Big data has certainly changed retail optimization and the way apparel companies plan and market their products, but how they follow through with that information can spell the difference between success and failure.
As Edward Hertzman, founder and president of Sourcing Journal, asked experts on the panel “Big Data and Manufacturing–How to Effectively Capitalize on the Next Big Trend,” Tuesday at Texworld USA, “Is there inherent risk to relying too much on data when it comes to…making decisions on your product?”
The risk, Trendalytics founder and CEO Kathy Leake said, stems from “relying on one source of data,” such as retail’s over-reliance on historical data. That can be “incredibly dangerous,” especially when there are so many other data sources available to help drive business decisions, she added.
There is by its nature inherent risk in launching new products, which deliver 50 percent to 80 percent failure rates, Gretchen Jezerc, senior vice president of marketing at First Insight Inc., said. Rue 21, a First Insight client, saw 93 percent of new products fail when tested in stores, she said.
“The good news is that there are predictive analytics tools for retail available leveraging data and a variety of sources of data and tools to be able to mitigate that risk,” Jezerc said. “First Insight, for example, has been able to improve speed to market and increase new product success rates by 30 percent to 80 percent.”
First Insight recently signed an agreement with Li & Fung to integrate First Insight’s Voice of the Customer retail predictive analytics with Li & Fung’s digital product development solution to help brands and retailers confidently make buying decisions, minimize markdowns and end the season with less excess stock.
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