Fashion Metric has released a solution designed to address the potential inaccuracies and reliability issues that come with online sizing. The Virtual Sizer platform deploys artificial intelligence and machine learning techniques to:
Predict more than 50 body measurements based on data points consumers are likely to know by heart (e.g. height, weight, bra size, shoe size), rather than requiring users to measure their waist, inseam or neck with a tape measure;
Integrate with retailers’ online product catalog to more accurately match customer body types with specific pieces of clothing; and
Aggregate customer sizing data for retailers and manufacturers, providing insights for improving inventory management, merchandising, and the pattern-making and design processes for future products.
The solution’s filtering capabilities fit for mobile shoppers as well; rather than thumbing through dozens of garments, a mobile site could provide two or three items that will fit the shopper’s individual body shape.
Virtual Sizer not only integrates with a range of retailers’ inventories, but as a plug-in API it can be deployed at a variety of points in the shopping journey. For example, some shoppers will order the same item in two different sizes, planning ahead of time to return the non-fitting garment after they receive their order.