In the apparel industry, changes in the ways consumers interact with retailers and make purchasing decisions are leading to an increase in the volume of products returned to the seller. The growth of online channels and lenient return practices have reinforced consumers’ treatment of purchases more as risk-free discoveries for size and style than as end-of-shopping journeys. Retailers report that this is especially true for select categories such as women’s shoes and dresses—particularly for online purchases.
The phenomenon isn’t limited to apparel. All told, American consumers returned a whopping $428 billion of goods in 2020, a return rate of 10.6 percent, with e-commerce returns accounting for nearly a quarter of returns volume.1 But apparel retailers see the worst of it. A McKinsey Returns Management Survey2 conducted just prior to the COVID-19 pandemic noted a 25 percent return rate for apparel on e-commerce channels, compared to 20 percent overall. And with the sector’s e-commerce growing about 35 percent in 2020, its returns are at an all-time high.
Managing those returns, however, continues to be a relatively neglected issue. Many retailers see high levels of returns as a necessary evil and believe they need a generous returns policy to grow their share of wallet. According to our research, managing returns is not among the top five priorities for a third of retailers—and a quarter of the retailers surveyed don’t do so efficiently and effectively. More important, retailers tend to think more about shipping and logistics costs than about optimizing the profitability of returns. In a fashion-based business, any lag time in returns can lead to significant markdowns for merchandise being resold. Brands that sell via wholesale and direct-to-consumer (DTC) channels have an added challenge: returns from retailers often arrive all at once at the end of a season. Marking down prices on the brand’s own DTC site can lead to price matching and value erosion from competing retailers. And with an estimated 10 percent of all returns ending in a landfill, the environmental impact is not trivial.
Managing returns comes with a complex set of operational challenges, including consumer expectations, reverse logistics, process ownership, and data limitations.
Managing returns does come with a complex set of operational challenges, including consumer expectations, reverse logistics, process ownership, and data limitations. But apparel retailers are not powerless. Basic hygiene for returns management now includes a range of capabilities, and more advanced initiatives can help retailers manage the impact of returns in a consumer-friendly way, as well as the key operating model and structural changes that will enable them.
Why managing returns is so difficult
Managing apparel returns comes with challenges that are not necessarily unique to apparel. Retailers across the board—from home goods to consumer electronics and personal care to food and beverage—face similar challenges in returns management. While this may vary across retailers, segments, or even geographies, the following four key challenges are common.
Consumer-friendly retailers feel obliged to accept high levels of returns
Returns journeys present numerous opportunities to disappoint consumers and limited potential to strengthen relationships. As a result, 86 percent of survey respondents agree that a lenient returns policy is critical to increasing revenue and share of wallet, and 75 percent agree returns are a necessary evil.
A particular constraint for department stores is that often the consumers with the highest returns rates are among the most valuable: loyal consumers become used to the returns processes over time, and therefore apparel retailers increasingly feel the need to pay for return shipping. This can have a notably negative impact on fulfillment costs as a share of revenue, given that an apparel retailer often pays round-trip shipping while generating no revenue. The degradation of fulfillment costs as a percent of revenue is particularly acute for retailers with low gross margins per unit. This is not necessarily the case for integrated brands, through which consumers can better refine their size preferences.
Reverse logistics process efficiencies are difficult to achieve
Despite the growth in volumes, most reverse logistics operations remain fragmented and subscale. According to our survey results, the fragmentation of the reverse-logistics operations leads to an increasingly higher complexity in the path for a return to become available to sell, ranging from 10 percent for the most straightforward in-store path to 42 percent for returns that are returned by mail, processed centrally, and restocked in the store or online. As a result, it is difficult to justify the investment in the processes and technology needed to increase efficiency. Complicating matters further, retailers have little control over the timing and volumes of returns, which often come back in nonstandard packaging.
Ownership is difficult to define given the cross-functional nature of returns
While efficient returns processing is naturally the responsibility of operations teams, preventing returns and maximizing their resale value may require the coordination of merchandising, marketing, e-commerce, and finance teams, to name but a few. Perhaps because of this cross-functional effort, 58 percent of survey respondents say that lack of accountability for returns management within any single department or business unit is a pain point within the organization.
Furthermore, the absence of aligned incentives across relevant teams hinders coordination and reduces impact. Without an owner, structure, processes, or comprehensive metrics, it is no surprise that companies have struggled to prioritize returns management.
Data limitations restrict companies’ ability to understand and address root causes
Most retailers do not understand the full unit economics of returns, including markdown liability, how return rates and causes vary by product category, and what an expected level of returns may be for a given product line. Two-thirds of survey respondents say their company has a strategy to improve the economics of returns, while 83 percent of them strongly agree that returns are a concern for profitability. Many retailers find it less expensive and logistically easier to dispose of damaged returned goods in a landfill than identify a separate disposition channel, further eroding the economics of the return. Without this visibility, decisions are being made on an ad hoc basis, and the root causes cannot be addressed.
Initiatives to improve returns management
Tackling these challenges requires both concrete initiatives to manage the impact of returns and meaningful changes to the operating model. Simply put, how can retailers reduce the number of returns in a consumer-friendly way—while improving the economics of the returns that can’t be avoided?
Most retailers have tried some strategies on return mitigation. For example, basic shopping tools such as consumer reviews and high-resolution images are typically associated with conversion improvement but have a side benefit of reducing return rates by helping the consumer select the right product. Even retailers with stricter returns policies prior to the COVID-19 pandemic have often loosened their restrictions during the pandemic to protect their top-line sales. Up to 70 percent of survey respondents now offer free return shipping on some or all items.
Overall, relatively few retailers have adopted sophisticated strategies to tackle returns.
Advanced shopping tools
Based on the experience of our survey respondents, 70 percent of returns were caused by poor fit or style, suggesting that shopping tools are a key lever for preventing returns and improving consumer experience. However, because retailers frequently prioritize and assess these based on improvements in conversion rates, tools that could benefit return rates are sometimes neglected (Exhibit 1).
Most companies we surveyed use basic tools such as consumer reviews, size guides, and high-res images, and some are now experimenting with nudges designed to discourage returns directly. These include, for example, online pop-up messaging when a consumer adds multiple sizes of the same item to the cart.
Some retailers have begun showing product photos or videos with models of different skin tones and body types to give shoppers a more realistic idea of how a product will fit them. Moreover, few retailers are fully applying previous and real-time consumer experiences to inform the shopping and merchandising experience. For example, while there is excitement around in-store clienteling tools—tools that support store associates to better recommend products based on the consumer profile—and the potential to leverage consumer size data across channels, few have tried it at scale. Only one in four retailers in our survey pool use consumer clienteling tools in stores or advise on how brand fits compare to each other. Leading examples of this capability include Stitch Fix, for which consumer feedback on fit and style goes beyond too big or small and is used to improve personalized product recommendations. Looking further ahead, several companies are investing in augmented-reality shopping tools. For example, Nike launched a digitally focused store in China that offers an augmented-reality, foot-scanning technology to determine their best-fit size for different sneakers and styles. Tools such as Sephora’s Virtual Artist allow consumers to “try on” makeup products through the app or on in-store screens.
While these are exciting developments in consumer experience, the impact on return rates is not yet proven. In addition, although makeup and shoes may be well-suited to this technology, it is not yet clear how effective it will be on the product categories with more complicated fit parameters that have the highest return rates (women’s dresses and men’s suits, for example). From a returns perspective, retailers should focus on the best-practice tools that are possible with existing technology instead of waiting for this as-yet-unproven technology.
Many retailers will need to train associates and improve their online return processes to collect more specific data on the reasons for returns, going well beyond “it doesn’t fit.”
Using returns data
Few retailers are driving initiatives to merchandise products with low return rates (Exhibit 2). More broadly, many are missing the opportunity to close the feedback loop by incorporating returns data into the whole product development life cycle. Only 6 percent of retailers we surveyed give merchandising any responsibility for returns, and product-development teams are absent almost entirely. Returns data could, in fact, be considered throughout the go-to-market process.
- Planning: Returns data from previous seasons can be used to inform line architecture, for example, by assessing category performance with the full unit economics, including returns processing costs.
- Design and development: The product line can be optimized to address specific reasons for returns. For example, “these sweaters were often returned because of pilling, so let’s adjust the blend.” To achieve this, many retailers will need to train associates and improve their online return processes to collect more specific data on the reasons for returns, going well beyond “it doesn’t fit.”
- Assortment: Given the significant impact of returns on the overall profitability of an item, it makes sense to factor returns rates into decisions on which products to recommend and merchandise more broadly. Online, return rates could be an important input into the algorithmic and manual assortment of products on the home page and on carousels. In stores, businesses can systematically share data with associates to help them avoid recommending products with very high return rates. As discussed above, clienteling tools can also be used to recommend products most suited to consumers’ size and style preferences, based on their purchase history.
Faster, more accurate returns
A key determinant for both the cost and speed of processing returns is the channel that consumers use to return their items (in the store, through the mail, or at third-party drop-offs). Of the retailers we surveyed, the difference in processing cost between the most and least expensive channels is $5 to $6 on average, while processing returns in stores can save up to 18 days of processing time, improving the chances that the item can be resold at full price.
However, most retailers are not yet actively guiding consumers to their preferred channel, other than the about 30 percent of survey respondents who charge return shipping fees. As a result, the return channel is often decided by the sales channel: e-commerce sales are returned by mail and in-store sales are returned to stores. In addition, most retailers are taking a rudimentary approach to dispositioning returned merchandise, leading to suboptimal allocations of returned items and reduced resale prices. However, “Retailers can incentivize consumers to return through specific channels while optimizing for SKU profitability, reverse logistics costs, or labor-capacity data models behind the scenes. We have seen clearly that consumers return faster when retailers provide a network of convenient locations for returns drop-offs, as an example using a QR code instead of printing a label, or provide packaging at the point of return,” said Amit Sharma, CEO of Narvar.
In the future, retailers have several ways to improve returns economics. They can do the following:
- Nudge consumers toward in-store returns: Based on our survey, in-store returns that are restocked in the store take, on average, 12 to 16 days fewer to process as compared to slower paths, such as returning by mail and restocking in the store. This directly translates to a higher likelihood of full-price sell-through and, for an apparel retailer, a longer time frame that a product will be available to sell in-season. Consumers could be nudged toward in-store returns with messaging during the online return journey or in transactional emails after their purchase, incentives toward a preferred channel, or by leveraging in-store associates at the time of the original sale.
- Create and promote third-party drop-off locations: Some companies are using lockers at transit stations (for example, ASOS in London), grouping together to create returns centers at malls, executing home pickups for returns in areas of high population density, or striking agreements with other retailers. Rent the Runway, for example, has opened multiple drop-off locations leveraging Nordstrom locations, owned Rent the Runway locations, and a mobile pop-up truck in select cities. Amazon orders can now be returned at Kohl’s stores or Whole Foods locations. However, sufficient scale is required to reap the benefit of batching these packages and reducing shipping costs, and so these options may not be available to all apparel retailers.
- Make it easier to return by mail: Companies can, for example, provide everything needed for a return by mail inside the original shipment (preprinted shipping labels and self-sealing packaging) for items that cannot generally be processed and resold in stores. Here, it is important to understand the trade-off in providing a frictionless consumer experience versus the cost of providing free labels and increased probability of returns.
- Use heuristics or algorithms to direct product for resale: Many retailers have rudimentary policies on how to handle products that are returned to a distribution center or a store, either keeping them in the store or redirecting them to a warehouse. Ideally, returns-channel guidance would be created dynamically for each order, developed from granular data around the product, consumer segment, and store, and accounting for the processing costs and sell-through rates of the relevant SKUs in local stores. With this, retailers can drive better returns economics if merchandise can be dispositioned at the time of return and directed to where demand is greatest, therefore generating a higher resell price.
An opportunity to encourage repurchase, exchange, or loyalty building
Even if retailers employ all the best practice levers above, some level of returns will be unavoidable. In these cases, it is critical for retailers to use this opportunity to encourage either a repurchase or exchange, thereby preserving some of the original order value, or provide a seamless and convenient returns experience that encourages stronger loyalty.
33 percent of repeat consumers would choose to abandon a retailer if they had a “difficult” returns experience.
According to a 2020 report on returns from Narvar,3 the level of convenience and transparency in the returns experience is critical to consumer retention. Seventy-six percent of first-time consumers who had an “easy” or “very easy” returns experience would shop at a retailer again; however, 33 percent of repeat consumers would choose to abandon a retailer if they had a “difficult” returns experience. For retailers, this underscores the importance of providing optionality in returns channels (for example, third-party drop-off locations) and clear, consistent communication on the returns process and status.
Structural changes for successful returns management
In support of these initiatives, retailers also need to think through structural changes that need to be in place to support and sustain returns management. Data and analytics is one foundational factor that is critical to understanding the returns economics, as well as highlighting insights that can inform how retailers want to structure and focus the advanced initiatives. Changing the ownership and accountability structure within the organization is another factor that ensures returns management is a strategic priority across the business. With this in mind, the most successful retailers focus on three structural changes to embed successful returns management.
Data and analytics
While some retailers have made progress even without data transparency and analytics capabilities by, for example, adjusting policy and improving process efficiency, rigor and granularity around data and analytics can unlock the full value of returns management.
Tobin Moore, CEO of Optoro, told us, “Data has the power to transform retail returns and modernize a process that for many retailers remains a pen-and-paper business. With the right information combined with the use of predictive analytics and machine learning, retailers can quickly find the most profitable disposition channel for a return, avoid unnecessary shipping and redundant touches by optimizing the best path from the initiation of the return. The right analytical approach to returns from the outset helps to fend off depreciation, reduces the number of items that end up in landfills, and even boosts revenue by driving repurchases of goods.”
Increased rigor around data collection and analytics can also enable broader business impact, including identifying consumer fraud, executing effective cross-selling opportunities for in-store returns, and understanding the total earnings before interest and taxes (EBIT) impact of returns rather than just the cost. For example, transparency on the depreciation profile of returns by item and location can help retailers triage and prioritize the processing of returns.
The key challenge for retailers in these use cases will be collecting and integrating a wide range of data types from different areas of the business. For example, dynamically guiding return channels requires both cost data on processing paths by SKU, as well as inventory and sell-through rates for those same SKUs by channel or store. The analytics and data-science tasks will also present challenges to retailers, many of which are still focusing on building out internal analytics organizations for foundational, non-returns-related use cases such as pricing, inventory management, and improved marketing ROI. In these instances, third-party solutions can offer portions of the solution (such as tracking or dispositioning) to immediately unlock the value of returns management.
Returns management is inherently a cross-functional problem. While operations teams are responsible for the efficient processing of returns, there is no consensus on who is responsible for reducing the volume of returns. In all, about half of retailers task at least four functions with responsibility for managing some aspect of returns.
As a result, 58 percent of retailers we surveyed do not have a single owner for managing returns holistically, leading to siloed, ad hoc decisions that do not drive impact for the end-to-end business except for a specific function or decision at a specific point in time (Exhibit 3). To increase strategic focus and coordination, we recommend designating a single senior leader with responsibility for managing the end-to-end impact of returns and coordinating between cross-functional stakeholders to drive progress on returns.
Aligned performance metrics
The obvious challenge for a single leader attempting to manage returns holistically is aligning different functions that they do not directly control. Part of this alignment will depend on the operating cadence and on available resources. However, aligning key performance indicators (KPIs) across the business and translating them into metrics that are relevant for different stakeholders will also be a key enabler. Possible examples include the following:
- giving merchandising and product-development teams some accountability for the return rates of their styles, which builds the economics of returns into productivity metrics
- aligning incentives of in-store associates by including regional e-commerce sales and returns transactions in their targets
- using net sales instead of gross sales as the objective function for online assortment
Before agreeing on aligned KPIs, many retailers have work to do on simply providing visibility on the full cost—explicit and implicit—of the returns as well as the total EBIT impact of returns. Approximately half of retailers surveyed do not have easy access to processing costs or to breakdowns of return rates by product category.
Starting the journey
The experiences of retailers that have made progress on returns management suggest the following critical first steps.
- Appointing an end-to-end owner: Although returns management is cross-functional in nature, appointing a single owner with clear KPIs can help ensure accountability and transparency.
- Understanding the unit economics of returns: Starting with one returns flow (such as in-store returns), analyze granular returns cost data to understand the true unit economics of returns and where the biggest cost reduction opportunities may exist.
- Understanding root causes of returns: Collect detailed reason codes for returns through store-associate training and online return-survey design to create the feedback loop to inform product design and assortment planning.
Only after this journey can retailers prioritize a pipeline of initiatives along the returns journey.
In the accelerated world of omnichannel shopping, the financial impact of returns could become unsustainable for many apparel retailers. However, if retailers can improve their capabilities to manage returns, there are opportunities to add value to their bottom line, improve consumer experiences, and reduce fashion’s environmental impact.