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How analytics and market research could predict the future of fashion

DECEMBER 5, 2011 – As analytical technology continues to develop, clothing designers and advertisers may be able to begin conducting market research to foresee the next big fashion trend, Robert Mitchell suggests in a column for Computerworld.

With the use of predictive analytics, those in the fashion industry may be able to assess how historical trends influence consumers’ clothing choices, thus helping to determine whether a certain style will be a hit or miss after it leaves the runway. While it can’t give much insight when it comes to a truly unique new idea, the tool could be useful when trying to draft a strategy for distribution or production.

Additionally, some clothing brands have enough sway to determine what the next fashion will be by practically telling people that they want the item.

There are some limitations, however, as Leslie Ghize told Mitchell.

“Technology never captures free will. People buy things for reasons that never really can be quantified,” she claims. “A lot of people don’t know what they want until you show it to them.”

The better application of analytics, Mitchell concludes, could be to include the findings as part of a bigger argument to try something completely different.

“The application of analytics to accurately predict the demand and optimized distribution mix for more established fashion items may free up designers to take those risks,” he argues.

Linda Rosencrance pens a response to Mitchell on the SmartData Collective, noting that advertisers may also be able to dictate how consumers respond to a recent fashion offering with the use of social media, well-placed display ads and other influential content.

But she also holds out hope that fashion designers will change their thinking when they go to their sketchpads – rather than creating an item and then trying to figure out how to sell it to consumers, they may start asking what their customers actually want.

Rosencrance adds that data has to be accurate and in context if it’s to be useful. She says it has to be “clearly represented so users can navigate it, talk about it with colleagues and make informed business decisions” quickly.