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Consumers to Return Half of Online Clothing Purchases this Holiday Season
[December 05, 2018]

Consumers to Return Half of Online Clothing Purchases this Holiday Season


SAN MATEO, Calif., Dec. 5, 2018 /PRNewswire/ -- While record-breaking Black Friday and Cyber Monday sales are always a delight to retailers, many quickly begin to feel the pain of returns. This Holiday Season, e-commerce sales reached $14.12 billion, up over 20 percent from last year, according to Adobe Analytics. Clothing sales were $2.78 billion since they comprise 20 percent of total e-commerce sales, reports eMarketer. This means online apparel retailers will only achieve $1.39 billion in total revenue since half of Americans are expecting to return clothes ordered online due to poor fit, according to a new study. Despite technical advancements, the apparel industry has struggled to address this consumer pain point, and as a result, bottom lines continue to suffer greatly.

To better understand the frustrations of online shoppers and their experiences with finding clothes that fit them, BodyBlock AI recently surveyed 1,200 Americans and asked them how often online shoppers ran into issues with clothes fitting poorly, how often they return clothes due to poor fit and how likely they are to return to a brand if the clothes they ordered fit poorly.

To download the full report and infographic see here.

Having the wrong fit has significant consequences for brands, with nearly three-quarters (72 percent) of those surveyed having returned items ordered online that didn't fit, this is a wide reaching issue. In fact, as first-time customers, nearly half of shoppers (45 percent) wouldn't return to a new brand if the clothing they ordered didn't fit, or if they received the wrong size. Customers have caught on to this problem too, as 50 percent of those surveyed are expecting to return clothing ordered online this holiday shopping season.

Unsurprisingly, most people have ordered clothes online and weren't satisfied with how they fit, with 91 percent of those surveyed having ordered clothes online that didn't fit asexpected. This despite of the fact that consumers are actively looking for ways around this issue; 72 percent of shoppers use fit predictors and size charts when ordering clothes online and still over a third (37 percent) regularly buy more than one size of one item, just to be sure they order the right size.



"Brands have been playing a costly guessing game when addressing the sizing and fit of their customers for decades. If apparel companies don't rethink their strategy, they will continue to hemorrhage billions of dollars every year in returns and dissatisfied customers," said Greg Moore, CEO of BodyBlock AI. "By taking a BodyFirst approach, companies can efficiently design for the true shapes of their customers and sell the right trim and size to each customer; resulting in increased consumer confidence, conversions, and reduced returns. BodyBlock AI helps brands create a better customer experience and increase their sustainability quotient."

Solving the fit problem will be highly beneficial for brand loyalty and retaining new and current customers alike. An overwhelming 89 percent of shoppers surveyed were likely (28 percent) to very likely (61 percent) to order more clothes from a brand if the first item they ordered fit well. This would bode well for new and returning customers as 88 percent of those surveyed said they would shop online more if they didn't have to worry about fit. In fact, 17 percent of shoppers surveyed would do all of their clothing shopping online if they didn't have to worry about poor fit, and 40 percent said they would do at least 50 percent more shopping online. If clothing ordered online fit perfectly, 87 percent were very likely (58 percent) to likely (29 percent) to buy more of that same item, or more from that same brand.


Issues with poor fitting clothing was seen for both men and women. Jeans and pants were the most commonly returned apparel item for men and women, though men were also twice as likely to return t-shirts as women. For women, sizing on clothes can often feel random, especially when comparing clothes from brand to brand. Of those surveyed, 84 percent of women felt that sizing was random or arbitrary depending on the brand.

It is clear that consumers enjoy the theoretical ease of buying clothes online, but the fear and hassle of getting clothes that don't fit deters new shoppers, hurts conversion rates and dramatically reduces the retailer's revenue as a result of high return rates. In order to meet their customers' needs and deliver quality experiences that keep customers coming back, apparel brands would be wise to take a data-driven approach to apparel design.

By taking a data-driven approach to apparel fit, brands can begin matching the bodies of their customers to the clothes they make, rather than models and patterns. It's time the apparel industry caught up to the 21st century both in terms of technological innovation and the diversity of human bodies. To do so would improve online conversions, reduce returns, secure more returning customers and create a more sustainable strategy for the modern era.

About BodyBlock AI

BodyBlock AI, a wholly-owned subsidiary of Fit3D, utilizes the world's largest user- and database of 3D body scans to help brands design and distribute clothing to fit their customer segment. BodyBlock AI solves the most challenging component of online clothing shopping – poor fit – through measurement prediction and fit recommendation technology. The data-driven approach to apparel fit is a proven method that has resulted in improved conversions, reduced returns, increased sustainability and overall cost savings for online and in-person apparel brands. To learn more about BodyBlock AI, visit https://bodyblock.ai/ or follow us on @BodyBlock_AI.

Media Contact:
Madeline Mains
FortyThree, Inc.
831.401.3175
bodyblock@43pr.com

 

Cision View original content:http://www.prnewswire.com/news-releases/consumers-to-return-half-of-online-clothing-purchases-this-holiday-season-300760466.html

SOURCE BodyBlock AI


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