Retailers Are Tapping Advanced Analytics Partners to Help Reduce Returns and Combat Fraud
Product returns continue to be a growing source of friction for the retail industry, with $685 billion in merchandise returned in the U.S. last year. However, retailers can convert these returns into exchanges, while also improving fraud detection and optimizing production selection, by leveraging a combination of advanced artificial intelligence-powered data analytics and customer service insights into the underlying causes of returns. These tools are critical to reducing return rates that continue to dampen sales profitability.
Customer experience management (CXM) providers offer a wealth of data and insights into customer interactions, including product returns. Utilizing these customer insights, leading CXM service providers that also specialize in deep analytics can offer retailers access to real-time data insights, tools, and capacity to help manage and reduce product returns and combat fraud.
Reducing Return Rates: Turning Return Data Into Actionable Insights
The average return rate of online apparel orders in the U.S. is 24.4 percent, according to a survey of U.S.-based apparel brands and retailers by Coresight Research. That translates to $38 billion in returns with an estimated $25.1 billion in processing costs. These staggering figures underscore the urgent need for innovative solutions to minimize returns and enhance profitability across the industry.
To address these challenges, brands must adapt quickly to shifting consumer behaviors and their related operational hurdles. In one recent case, an international apparel brand faced a more than 50 percent surge in return rates during a key sales period. The brand partnered with its CXM services provider's data analytics team to use descriptive and analytical modeling against its customer experience data to assess refund attributes. It then applied AI and machine learning to predictive modeling to determine probable refund percentages and identify refund drivers. The analysis found over 45,000 products contributing to the surge in returns, revealing key patterns in product categories, brands, colors, and timing. Using these insights, the CXM services provider developed targeted scripts for its customer care experts to offer personalized, alternative product recommendations to convert returns into exchanges.
This approach reduced the brand's refund rate by 13 percent, while emotionally intelligent interactions and tailored product suggestions improved overall customer satisfaction. Furthermore, the brand maintained a seamless return process that included personalized solutions and proactive engagement which turned disappointing purchases into positive customer experiences.
Combating Return Fraud With Data Analytics
Retailers are also increasingly grappling with return fraud which, according to a recent report, led to more than $100 billion in losses in the U.S. in 2024. To prevent further losses, 54 percent of surveyed retail executives said their organization manually monitors transaction data to identify fraudulent behavior. However, AI-driven data analytics services from CXM service providers can help to identify fraudulent returns on a large scale through a deep dive into transaction patterns, customer behavior, and return histories.
For instance, a major consumer packaged goods company reduced return policy violations by over 50 percent within 60 days by partnering with its CXM provider's data analytics team. Additionally, a global apparel brand increased its revenue by more than $20 million through improved fraud detection that effectively distinguished fraudulent and legitimate transactions.
By identifying suspicious trends such as frequent returns, inconsistent return reasons or flagged customer histories, retailers can mitigate fraud and preserve their profitability while still maintaining customer trust.
Enhancing Customer Experience and Driving Loyalty
Product returns are an essential aspect of the customer journey. While periods of return surges can be challenging, they also offer retailers a unique opportunity to refine their customer engagement strategies and improve operational capabilities designed to manage those challenges. By leveraging advanced data analytics, AI tools, and customer engagement data, retailers can transform the returns process into a more seamless and personalized experience. As we enter a new era of retail innovation, effectively managing product returns will be a defining factor in a retailer's success.
Ginnette Baker is the executive vice president of retail, e-commerce, CPG and QSR business development at TP, a global leader in digital business services.
Ginnette Baker is the Executive Vice President of Retail, Ecommerce, CPG and QSR Business Development at TP. She has a proven track record of collaborating with top-tier ecommerce, retail, IT, and services industry leaders. Ginnette brings transformational leadership expertise in Change Management, Solution Development, Customer Relationship Management, and Business Process Optimization.
