AI Case Study
Adidas learns from its consumers' design creation to better anticipate future demand trends using machine learning
With the use of machine learning, Adidas is able to reduce the typical 18 month timeframe of turning trends into commercially saleable shoes to just 24 hours. It does so by letting consumers design their own shoes in its prototype SpeedFactory, from which then the product ships immediately. As a result, by analysing the co-created designs with machine learning, the company gains insight into future trends and can efficiently anticipate future demand.
Industry
Consumer Goods And Services
Retail General
Project Overview
"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."
Reported Results
Adidas states the following results:
* Enhanced customer experience by delivering consumer-designed products in 24 hours
* Better anticipates future trends demand
Technology
Function
Marketing
Creative And Brand
Background
In 2017, Adidas unveiled the Speedfactory, a manufacturing site for radically accelerated footwear production, utilising athlete data-driven design and open source co-creation.
"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."
Benefits
Data
hundreds of millions of pictures of consumers' designs