Memo: Size Charts, Returns, and EBITDA

Retail is all about EBITDA. The keys to profitability for eCommerce-driven modern brands in the fashion retail space are:

  • develop a sustainable omnichannel strategy
  • master first-party data collection and retargeting
  • minimize returns by providing the best tools for fit-sizing and customer service

For nearly a decade, it seemed as if the digitally-native retail class of internet companies would never realize a string of positive outcomes. The prospects for most digitally-native vertical brands (DNVB) were minimal at best and exit optionality remained slim even when that brand demonstrated a strong “tech-like” growth curve. Cap tables were bloated and war chests were filled. But over time, many investors began to realize that industry shared an unfavorable attribute: there was little to no strategy for long-term sustainability or a potential exit.

Over the course of the pandemic, Vuori became one of the fastest-growing modern brands in the fashion retail space. When the retailer landed its $400 million Softbank investment (at a $4 billion valuation) in 2021, I admittedly didn’t understand the buzz. Then I bought my first pair of joggers from them around a year later. REI, one of Vuori’s top wholesale partners, made it easy. A section of the store is devoted to the brand and an REI associate is frequently stationed within the shop to answer any questions. I was an immediate fan, shifting spend from Lululemon to the slightly more affordable (and better constructed) DTC brand. Their 2021 press release:

With a strong ecommerce business, thriving brick and mortar stores, and a network of best-in-class wholesale partners, Vuori, unlike many other digitally-native brands, has been profitable since 2017.

Vuori is considered one of the top M&A targets in athleisure and rightfully so. Primarily an eCommerce shopper, I would have likely chosen different sizing than I did when introduced to the brand in early 2022 at REI. To account for this common issue, the brand recently partnered with Bold Metrics to encourage first-time buyers to find the right fit for their products. This got me thinking about the chief problems for clothing retailers trying to acquire customers online. The top eight reasons brands fail to convert new customers are:

  • a lack of clear product information and high-quality images
  • complex or confusing navigation
  • slow page loading speeds
  • high or unclear pricing
  • limited payment or shipping options
  • a lack of trust or few credibility signals
  • poor mobile optimization or limited mobile functionality
  • a poor returns policy

How do we minimize returns?

Business of Fashion recently noted an alarming data point in its latest report, The DTC Reckoning is Coming For Fashion: “Profitability in the online DTC channel is suffering, as digital marketing costs grow alongside online return rates — costing brands between $21 and $46 per returned product on average.” It’s an excellent report if you haven’t read it. This excerpt will be on the minds of all DTC fashion retail executives:

In the US, return rates across all sales channels increased to 16.6 percent in 2021 from 10.6 percent the year before, with the average return rate for online orders even higher at 20.8 percent.

Here are the eight ways that I found would be most beneficial for retailers to reduce return rates:

  • at the very minimum, include measurements and size charts on product pages to help customers find the right fit
  • carry a range of sizes to accommodate customers of different body types
  • allow for easy returns and exchanges: make the process clear and easy for customers to initiate a return or exchange if the item doesn’t fit
  • encourage customers to reach out for help: provide a customer service contact for customers to ask any questions they may have about sizing
  • consider offering customized or made-to-measure options for customers who have a hard time finding the right fit
  • use models that are representative of the target audience, so customers can see how the clothes will fit on people with similar body types
  • use of fit technology tools, like virtual try-on, to help customers visualize how the clothes will fit on them

Virtual try-on technology uses artificial intelligence (AI) and computer vision techniques to analyze a customer’s body shape and size and match it with the clothing item being considered. It simulates how the clothing item would fit on the customer’s body by using a 3D model of the customer’s body, created from a single image of the customer or a selection of data points.

I was skeptical when I first tested this.

It can also use machine learning algorithms to automatically adjust the fit of the clothing item to the customer’s body shape and size, taking into account factors such as body measurements, age, and even activity level. This allows customers to see how the clothing item would look on them in a highly realistic way, helping them to make more informed purchase decisions and reducing the chances of returns due to poor fit.

Three of the leading artificial intelligence-enabled sizing tools are True Fit (Lululemon, Todd Snyder, Madewell, Carhartt), Fit:Match (Savage x Fenty, Fabletics),  and Bold Metrics (Canada Goose, UpWest, Burton, Vuori). While both technologies are proprietary, I expect the vast majority of fashion retailers to adopt one of the two services for their product pages. One of the value propositions for Bold Metrics is that it will help a retailer reduce returns and improve conversion rates – both directly and indirectly improving profit margins for retailers.

Sizing technologies like True Fit and Bold have a role in the three-fold approach to profitability for DTC fashion retailers. While it’s not one-size fits all for brands, virtual try-on technology will become a requirement for any brand still relying on sizing charts to communicate fit to an interested customer.

By Web Smith | Edited by Hilary Milnes with art by Alex Remy

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