Artificial Intelligence and Machine Learning are intimidating terms—but they shouldn’t be! Heeluxe is using AI to change the footwear testing landscape and the benefits will soon be realized by all footwear brands. Here’s a sample of how AI is being used to predict shoe fit.
Many footwear innovators had their first introduction to the concept of “Predictive Analytics” during our talk at the 2019 Footwear Innovation Summits in Los Angeles and Donguan. For those that missed, a quick analogy is with crash testing of cars: we used to have to make many big, costly cars to be used in crash testing (similar to how shoe samples are tested for fit) while now we use Predictive Analytics to simulate the car crash testing with a computer, quickly fixing issues and re-testing before a final test is done on a single car. In footwear, we could do a ‘fit and wear’ test simulation with a computer before making our first sample. Car companies are saving time and money with Predictive Analytics, and the footwear industry can, too!
In order to build Predictive Analytics, we need to use AI to process tens of thousands of completed tests (aka “historical data”). Luckily, we have many shoe tests here! Heeluxe is using results from fit testing shoes with sensors to train our AI “model”.. The AI system then can “predict” a fit outcome during shoe design phase by inputting certain features of a shoe (such as last measurements, materials) and features of the wearer (foot measurements, activity).
Sound easy? IT IS!
Sound fast? IT IS!
Sound accurate? IT IS!
Sound valuable? …you tell us!
If you’re excited about using AI and Predictive Analytics for shoe fit, stay tuned. We’ll be sharing updates as we continue to develop these tools in 2020. In the meantime, learn more about Predictive Analytics in Footwear in this short lecture and contact email@example.com with any questions.