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Consumer Fit Uncertainty Costs Retailers—How Data-Driven Sizing Can Help

With a greater portion of fashion sales migrating online, retailers are facing a challenge in getting consumers to confidently choose the right size without the benefit of a fitting room to see how a garment will fall on them. As the typical size chart proves insufficient for e-commerce, a number of companies are taking a more tailored approach to fit to help customers make more informed decisions based on their individual preferences.

Sizing indecision is costing retailers. When buying fashion online, consumers who are unsure when it comes to sizing might abandon a purchase.

“All of that marketing, all the promotion, all the website design that went into guiding them to find that [item] can be lost immediately if they’re really nervous about whether that style’s going to fit and flatter them,” Amory Wakefield, vice president of product at personalization platform True Fit, said. “You’re spending all of this energy trying to get them down to that last moment. To have that abandoned at the very end because of uncertainty about fit is a real lost opportunity and lost investment.”

Aside from lost sales, retailers are also facing a mountain of returns tied to size issues. Consumers that do make a purchase may choose to buy multiple sizes in the same item with plans to return what doesn’t work. Not all items that are sent back are returned because of fit, but a recent study from Narvar found that size and fit were two of the top three reasons that e-commerce fashion purchases get sent back to a retailer.

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While more fashion returns happen online than in-store, consumer size uncertainty also means that brick-and-mortar shoppers might bring more merchandise with them into the fitting room, potentially damaging items before they are able to be sold.

Beyond the economic costs of returns, there is an environmental impact tied to shipping. “We see now that brands are becoming more concerned about their practices and how they can be more sustainable as a brand,” said Daina Burnes, co-founder and CEO of technology company Bold Metrics. “A lot of the sustainability conversation has been centered around sourcing of materials and inventory management, but I think that there’s some low-hanging fruit when it relates to returns.”

Solving retail’s fit-based return problem is complex.

Fit is highly subjective, and goes beyond matching a consumer’s body measurements to a size chart. One customer might want to wear clothing that is more fitted while another favors a more oversized look. The right fit for a particular garment is also dependent on the use. For instance, a consumer might want a stretchy running shirt to fit close to the body. Taking the idea that fit is a personal preference for what consumers find flattering on themselves, technology companies are creating ways for shoppers to more specifically pinpoint what will work for them.

Part of the issue surrounding fit and sizing is that consumers either don’t know their measurements or inaccurately measure themselves.

Three-dimensional body platform Meepl has consumers take images of themselves from the front and the side, which can then glean about 200 different measurements such as inseam and sleeve length from these two photos. One of the company’s offerings is a virtual dressing room that enables consumers to try out clothing on an avatar with their body shape.

Offering its own answer to the measurement problem, app developer MySize replaces the measuring tape with a mobile device, using the phone’s motion sensors to determine a user’s size. “You, the consumer, actually measured yourself, so your confidence level goes up because you feel…it is the most accurate measurement,” MySize, Inc. CEO Ronen Luzon said.

Other solutions favor questionnaires over physical measurements or scans. Bold Metrics creates a profile of about 50 of a consumer’s measurements through artificial intelligence by asking them questions that they can reliably answer, such as their height, weight, age, jean size and bra size. Combined with garment specifications, Bold Metrics can then tell a shopper how something they are looking at will fit them.

True Fit asks questions such as what sizes a consumer loves to wear in a particular brand and then blends it with fit data on garments or footwear from brands to deliver sizing suggestions through machine learning and algorithms. The solution also learns about consumers over time.

“We are trying to model how users like to wear their clothes, not just how their body measurements would fit into that size chart,” Wakefield said.

These technology companies are reaching the consumer through retail partners, with in-store or online integrations. For the brands that partner with them, there is also a significant opportunity to gain insights about their actual consumers’ body types or fit and style preferences. This includes learning about what buying behavior leads to returns. Fashion companies’ development of sizing specifications has traditionally been based on fit models or dress forms, partly because they lacked a scalable option to capture this type of consumer size data.

“Right now, brands are essentially arriving at their standardized sizes based on a lot of assumptions with almost no data going into it,” Bold Metrics’ Burnes said.

As more of the design process is done in 3D, consumer profiles can also be used to build avatars or virtual fit models, taking this size data upstream in the supply chain. Measurement information can also be used to remotely facilitate made-to-measure orders.

With the added knowledge about customers’ individual body shapes and sizes, experts expect the future of sizing to be more data-driven. However, they are skeptical that fashion will broadly embrace an on-demand or completely size-free strategy in the near future. While there are some companies cutting custom patterns or knitting made-to-order clothing, manufacturing constraints currently prevent this production model from reaching a scale to make on-demand clothing affordable for the average consumer.

MySize’s Luzon believes that size charts will become irrelevant because they make the process of finding the right fit more “complicated.” Wakefield also sees an opportunity for the size chart to be a better guide to the individual consumer.

“I envision a future where people can describe their own body and the possibility to describe a garment in numbers and algorithms will solve the fitting part automatically; Therefore, it doesn’t really matter if you’re a 4 or a 6 or an 8, or whatever you want to be,” said Ferdinand Metzler, founder and CEO of Fision, the technology company that includes Meepl. “The number that is written in the garment itself will become less important.”