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The Secret to Solving Retail’s $743 Billion Returns Problem: Intelligent Customer Support

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With returns siphoning off a staggering $743 billion from retailers’ bottom lines in 2023, it’s clear that the industry’s approach needs an overhaul. But instead of leaning on rigid policies that risk driving customers away, retailers can use this as an opportunity to rethink returns.

The key? Customer-first strategies that not only reduce returns but also boost experience and loyalty.

A combination of proactive, intelligent customer support and advanced technologies can reduce costs, improve customer satisfaction and foster stronger relationships — transforming returns from a setback into an opportunity to provide a hyper-personalized customer experience for both shoppers and retailers.

The Growing Impact of Returns on Retail

For every $1 billion in sales, the average retailer experiences $145 million in returned merchandise. If a nearly 15% return rate sounds high, consider the range of reasons why consumers return merchandise.

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Unmet product expectations, quality issues, unclear product descriptions and the purchase of multiple items with the intent to keep only one are frequent motivators for returns. In the clothing and electronics categories, incorrect sizing and functionality problems are common reasons for returns, and more than 33% of all products ordered online are returned.

These challenges frustrate both retailers, who face increased costs and logistical burdens, and consumers, who feel dissatisfied when products fail to meet their needs. Poor product onboarding, a lack of personalized support and inefficient return processes only make the problem worse, ultimately damaging customer satisfaction and loyalty.

Quick-fix solutions like rigid return policies and additional fees may seem like the right move for retailers aiming to reduce returns, but these tactics often damage trust and drive customers to competitors.

A better solution is to address the root causes of returns by using AI-driven customer support tools, predictive analytics and solutions that help customers find the right product from the outset. This approach creates a seamless customer journey, reduces return rates and helps customers feel more confident and satisfied with their purchases.

The Use of Intelligent Customer Support to Improve Customer Satisfaction and Reduce Returns

To transform the returns process, retailers should prioritize a customer-first mindset that turns returns into a strategic advantage. Instead of merely reacting to issues, investing in solutions that enhance the customer journey can help build stronger relationships. Using advanced technologies like AI-driven support and data analytics, retailers can create a more seamless, customer-friendly experience that leads to greater trust and long-term loyalty.

1. Offer proactive customer support using predictive analytics.
Stricter return policies are not the solution to your return challenges. Instead of limiting dissatisfied customers’ ability to resolve their problems, consider tackling the root issues that cause customers to return products in the first place.

Predictive analytics and AI-driven chatbots help you identify potential issues before they escalate, allowing you to engage customers with timely, personalized support such as reassurance, product education or alternative solutions. This early intervention helps reduce return rates and boost customer satisfaction.

While returns are sometimes unavoidable, you can improve the customer experience by automating return processes, providing clear instructions and approvals upfront, and making returns less troublesome and inconvenient. Moreover, by analyzing return data, you can refine inventory, enhance product quality and develop targeted outreach strategies to retain customers even after a return, turning challenges into opportunities for stronger customer relationships.

2. Help customers select the right products with AI-driven marketplace solutions.
Inaccurate product selection is a primary driver of returns. And in many cases, customers purchase the wrong product due to unclear descriptions, poor recommendations or limited guidance.

But what if you could improve your ability to help customers make the right choices from the beginning?

Personalized guidance and recommendations can significantly enhance the shopping experience. By using AI algorithms to analyze customer preferences, browsing history and behavior, you can deliver tailored product suggestions. Virtual advisors or chatbots offer real-time assistance that caters to specific customer needs, while behavioral analytics adjust recommendations dynamically, making interactions feel more intuitive.

Enhanced search and discovery tools, like AI-driven filters, natural language processing and visual search help customers find what they need easily — whether by typing conversational queries or uploading images. Comparison tools help customers analyze product features, reviews and pricing side-by-side, which makes evaluating products simpler and gives them more confidence in their decisions.

In addition, immersive experiences using augmented reality (AR) help customers ‘try before they buy,’ from virtual fitting rooms to visualizing furniture at home. AI sentiment analysis enhances this experience further by summarizing common praises and concerns from reviews, making it easier for customers to make informed choices and enjoy a more engaging shopping journey.

3. Optimize the customer journey with data-driven insights.
Advanced analytics shed light on crucial stages in the customer journey where returns are most likely to occur, enabling you to address issues early in the process. By focusing on key touch points — such as onboarding, product education and post-purchase support — you can create a seamless experience that builds customer confidence.

Optimizing the onboarding process might mean offering detailed product tutorials or fit guidance, while enhanced post-purchase support could involve proactive check-ins to address potential concerns early on. By prioritizing these touch points, you not only minimize customer frustration but also foster loyalty, making customers feel supported and less inclined to return products.

Minimize Returns with a Data-Backed Approach

Returns are an unavoidable part of the retail experience, but they don’t have to be a drain on profits or customer loyalty.

It’s time to move beyond quick fixes and embrace a smarter, more proactive strategy. Retailers that help customers identify the right products, optimize the customer journey and provide proactive support can transform returns from a liability into an opportunity to strengthen customer relationships.

The key to returning success lies in understanding customer needs, taking advantage of advanced technologies and making every touch point count to create a satisfying and seamless experience.


Banwari Agarwal is the CEO of Retail, Marketplaces, and Consumer Packaged Goods at Sutherland, an experience-led digital transformation company. Agarwal brings deep expertise in digital technologies and operations and over 25 years of leadership experience across the U.S., Europe, and APAC. His strategic vision has driven transformative outcomes in digital business services across multiple industries, delivering innovative, cutting-edge solutions in finance, HR, procurement and supply chain management.

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