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Reducing Returns: the fashion challenge

Ecommerce has revolutionised the retail industry, more than we ever could have imagined. Yet with this success we have seen a whole new set of challenges, particularly in the fashion industry, where returns can represent up to 40% of online sales. A significant overhead from shipping costs, management of returns and stock write-offs, retailers are continually searching for ways in which to reduce returns rates. But are they looking in the wrong places?

To really get to grips with the returns challenge, we need to understand why customers return goods. This can largely be distilled to three key reasons

  • Fit
  • Expectation
  • Fault


The third point is largely down to quality control and generally falls outside of the ecommerce / marketing teams, but the first and second offer plenty of opportunity to reduce return rates.

Setting accurate expectations is a challenge that touches almost every online retailer. When you cannot touch, feel, smell or try a product, how do you really know what it’s like? Your expectation is often set by the retailer’s description, product imagery & previous customer reviews, and in many cases, these may not be wholly accurate. The product copy may have been written by someone that has never seen the product and the images may not allow you to really get up close with the product to see the stitching detail, the fabric texture or the cut of the clothing. If retailers do not give customers the chance to make an informed decision, it is no surprise that the gap between expectation and reality is contributing to high returns rates. Surfacing customer review content, ensuring descriptions are truly accurate and investing in great quality high resolution product photography all help to ensure a customer knows what they will arrive on their doorstep. 

A more complex challenge is that of fit. When buying on the high street, a customer may try on many items before making a purchase decision. Online, they have merely the data in front of them to go by. Technologists and retailers alike have been throwing resources at the issue, with mixed success so far. But out of the chaos, a handful of solutions are beginning to look promising.

  • Metail
    First seen in mainstream clothing retail when Tesco launched a trial of the Metail fitting room on Facebook a few years ago, Metail allows customers to enter their vitals, producing a realistically shaped model upon which to try clothes and outfits. Metail also works with Warehouse, Dafiti, isme and Zalando.

  • Fits.me
    Similarly to Metail, Fits.me provides a virtual fitting room, making intelligent suggestions on the size of garment that will provided the best fit based on the customer’s measurements. It’s seen uptake from some well-known brands including Charles Tyrwhitt, Hugo Boss, Henry Lloyd and Muubaa.

  • True Fit
    Taking a slightly different approach, True Fit boasts more than 1000 retail clients, and uses a quick to complete True Fit profile of the shoppers’ measurements, making recommendations on size and fit based upon past data from the individual shopper, and data from all True Fit users and brands. Claiming to get smarter the more it is used, True Fit can be seen on sites such as Nordstrom, House of Fraser, Guess and Arc’teryx.

Where almost all of these solutions fall short is uptake. They have so far failed to get past the most engaged users of a brand’s site, and reach the everyday customer. In order to use any of these services, a user is required to take personal measurements and input them into the site in order to receive recommendations. If, like me, you do a fair amount of your browsing on-the-go, I think it’s unlikely that you are going to whip out a tape measure and start jotting down your particulars whilst on the train, or on lunch break in the office.

True Fit has tried to tackle the adoption challenge by creating a single database, where users only need upload their details once across all sites that use True Fit. It has made the upload process as simple as possible and claims to allow customers to ‘get fitted in 60 seconds’. I can see this having a big impact on adoption, but it will rely on a leap of faith from a large proportion of retailers before we see these services truly becoming mainstream.

However, I don’t think it will be long before we see one of the big platforms, such as Google or Facebook, make a play in this arena, whether this will be through acquisition or as an aggregator of the data remains to be seen.

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