Fashion brands are increasingly vocal about their commitment to sustainability, proudly unveiling initiatives centered on recycled polyester, reduced water consumption in denim production, and ethically sourced materials. Top brands like Gap Inc. and Marks & Spencer (M&S) have indeed made tangible progress, from increasing their use of organic cotton to M&S' ambitious ‘Plan A’ aimed at carbon neutrality and zero waste. These efforts represent crucial steps towards a more environmentally conscious future for the fashion industry.

The environmental burden of returns

However, a closer examination reveals a significant and often deliberately obscured environmental burden: the escalating issue of product returns. In the growing realm of fashion e-commerce, almost 30-40 per cent of online purchases are routinely sent back by consumers, reveals data aggregated by Shopify and McKinsey. This translates to three or four out of every ten items embarking on an immediate return journey, with the primary culprit being the persistent and pervasive problem of inaccurate and inconsistent sizing.

This constant two-way flow of garments generates a substantial and largely unaccounted-for environmental cost. The additional greenhouse gas emissions from the extra transportation legs, the increased consumption of packaging materials, and the significant labor, water, and energy resources required for processing these unwanted items all contribute to a considerable ecological footprint that remains conspicuously absent from many corporate sustainability reports.

Alarmingly, research indicates that a substantial portion of these returned items, estimated by various sources to be between 25 per cent and even as high as 30 per cent for certain categories, never re-enter the sales cycle, ultimately ending up in landfills or being liquidated at a significant loss.

Table: The vicious cycle of returns

The financial ramifications of this return epidemic are equally profound. For every $1 billion in sales, the average retailer incurs $165 million in merchandise returns (PYMNTS.com). Data from AfterShip further underscores the immense financial burden on apparel brands, estimating the annual cost of returns to be almost $218 billion globally. The operational cost of processing each individual return can range from 20 per cent to 65 per cent of the item's original value, encompassing expenses related to reverse logistics, quality checks, repackaging, potential cleaning or minor repairs, and the often-significant depreciation or loss of resale value.

The journey of a returned sustainable T-shirt

Consider a conscious consumer in Bengaluru who purchases a ‘sustainable’ T-shirt made from organic cotton, attracted by the brand's eco-friendly marketing. However, upon arrival, the sizing is inconsistent with the brand's size chart, resulting in a poor fit. The consumer initiates a return.

This single transaction now involves:

Outbound shipping emissions: The initial carbon footprint of delivering the t-shirt.

Return shipping emissions: The additional carbon footprint of the t-shirt's journey back to the retailer's warehouse.

Packaging waste (double): The impact of original packaging plus any additional packaging used for the return.

Warehouse processing: Labor, energy, and potential water usage for receiving, inspecting, and potentially cleaning the returned item.

Potential disposal emissions: If the T-shirt cannot be resold as new (due to minor damage, being out of season, or exceeding restocking limitations), it may end up in a landfill, contributing to methane emissions and waste accumulation.

Even if the T-shirt is resold, the environmental benefits of the organic cotton are partially negated by the emissions generated from the unnecessary back-and-forth transportation.

The fit and size labyrinth

The primary catalyst for this unsustainable cycle is the issue of inconsistent and unreliable sizing standards within the fashion industry. And the lack of standardized sizing is not just a consumer frustration; it's a significant barrier to sustainability. The seemingly universal size labels ‘S’ ‘M’ ‘L’ or numerical designations – exhibit significant variations not only between different brands but also within the diverse product lines of a single retailer. A size 12 dress from one brand might feel like a size 8 or a size 16 from another. This sizing landscape forces consumers into a trial-and-error approach, often ordering multiple sizes with the explicit intention of returning those that don't fit.

Studies by companies like Body Labs have indicated that poor fit is the primary reason for approximately 60-70 per cent of fashion e-commerce returns. Surveys conducted by Klarna and ZigZag further corroborate this, highlighting the frustration and inconvenience caused by inconsistent sizing. McKinsey data further emphasizes that sizing issues account for the majority (around 70 per cent) of fashion returns.

Limitations of band-aid solutions

Faced with mounting return costs and logistical complexities, some retailers, like Zara and H&M, have begun implementing return fees in certain markets. Zara, for instance, introduced a fee for online returns in the UK in 2022, and H&M followed suit shortly thereafter. While these measures may slightly deter frivolous returns and encourage more considered purchasing, they fundamentally fail to address the core problem of inaccurate sizing.

Indeed, return fees might lead to a marginal decrease in return volumes (early data suggests a potential reduction of 5-10 per cent in some cases), they also risk alienating customers. A significant 54 per cent of shoppers report being unlikely to purchase from a retailer that doesn't offer free returns, highlighting the importance of a seamless and cost-free return experience in online shopping.

Revolutionizing fit and minimizing returns

Fortunately, the rise of sophisticated technology and innovative sizing software offers promising solutions to mitigate the fit problem and drastically reduce return rates in the fashion industry.

• AI-powered size recommendation: These intelligent systems analyze vast amounts of data, including customer measurements (often obtained through questionnaires or past purchase history), body type information, garment specifications, and even customer reviews, to provide personalized size recommendations in real-time. Companies like PRIME AI and Fit Analytics utilize advanced algorithms and machine learning to predict the most accurate size for individual shoppers across different brands and styles.

PRIME AI conducted a study across 14 different fashion brands and found that shoppers who followed the AI-powered size recommendations experienced a 31 per cent lower return rate compared to those who ordered without size advice. Furthermore, retailers using PRIME AI reported a 3-15 per cent increase in conversion rates, indicating that accurate sizing recommendations not only reduce returns but also boost customer confidence and sales.

• Virtual Try-On (VTO) technology: Leveraging augmented reality (AR) and artificial intelligence (AI), VTO allows customers to virtually ‘try on clothing items using their smartphone cameras or webcams. This overlays realistic digital rendering of garments onto the user's image or a 3D avatar, providing a visual representation of how the clothes might look and fit. Companies like Zeekit, Metail, and SHAKU offer sophisticated VTO solutions for e-commerce retailers. Fashion giant ASOS has been actively investing in virtual try-on technologies. While specific return reduction figures are proprietary, industry reports and case studies from VTO providers indicate that retailers implementing virtual try-on have experienced a 20-30 per cent reduction in return rates and a significant increase in conversion rates (up to 30 per cent). By allowing customers to visualize the fit and style of garments on themselves, VTO significantly reduces sizing uncertainty and buyer's remorse.
• 3D Body Scanning and Measurement Solutions: Companies like 3DLOOK are developing mobile body scanning apps that enable customers to obtain accurate body measurements using their smartphone cameras. This data can then be used by retailers to provide highly personalized size recommendations. While widespread adoption is still evolving, pilot programs have shown significant potential in reducing size-related returns, particularly in categories where precise measurements are crucial, such as tailored clothing and swimwear. A retailer specializing in swimwear partnered with a 3D body scanning technology provider. By offering customers the option to get their precise measurements through the app, the retailer saw a reduction in return rates for swimwear below 10 per cent, significantly lower than the industry average of 17-30 per cent for online apparel. This highlights the effectiveness of accurate body data in minimizing fit-related issues.
• AI-Enhanced Product Descriptions and Fit Reviews: Artificial intelligence can also be used to analyze customer reviews and product descriptions to extract valuable insights about fit. This information can then be used to create more accurate and detailed size guides, highlight whether items tend to run large or small, and provide data-driven fit recommendations. Amazon Fashion, for example, utilizes AI to generate "Fit Review Highlights," summarizing relevant customer feedback on sizing accuracy to help new shoppers make more informed decisions.

Integrating technology into the sustainability equation

The fashion industry's commendable efforts in adopting sustainable materials and reducing production waste will ultimately be undermined if the significant environmental and financial costs associated with excessive returns are not addressed. True sustainability necessitates a holistic approach that integrates the entire product lifecycle, including the often-overlooked reverse logistics process.

Moving forward, brands must:

• Embrace technological solutions for fit: Prioritize the integration of AI-powered sizing recommendations, virtual try-on technologies, and 3D body scanning solutions into their e-commerce platforms.
• Leverage data analytics: Utilize return data and customer feedback to continuously refine sizing algorithms, improve product descriptions, and identify brands or product lines with significant sizing inconsistencies.
• Increase transparency in return data: Include return rates and the environmental impact of returns in their sustainability reports to provide a more accurate picture of their overall footprint and the effectiveness of their mitigation strategies.
• Re-evaluate return policies: While some return fees may be implemented strategically, the primary focus should be on preventing returns in the first place through enhanced sizing accuracy and customer guidance.
• Optimize reverse logistics: Implement more efficient and environmentally friendly processes for handling and processing returns, prioritizing resale and responsible recycling over landfill disposal.