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Apr 10, 2019 | 2 minute read

How machine learning can solve a $300 billion-dollar problem for apparel companies

written by Kristin Schepici

Machine learning, artificial intelligence (AI) and big data are the latest of a slew of buzzwords taking over the retail industry. While these emerging trends are exciting and offer great opportunities, many brands are still trying to figure out what these can mean for long-term growth and sustainability strategies. One innovator looking to apply value to the latest buzzword of “machine learning” is BodyBlock AI. Deemed the world’s largest 3D body scan database, BodyBlock AI is setting out to help apparel brands predict better fitting clothing.

Using 3D body scans to transform an entire business throughout design, manufacturing, and ecommerce is the latest of emerging disruptive technology. The “fit prediction platform” announced its online size finder widget, BodyBlock Predict. Predict helps apparel retailers recommend better fitting clothes by predicting the physical body measurements and sizes of customers that are shopping online. It uses AI and machine learning to make the recommendations based on body scans versus historical consumer buying behavior. 

Ill-fitting clothes are not just an emotional hurdle for consumers, it’s also a $300 billion-dollar problem for apparel companies. Massively impacting revenue, sustainability and operations. While 3D body scanning isn’t revolutionary, it has been a long allure in apparel and retail. However, the logistics of scanning every consumer simply outweighs the benefits. This predictive solution can now allow the consumer and brand to get the value of a body scan without the operations, logistics and privacy burdens of actually capturing 3D body scans of consumers. And, it allows brands to address the gap between poor-fitting clothes and the actual body sizes and shapes of customers buying clothes online. 

Customers who visit online retail websites using the Predict plugin can select “Find My Fit” when shopping for clothes to begin the fit prediction process. Once selected, they’ll be prompted to enter a few basic inputs (gender, height, age and weight) which will generate a full 3D avatar to help with the fit process. Predict then extrapolates data from over 70 body measurements (ASTM) by comparing the customer’s inputs with its database of 3D body scans and recommends the appropriate product size based to fit as the designer intended. 

Source: BodyBlock AI

Not only would a tool like this help customers feel better about how clothes purchased online will fit their bodies, it also has substantial impacts to businesses with respect to revenues, time to market and sustainability.

BodyBlock AI also offers up analytics to help brands analyze web performance from a new perspective. Once the Predict plugin is installed onto a retailer’s website, brands gain access to powerful insights on the body measurements of the customers visiting online stores. Rather than just seeing the product SKUs, brands can see the height, weight, bust, waist, hip, inseam and other measurements of website visitors. These backend analytics give brands the power to see how clothing matches up with the actual body measurements of customers, whereby bridging the gap between the brand’s target customer segment and the customer’s body shape and measurements.