Europe HQ: London
London, WC2R 1DA
True Fit India
No.306, A-Wing, Boomerang,
Chandivali Farm Road, Chandivali,
Mumbai, Maharashtra, India, 400072
Here we're diving deeper into the ways that people are shopping for clothes online. As we established in previous “State of Returns” posts, customers returning purchases is inevitable – though not always a bad thing. And of course, there is enormous potential for growth in online shopping for apparel and footwear if retailers can help shoppers switch their focus to finding more styles they’ll love with confidence in fit on their side.
Say Hello to Sara
In an effort to best understand how to leverage developing consumer behaviors in this malleable marketplace, we’re taking a deep dive into the three types of returners: those who sample by Size, Style and Color. Let’s start with our costliest customer: the Size Sampler – we’ll call her Sara. Sara is in the practice of buying the same article of clothing in two – or even three – sizes while shopping online. Since sizing varies widely across brands and even within one label, she’s perpetually unsure of what will fit, and doesn’t want to face disappointment when a style is a touch too small or doesn’t work with her shape as well as she’d like it to. Because she’s buying with the preconception of failure of at least one of the sizes in her cart, it’s guaranteed that Sara will return 50–66% of the purchases in her order. As a retailer, this consumer behavior costs money in admin, shipping and processing.
Recreating the Fitting Room, in Real Time
One of True Fit’s top retailers has learned to preempt and deter this costly consumer behavior by implementing an automated system that interfaces with shoppers like Sara when they add multiple sizes of one style to their carts. See below for a pop-up that helps reel in the size shopper:
Encouraging Sara to take advantage of millions of fit-centric data points that will help her circumvent the inconvenient process of size sampling, she can find not only a single size of a garment that will best fit her, she may also be encouraged to find other styles with a high fit rating designed to work with her body shape – which is much more nuanced and individual-centric than today’s gamut of arbitrary sizing.
Recognizing consumer behavior, like Sara's, allows retailers an opportunity to provide shoppers with a more “measured” approach to selecting styles in sizes that will fit the first time by mitigating size sampling – and in turn, save money on returns. In fact, retailers can lower fit-related returns some 35% by implementing fit data tools like True Fit.
To learn more about return rates that impact the bottom line and how to lower fit-related returns by 35%, check out this special report.
SHARE THIS ON: