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Businesses selling clothing and other fashion items face obstacles in trying to forecast how much product to order: tastes and styles change quickly, while manufacturing clothing takes a significant amount of time. Researchers Youran Fu and Marshall Fisher have found that combining sellers' own data with information gathered from social media can dramatically improve the accuracy of such forecasts by 24 to 57 percent in the cases they directly studied. Better predictions mean demand is easier to meet without retailers becoming overstocked.

Becoming overstocked is the main preoccupation of sellers trying to forecast demand for fashion items.

Social media is revolutionizing how both sellers and researchers view the fashion industry.

Using multiple data sources can enhance the ability of sellers in the fashion industry to anticipate demand.

Retailers can use their own data to accurately predict how tastes and styles are evolving.