IBM uses social media to predict market trends

The topic of women’s heel height may seem a far cry from debates over big data, but they do have something in common. IBM Corp. has been demonstrating a talent for using big data, specifically social media analytics, to predict trends across industries. As a demonstration of this analysis technique, Armonk, New York-based IBM has used a collection of big data from social media to predict an incoming decline in heel height.

In the press release accompanying the study, Dr. Trevor Davis, a consumer products expert with IBM Global Business Services said that heel height usually increases in the case of an economic downturn. “This time (however), something different is happening. Perhaps a mood of long-term austerity is evolving among consumers sparking a desire to reduce ostentation in everyday settings,” he said.

The full study uses the history of cultural shifts and their relation to women’s fashion, while incorporating a recent collection of more than 10,000 social media instances mentioning women’s footwear. It was parsed using algorithms to determine which posts were the most influential and used that to hypothesize the conclusion.

Independent technology analyst Carmi Levy saw this study as a smart move for IBM. “I’m surprised more companies haven’t jumped on the social media bandwagon. It’s ripe for the picking,” he said. “All this unstructured data is social media intelligence.”

Levy said that it’s natural to turn to social media to predict trends. “If you’re trying to understand consumer behaviour, you have to go where consumers are,” he said. And where they are, is social media like Facebook and Twitter. “If you study their behaviour in those new media channels, you can learn a heck of a lot at what they want and what they’re getting.”

Not only that, he thought it was telling that the data that IBM collected actually spoke against the standard trend. This might lend it more credence with skeptics, if the predictions stand. “It’s very easy to make predictions that are consistent with consumer trends,” Levy said. “Analytics don’t merely confirm what you know, it points you in new directions.”

Rod Smith, vice president of Internet emerging technologies, at IBM, said the service already works well focusing on a few social networks, but there is room to include more. “Twitter and Facebook are the two biggest places to look for this information right no,w but businesses want to be flexible, so if Tumblr starts to be a good source of information, or Quora, then you adapt,” he said. “IBM’s Big Insights product can enable ways to hook connectors to that data.”
— With files from Brian Jackson

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