Machine Learning Lets Adidas Customers Contribute To Product Design
Through the analysis of millions of consumer-created prototypes, the company can better anticipate future demand by allowing customers an active role in product design, as opposed to simply collecting data on shoppers' behavior
In order to stay ahead of the curve in the realm of consumer trends, athletic brand Adidas is infusing its supply chain with customer input through machine learning. The change breaks the company out of the model it’s been using, and is an initiative of the brand’s Future division, which focuses solely on innovative products and services.
Last year, the “Storefactory“—which let consumers create their own customized, on-demand sweaters—debuted in Berlin, Germany, and the Speedfactory for footwear followed. However, along with real-time product creation capability came an increased need for anticipation of the materials necessary, as well as their location within the supply chain. This was especially important as Adidas geared up to open the U.S. outpost of the Speedfactory in Atlanta this past April.
By utilizing machine learning, the brand is now able to assess millions of consumer-created designs to determine general trends, and use that information to more intelligently shape the entire design process. Adidas’ endeavor also marks a creative and less invasive way to integrate customer needs and desire into products, allowing customers an active role in designing goods rather than simply using data collected on consumers’ preferences and behavior.