Unlocking retail value through returns data
In today’s eCommerce-driven retail landscape, returns represent a significant challenge. Retailers face growing costs, logistical complexities, and an increasing environmental toll. However, with the right strategies and tools—particularly AI and data analytics—retailers can transform the returns process from a drain on resources into an opportunity for growth.
During a recent workshop focused on innovation in retail, several practical strategies emerged for turning returns data into a value-generating asset. Here’s a look at the key insights and how they can be applied to unlock value in the returns process…
In a nutshell…
- Turn returns into donations: Partner with charities to reroute low-value returns, offering loyalty rewards to customers while reducing costs and environmental impact.
- Leverage returns data: Use AI to predict return risks at checkout, offering accurate sizing recommendations and enhanced product visuals to prevent returns.
- AI-driven exchanges: Suggest alternative products during the return process, using AI to turn returns into new sales opportunities.
- Smarter product recommendations: Personalise the shopping experience by recommending products based on previous purchases to reduce impulse buys and returns.
- Automate the returns process: Implement AI-powered, real-time returns systems to streamline the process for customers, offering instant exchanges or refunds.
- Turn returns into a strategic asset: With data-driven insights, retailers can optimise returns management, reducing costs, improving customer satisfaction, and driving future growth.
A closer look…
Turn returns into donations to build loyalty
One idea explored is partnering with charities to divert low-value returns, especially items that are costly to process or restock. Rather than sending these items back to the warehouse, customers could be encouraged to donate them.
In exchange, retailers could offer loyalty points or small discount incentives, creating goodwill while reducing logistical strain. This approach strengthens brand loyalty and demonstrates a commitment to sustainability.
Use existing data to prevent future returns
Returns data provides a wealth of insights into why items are being sent back—whether due to sizing issues, product misrepresentation, or other factors. AI can help retailers proactively address these pain points by predicting return risks at the checkout stage. For example, customers could be offered enhanced product visuals or accurate sizing recommendations based on their past behaviour and similar customers’ feedback.
Leverage AI for product exchanges
Instead of viewing returns as lost sales, retailers can use AI to recommend exchanges that better fit the customer’s needs. By analysing past returns and purchase behaviour, AI can suggest alternative products that align with the customer’s preferences, increasing the chances of retaining the sale and turning a return into a positive customer interaction.
Optimising returns management for the future
Looking ahead, AI and data analytics will play an increasingly critical role in how retailers manage returns. Here are two forward-looking approaches that could shape the future of returns management:
Smarter product recommendations through AI: Retailers can use AI to personalise the shopping experience and reduce the likelihood of returns. For example, by analysing a customer’s previous purchases, AI can suggest products that complement their wardrobe or lifestyle. This not only improves the shopping experience but also reduces impulse purchases, leading to fewer returns.
Streamline returns with automated systems: Automation can simplify the returns process, making it more efficient for both customers and retailers. AI-driven systems could offer real-time returns processing, providing instant exchanges or refunds and reducing the friction that often accompanies returns. By integrating automated return systems, retailers can enhance customer convenience and minimise manual effort.
Turning returns into a strategic asset
Returns don’t have to be a costly burden. By leveraging AI and data-driven insights, retailers can shift the focus from managing returns to optimising them. Whether through reducing returns with smarter product recommendations or turning returns into new sales opportunities via exchanges, retailers have the tools to transform returns into a strategic asset.
By rethinking returns management, retailers can not only reduce waste and cut costs but also improve customer loyalty and drive future growth. The future of retail lies in using data and innovation to turn challenges into opportunities—and the returns process is no exception.
