Mart Store Inc.'s new "Toyland Tuesday" contest, which lets fans vote on which of two toys will be discounted on the following Tuesday. Once a winner is declared on Thursday, the retailer acts quickly to inform its 4,000 stores of how to adjust pricing and displays, says Wanda Young, senior director of social media for Wal-Mart, which has more than 25 million likes on Facebook.

Although it's the first time Wal-Mart is letting shoppers have a direct say in what merchandise gets discounted, the retailer is learning to use social media in more discreet ways as well. Last year, Wal-Mart, based in Bentonville, Ark., acquired an analytics company called Kosmix that monitors online chatter to try and predict what products might suddenly become popular.

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