‘Accepting rocketing returns as “cost of doing business” is limp admission of defeat’

Rocketing returns rates are symptomatic of the shopping experience shifting from the changing room to the bedroom, representing a persistently painful sore for apparel retailers.

While acutely aware of the issue, they have yet to truly tackle the deeper systemic challenges lying beneath the startling figures – returns rates regularly settle in the 40% to 50% range in fast fashion. Party and occasionwear can hit 60% or more.

The freedom afforded by ecommerce to order from home in multiple sizes, colours and fits to find the right look has left retailers footing the bill for servicing the return and resale of unwanted or damaged items – to the tune of £6bn in the UK in 2022, according to GlobalData. ­

“Making customers pay for your reluctance to tackle returns is not a good look and many will let you know by taking their business elsewhere”

Simply accepting and annually forecasting for this phenomenon as ‘the cost of doing business’ is a limp admission of defeat. At the other end of the spectrum, punishing all customers via blunt instruments such as blanket charges for returns, or instigating changes such as drastically reduced returns windows, is largely unproven and doesn’t get to the heart of the matter.

The reward for successfully addressing the issue is huge: a 5% returns rate improvement could translate into an increase of approximately £14m in EBITDA for a £1bn ecommerce retailer with an average 45% returns rate.

However, driving returns rates down is a complex, multidimensional challenge, as there are many reasons for returns. Some are legitimate cases of flawed goods, while fit, style and quality feature regularly. Other contributing trends include ‘bracketing’ (buying multiple styles and sizes), ‘wardrobing’ (wearing and returning) or ‘staging’ (purchasing to showcase on social media and then returning).

There are tactical point solutions, such as virtual mirrors and fitting apps that measure and interpret body shape based on algorithms trained on data sets. Returns portals also provide some insights via reason codes but suffer from limited options and customers simply clicking the first available option to get through the process faster, thus polluting the data.

The most sophisticated response lies much deeper in the data and the good news is that you probably already have the raw ingredients. See which of these questions can answer:

• What are the item level drivers of returns – size, quality or something else?
• Who are the serial returners in your customer base?
• Are certain products more prone to particular channels of return (for instance, store vs online)?
• Are specific suppliers presenting issues and does that vary by category or location?

You won’t be surprised to find yourself searching in disparate digital locations for the answers or speaking to multiple departments.

For a tougher challenge, how about these questions?

• When should I push a return to store (and what are the economics for different channels)?
• Should I be consolidating returns or finding alternatives (such as local jobbers)?
• Should I charge for returns (for instance, by order, or waive for ‘premium’ customers) and what might the impact be on lifetime value?
• What thresholds should be set for free returns?
• How often do I double- or triple-handle a product that ultimately never gets sold?
• What is the true end-to-end cost of a return and does it vary by category?

These are meaty operational questions that cut to the core of the challenge and require a deep understanding of the cross-functional data that supports the returns journey. The solution we use with our clients drives real-time decision making and is focused on the bottom line.

The richness of the data that can be uncovered around returns and distilled into new operating practices makes a business more intelligent, not just transactionally efficient.

Ignoring this data is unforgivable, given the size of the problem that it could solve. Making customers pay for your reluctance to tackle it is not a good look either and many will let you know by taking their business elsewhere. But wouldn’t you like to know how many of them you should happily be waving goodbye to?

A personalised approach will win out in the end – for business and consumer – but that relationship can only be deepened through data. In the complex world of returns, all customers are not equal and nor should they be treated that way.