Returns are shaping the future of retail — and while they’re an integral part of the consumer experience, they’re also becoming a growing pain for retailers.

Retailers that offer hassle-free returns gain a competitive advantage. But without proper management, the return process can quickly escalate into a major headache, draining financial and other resources.

The average return rate for online orders hovers around 30%, which experts expect to grow in the future. Small businesses are particularly vulnerable to higher return rates, as they often lack the resources to invest in sophisticated return-management systems and may not have the expertise to handle returns effectively.

It’s time for retailers to embrace a different approach. By predicting returns instead of trying to prevent them, they can reduce return rates and improve customer satisfaction.

The Return of Returns

According to a 2022 survey by the National Retail Federation and Appriss Retail, the total value of retail returns has reached a staggering $761 billion. The rise of e-commerce has played a crucial role in driving this surge, allowing online shoppers to make purchases without physically experiencing the products, and resulting in higher return rates. Retailers are increasingly recognizing the need for better returns-management strategies, to mitigate the financial strain caused by returns and enhance customer satisfaction.

The management of returns requires that retailers address many costly operational obstacles, including meeting strict consumer expectations, navigating reverse-logistics complexities, determining process ownership and dealing with data limitations. 

Nevertheless, many retailers believe that implementing an overly generous return policy is a worthy investment to offset costs. They prioritize shipping and logistics price optimization over maximizing returns profitability, especially because loyal customers exhibit the highest return rates. Additional hurdles in managing returns include:

• A complex and fragmented returns process. It’s riddled with inefficiencies and difficult to improve.
• Nonstandard packaging and lack of control. Retailers find it tough to control these packages because of their unpredictable frequency and quantity.
• Collaboration and responsibility. Multiple teams — such as merchandising, marketing, e-commerce and finance — need to cooperate, posing a challenge in assigning clear responsibility for the process. 
• Understanding reasons and impact. Retailers struggle to comprehend why customers return products and how returns affect profits, making it tough to predict and reduce returns.

Simply put, retailers need to enhance returns management to achieve a few objectives: reduce returns, improve the consumer experience and optimize the economics of return processes.

Streamlining the Process

While handling returns presents numerous challenges, it also allows retailers to thrive in a highly competitive industry. To do so, they must enact a clear return policy that makes the process seamless for customers — particularly because 62% of consumers are more likely to shop online if they can return an item to a store. 

The process of reverse logistics moves returned goods from the end-user to the manufacturer or retailer. It’s an essential part of the supply chain, as it helps to recover materials and reduce product lifecycle costs. Its key stages include:

• Collection. End-users employ various channels like mail-back, drop-off or pickup to return goods.
• Inspection and disposition. Teams carefully inspect returned goods to assess their condition and determine if they can be re-sold, recycled or disposed of.
• Re-manufacturing. If feasible, returned goods can undergo repairs or reconditioning to return them to a sellable condition.
• Disposal. Returned goods that can’t be re-sold or re-manufactured are disposed of in an environmentally friendly manner.

Retailers need efficient reverse logistics systems to handle returns, repairs, recycling and disposal. The function recovers value and optimizes resource utilization by reselling returned goods via online marketplaces or brick-and-mortar stores. It also contributes to sustainability efforts, by recycling or donating products that can’t be resold.

There are additional best practices that retailers should employ to reduce returns. They can provide detailed product reviews and pictures to help customers make informed purchasing decisions. They can also send notifications when customers add multiple sizes of an item to their cart, prompting them to make more precise purchasing choices.

However, these methods are not enough to address the root cause of returns. The best way to reduce returns is to improve the overall customer experience, by providing high-quality products, accurate descriptions and competitive prices.

Furthermore, collecting data from returns can improve product offerings and marketing campaigns. Analysis of that data helps to identify trends such as return rates, reasons for returns, seasonal fluctuations and product performance.

The Next Frontier in Retail

It makes sense to focus on preventing returns from occurring in the first place, but retailers should be wary of the strategies they employ to that end. While policies like rigid return windows, restocking fees and damage waivers may prevent some returns, they’re ineffective in avoiding all returns. Even worse, customers may see these rules as punitive.

Instead, retailers should use data and technology to foresee risks and identify customers more likely to return items. Predictive returns deliver:

• Cost savings. Machine learning algorithms analyze customer data such as purchase history, product reviews and shipping information to target the right shoppers. As a result, retailers can avoid unnecessary returns and reduce shipping, restocking and processing costs.
• Enhanced customer experience. Retailers can proactively reach out to customers who are at a higher risk of returning items, offering personalized solutions and addressing concerns before an issue arises. Engaging sooner and providing alternative options enables brands to enhance the overall shopping experience and foster customer loyalty.
• Optimized reverse logistics. Retailers can pinpoint which items customers are most likely to return. They can also more efficiently manage storage, transportation and disposal, will minimize costs, reduce waste and streamline operations.

Predictive returns is still a relatively new field, but it’s growing rapidly. With the help of quality data and technology, retailers can take a proactive approach to returns management.

The integration of AI-enabled supply chain management software yields remarkable improvements across logistics costs (15%), inventory levels (35%) and service levels (65%). When combine with supply chain and customer data, reverse logistics enables retailers to reduce returns, mitigate risks, lower costs and enhance customer satisfaction.

Retailers who want to beat the competition must get their returns management in order. By shifting gears from preventing returns to predicting them, brands can provide top-notch service, save money and avoid headaches.

Yifat Baror is co-founder, chief marketing officer and chief growth officer at Osa Commerce.