How retailers are reducing returns — post-holiday and year-round

By Teleperformance
A photo of someone purchasing something on their computer. We see a person with a laptop on their lap and a credit card in their hand. Representing the purchasing of goods and the topic of the article - how retailers are reducing returns

Ginnette Baker, evp, retail, e-commerce and CPG, Teleperformance and Ruchi Gupta, evp, retail and global business services, Teleperformance

The returns process has been made easier over the years as brands and retailers work to provide a frictionless customer experience. However, this has created an unwanted rise in product return rates. According to the National Retail Federation, roughly $743 billion in product returns were processed in the U.S. in 2023. 

Some retailers have started charging restocking fees or limiting the time window for a return to mitigate increasing returns. Despite these efforts, the challenge remains for retailers to provide an easy customer experience while reducing returns. This challenge takes on even more significance for retailers during the holiday season.

How a fast-fashion retailer reduced return rates with advanced data analytics support

Retailers are working with leading third-party business and customer experience management (CXM) service providers to tap into AI-powered data analytics to uncover actionable insights that help combat growing returns. By leveraging data insights from customer service interactions and returns, retailers can convert returns into exchanges, detect return fraud and adjust product selection based on return drivers — all while supporting an easier and more personalized experience. 

For instance, an international fast-fashion retailer with more than 20 brands experienced a significant rise in refund rates. Refunds spiked to 60% of sales during a large sale period, and the retailer was unsure of the cause behind this.

The retailer turned to Teleperformance (TP), a third-party CXM services provider, to help tackle return rates. 

In this situation, TP used descriptive and analytical modeling to assess refund attributes. Then, AI and machine learning were applied to predictive modeling to determine probable refund percentages and identify refund drivers. 

As a result, the retailer identified 45,000 products that contributed to the high refund rate, including data on the most impactful product categories, brands, colors and timing that led to returns. 

TP data analytics teams also applied predictive modeling to help the retailer forecast return rates based on its current product mix and shopper profiles. This data was then applied to real-time interaction analytics, which helped the fashion retailer identify the top return reasons and substantial sub-reasons. Based on these insights, customer experts were also equipped with scripts to help provide shoppers with personalized, alternative product recommendations to convert returns into exchanges. 

These efforts resulted in a 13% decrease in the refund rate. Furthermore, the personalized shopper insights enhanced customer satisfaction by providing more helpful, emotionally intelligent interactions and value-added suggestions for alternative products that better suited shoppers’ needs.

Combating fraudulent returns with data analytics

Retailers also face the challenge of combating fraudulent returns which, according to the NRF, resulted in $101 billion in losses in the U.S. in 2023 alone. 

Leading CXM service providers can help combat fraudulent returns by leveraging AI-powered data analytics. For example, TP data analytics has aided retailers in recognizing and preventing fraudulent returns through pattern recognition, customer behavior analysis and transaction data integration. By uncovering subtle indicators and suspicious patterns — such as return frequency, customer behavior history and vague or inconsistent reasons for making a return — service providers help retailers identify organized fraud rings and individual bad actors.

For instance, a well-known consumer packaged goods brand experienced more than a 50% reduction in returns policy violations in just 60 days after partnering with TP’s data analytics teams. Another client, a global sports footwear and apparel company, increased revenue by over $20 million due to enhanced fraud detection, which more accurately differentiated potentially fraudulent orders from genuine ones.

Proactively addressing return issues enhances customer experiences

Frictionless product returns are crucial for maintaining customer loyalty during the busy holiday season and beyond. Leading CXM providers can serve as an extension of an in-house team, accessing real-time customer engagement data to help turn returns into exchanges, recognize product changes that are likely to reduce returns in the future and help identify fraudulent orders and returns. 

In harnessing these capabilities, retailers enhance customer experiences and foster brand loyalty. And, in doing so, they also proactively address return issues and implement forward-looking strategies designed to reduce holiday returns and set the stage for sustainable growth.

Sponsored by Teleperformance