The Trouble With Online Shopping Returns

If there was any doubt that the pandemic has sped up the growth of e-commerce in this country, a recent report from KPMG helped put it to rest. It found that 66 per cent of Canadians have increased their online shopping habits during the pandemic and that most will likely stick with these habits. 

With all these online purchases, however, comes a significant rise in the number of returns to retailers. Kevin Lyons, an associate professor of supply chain management and environmental policy at Rutgers University, says that 30 to 40 per cent of all online purchases are returned. Compare this with 10 per cent of purchases at brick-and-mortar stores. 

The big problem with all these returns is the environmental impact. Each year in the U.S. alone 3.5 billion products (worth US$400 billion) are returned, generating five billion pounds of waste. Although only 20 per cent of returned products are defective, many are liquidated or sent to landfills. Returns also create a giant carbon footprint. In the U.S., waste generated through returns each year contributes to 15 million metric tons of carbon dioxide emitted to the atmosphere.

The other problem is that returns can be difficult for retailers to deal with since many don’t have the technology or know-how to handle goods sent back to them. Typically, if retailers don’t send returns to landfills, they sell them to discounters, wholesalers or liquidators. But not all brands do so. Burberry, for example, admitted to burning clothing and accessories that didn’t sell. And fast-fashion retailer H&M said it burned 15 tons of clothing it deemed not in good enough condition to recycle. 

Returns are also expensive for retailers. In the U.S., Statista reported that return deliveries cost US $550 billion in 2020, which is 75 per cent more than four years prior. Fashion retailers especially suffer this problem since some customers buy garments in different sizes, then use their homes as dressing rooms. Online retailer Revolve, for example, reported $499 million in sales in 2018, but in the same year it spent $531 million on returns. Industry experts estimate that retailers are losing a third of their revenue because of returns. 

So, what can retailers do to combat the growing problem of e-commerce returns? Plenty, it turns out, and some of the most promising solutions leverage existing analytics tools.  

Optimize your operations 

Operations is a good example of an area where analytics can make a big impact. Take delivery and return processes, which are often not co-ordinated within retail operations. For instance, if a customer has a delivery and a return pickup on the same day, the tasks are usually handled in different ways and by different people working for the retailer. If, however, the retailer co-ordinated these tasks using global information systems (GIS) and global positioning systems (GPS), redundancies could be eliminated.

Of course, smaller retailers might not have the resources to develop sophisticated GIS and GPS applications. But they can still improve their return logistics with things like pickup and drop-off sites. These allow customers to manage their returns with convenience and they give retailers a more cost-effective solution compared with door-to-door courier collections. Smaller retailers can also use dedicated return specialists. In the U.K., for instance, Clicksit automates and manages returns and provides data that can help with planning and improved service.         

Further action can happen when returned items arrive at the retailer’s warehouse. There, returned products should be scanned to identify which warehouses they came from and whether items can be resold. If returns consistently come from a few warehouses only, retailers need to figure out why. Perhaps staff at those warehouses aren’t ensuring that correct and intact products are delivered. 

If items can be resold, they should be repackaged and be available for shipping as soon as possible. The longer items are unavailable, the greater their loss in value. It’s also important to figure out the most cost-effective way to reship items—either to the warehouses or directly to the customer—which can be done with the right data. 

Better managing e-commerce returns also comes down to ensuring that a company’s forward logistics, reverse logistics and inventory are well integrated and continuously analyzed for improvement. When there is strong integration across the entire inventory supply chain, products are routed in the most effective way, warehouse replenishment decisions are perfected and staff are more efficient.     

Evolve your business model

In some cases, it might be smart for a retailer to rethink parts of its entire business model to better deal with returns. That could mean offloading the returns process to third parties that have the ability to make that process cheaper and more efficient. One example is Happy Returns, which places “Return Bars” in malls, stores and at schools. Once returns are collected, Happy Returns ships them to its distribution centres where garments are assessed and then given a second life through restocking, recycling or donation.

Third parties like Happy Returns can also help retailers make significant environmental improvements to their operations. In doing so, they move retailers away from the linear economy and to the circular economy. In other words, instead of a retailer allocating resources solely to optimizing the production, use, and disposal of goods (i.e., the linear economy), by using circular economic tools like third parties, the focus moves to the elimination of waste and the continual use of resources. Eco-friendly packaging is another one of these tools, as is reusing returned goods for new products. 

It’s important to be wary of some third-party logistics providers (3PL), however, particularly those that look after most of the supply chain, including inventory management, storage, fulfilment, shipping, and, more recently, returns. In many cases, 3PLs don’t address environmental impacts or return costs.  

One alternative is to use fourth-party logistics providers (4PL), which employ a single interface to oversee the entire supply chain operation. This simplifies everything and makes oversight easier. The major advantage of having a 4PL system is that the co-ordination of different supply chain vendors is smoother than a traditional 3PL. A 4PL can use its resources for integration and optimization using data analytics and artificial intelligence. This bridges the gaps that 3PL leaves behind and leverages the strategic use of data analytics to reduce inventory write off and waste. 

Make analytics your friend

Retailers may take different approaches to solving the e-commerce return problem. But most experts agree that analytics needs to be a key part of the solutions. That is why these same experts say it’s so important to hire experienced data analysts who know how to mine information, such as which products are returned, why they’re returned and who returns them.    

Those analysts can’t do much without the right information, however. So the first goal of retailers should be to collect lots of data about returns. One way to do that is by including disclaimers on return forms that encourage honest responses from customers (e.g., “all returns will be processed regardless of reason”). A comment field on return forms is also valuable since it allows customers to be specific. Is the colour off? Are the sleeves too short? Are there multiple reasons for the return? Improving the breadth and depth of collected data allows analysts to identify patterns in these comments, which, in turn, can uncover insights behind the why of returns.   

All that data can help retailers understand who returns products, which can minimize returns as well. This is usually done by segmenting customers based on their sales-return ratio, creating return profiles, and then designing unique strategies for each profile. The retail chain Winners, for example, gives loyal customers a 30-day return window, while non-loyal shoppers have only 14 days. Gaining insight into customer segments allows retailers to create targeted initiatives that keep the most profitable customers happy while minimizing returns from less profitable segments.

Next-level analytics

A growing number of retailers are also exploring even more advanced analytics and machine learning techniques to reduce returns. For instance, we might start seeing more applications of predictive risk-of-return models. These models predict the likelihood of returns before an online transaction is done by combining information such as product details, historical return rates and personalized sizing data. That prediction allows automated decisions to be made about the rewards or punishment to implement, if any, in order to reduce the probability of returns.    

Artificial intelligence (AI) is also being used more broadly to ensure customers buy with confidence and that their key reasons for returns are eliminated. Leading fashion and sports brands, for instance, use AI to provide customized recommendations during online shopping. This can include size recommendations based on the customer’s purchase history. AI is used to make accurate delivery promises as well. When next-day delivery is available, for example, AI can give inventory positions in real time, helping retailers keep their delivery promises. Not only does this curb returns, but it also does boosts customer confidence.

Augmented reality (AR) is another area gaining traction with retailers wanting to put a dent in return rates. In most cases, AR tools are used to help customers see what items would look like in their environment before ordering. This started in the beauty industry but now AR is used in the broader retail industry as companies see the benefits, including reduced returns. Ikea’s AR application, Ikea Place, is a good example. The app lets customers drop virtual furniture into their homes and view it through their smartphone.

Advanced manufacturing and consumer engagement technologies could also help reduce the mismatch between consumer expectations and the products they buy. Firms such as Levi’s, Ray-Ban and others combine interactive online “fitting rooms” with the Internet of Things, robotics, 3-D printing and other advanced manufacturing techniques to customize their products to the tastes and specifications of individual consumers. Such products are costlier to make and are harder to resell. (Would you buy a shoe with someone else’s initials on it?) Yet they are also less likely to be returned. A recent research paper by Anton Ovchinnikov, Distinguished Professor of Management Analytics at Smith, co-authored with Paolo Letizia from the University of Tennessee and Gokce Esenduran from Perdue University, shows that firms can use consumer behaviour analytics together with customization to increase profits and reduce returns.

Let’s face it: returns aren’t going away. Consumers now expect free returns and customer-friendly return policies. But that doesn’t mean retailers should ignore the financial and environmental problems of returns. Indeed, as a number of retailers have shown, using analytics to curb returns could be key to their very survival, while helping the planet too.

This article was researched and written by a team of Master of Management Analytics students at Smith School of Business: Scarlett Desmarais, Amir Hossini, Heidi Klotz, Noman Siddiqui, Himalay Vayeda, Natasa Zugic-Drakulic.