Retail Returns Will Never be the Same
By Raj Ramanand, CEO and co-founder, Signifyd
Raj Ramanand is a leading expert in the areas of online risk, fraud, payments and the use of artificial intelligence in commerce protection. An entrepreneur who was convinced that online merchants were at a disadvantage to physical stores when it came to credit-card fraud liability, he co-founded Signifyd in 2011 to level the playing field. Under his leadership, Signifyd had grown into a $1 billion business and one of the leading fraud protection companies in the world.
Before starting Signifyd, Ramanand was head of risk for emerging markets at PayPal. Prior to PayPal, Ramanand led payments and shipping risk at global delivery and logistics giant FedEx, where he built the first system to proactively detect fraud.
2025 will be the year that online retailers get serious about returns, with personalized returns and instant refunds setting a new standard for balancing customer loyalty and profitability.
The tipping point for online returns has been a long time coming.
In looking for the balance between protecting profits and providing fantastic customer experiences, retailers have accepted returns as the cost of doing business. They’ve blocked some customers from making returns. They’ve offered unlimited returns. They’ve limited the window for returns. They’ve offered unboxed returns. They’ve encouraged in-store returns. They’ve charged for returns. They’ve stopped charging for returns.
2025 will be the year that online retailers get serious about returns. The way the best among them will do that is by providing personalized returns and instant refunds.
How did we finally reach the tipping point? For one, all the tweaking and twisting of return policies haven’t worked. The cost in dollars, customer loyalty and to the environment caused by returns is worse than ever. Consider:
Offering personalized returns and instant refunds won’t be easy. But it is possible today — through data and machine learning. And it is necessary. Every merchant’s biggest competitor — Amazon — set the bar for instant refunds. When Signifyd asked consumers what made for a great returns experience, the top answer, cited by 48% of respondents, was instant refunds — more than free shipping, eliminating restocking fees or long return windows.
Providing personalized returns is exactly what it sounds like. Brands that embrace the concept will be able to offer returns that provide the smoothest tailored experience possible for each individual, based on a deep understanding of the returner’s identity, intent and reliability.
For more than a decade, Signifyd has been able to instantly determine at checkout whether an online transaction is legitimate or fraudulent. The concept is the same, though the technological task is more complex, when it comes to vetting returns.
Today, data and machine learning can provide the insights necessary for determining the legitimacy of a return request. Deploying a machine-learning solution means retailers can be confident in providing most customers with an immediate refund. In cases where caution is indicated, a merchant could issue a refund once it receives and inspects the returned item. Alternatively, a merchant might offer store credit. The important thing is that personalized returns mean an end to blanket policies that penalize the majority of consumers for poor behavior on the part of a small segment of shoppers.
Personalized returns focus on the customer as much as on the merchant. As it is, a customer returning a product can wait as long as three weeks before their refund appears on their credit card statement or in their account. The delay is often caused by the merchant’s need to receive and inspect the return to ensure it is getting back what the customer purchased. 85% of the time it is.
Why should a loyal customer — a shopper who finds a shirt doesn’t fit quite right or that a bike accessory won’t fit on their bike — have to wait three weeks to resolve their disappointment? They shouldn’t.
It won’t be long before consumers will expect instant refunds the way they expect free shipping today.
Online retailers aren’t doing themselves any favors with sluggish refunds. Survey after survey indicates that consumers take returns seriously, when selecting where to shop and especially once they’ve had a bad returns experience. Our polling, conducted by survey firm Talker, indicated that 65% of consumers would stop shopping with a brand based on a bad returns experience.
On the flip side, our initial research indicates that customers who receive an instant refund are significantly more likely to make a purchase with the same merchant in relatively short order.
And while that immediate sale is good news for the merchant, it’s nothing compared to the value of the longer-term relationship the merchant is building with that shopper. Consumers told us in a recent survey that they value a brand they can trust more than any other quality when shopping online.
Eliminating the wait for a refund not only validates the trust a loyal customer puts in a merchant, it also sends a message that the trust works both ways.
JAN 2025
State of the eCommerce Industry 2025
Inventory Optimization?
How Can Data-Driven Return Management Help Improve
By Gaurav Saran, CEO & Founder, ReverseLogix
Gaurav Saran, CEO & Founder
At the time he founded ReverseLogix, no other tech platform could manage product returns from start-to-finish for B2B and B2C companies. Gaurav built ReverseLogix with a passion for leveraging disruptive and emerging technologies, and created a cloud platform that truly solves and optimizes product returns. He is especially passionate about using returns technology to reduce waste and emissions, and is committed to building technology that serves people and the planet.
Once considered nearly unfixable, returns management is now a strategic focus area for the world’s largest brands, due in part to Gaurav’s leadership in solving the returns puzzle. Since its founding, ReverseLogix has fortified its leadership as the industry’s only end-to-end platform for returns management, offering global coverage across all areas of the returns management journey.
Today, Gaurav is a trusted advisor for ReverseLogix customers, which include DHL Supply Chain, FedEx, Samsonite, Amer Sports, Cole Haan, Electrolux and Foxconn. His expertise and engaging communication style make him a trusted source for media seeking to understand the returns/reverse logistics market, such as FreightWaves, Entrepreneur Magazine, TechCrunch, DC Velocity, Supply and Demand Chain Executive, and Business Insider, to name a few.
Gaurav’s creativity and care for others have built a company culture that fosters the imagination and supports good people doing good things. His high-performing team makes it a joy to come to work every day.
Prior to ReverseLogix, Gaurav was with Microsoft, where he led enterprise sales for Fortune 500 companies and drove strategic executive relationships. He has served at a number of Silicon Valley start-ups, such as Zoho, executing strategy, business development, sales and marketing – taking several organizations from the early stages to becoming established growth companies.
Gaurav mentors young professionals in the industry and enjoys seeing others develop, grow and become successful. He has been named a “Pro to Know” by Supply & Demand Chain Executive Magazine, and led ReverseLogix to its designation as a Cool Vendor in the 2022 Gartner report “Cool Vendors in Logistics and Fulfillment Technology.”
Gaurav holds a BS in ecommerce marketing and telecommunications and an MBA in global strategic management from California State University, Hayward.
Real-time data-driven returns management enables faster restocking of popular items, reduces idle inventory, and helps businesses meet ongoing demand without over-ordering fresh stock.
When it comes to running a retail business, gross sales figures and inventory turnover rates often steal the spotlight. However, behind the headline figures lies an often-overlooked issue that impacts the bottom line — product returns. Collectively, US shoppers returned products worth $743 billion in 2023, accounting for 14.5% of total retail sales that year. Returns on online orders are nearly double those of physical storefronts, and as e-commerce continues to eat into physical retail’s market share, return volumes are set to rise steadily year after year.
Recognizing this challenge, businesses are increasingly prioritizing flexible return policies and focusing on improving returns experiences, hoping to transform it from being a cost center to a competitive advantage. In a high-volume, low-margin industry like retail, this is easier said than done. That said, to know ‘how’ to minimize returns, it is important to understand ‘why’ returns happen.
This would require visibility into returns operations, which is a challenge considering the lack of widespread use of purpose-built tools to handle the process efficiently — from tracking return reasons and processing reverse logistics to restocking or disposing of returned inventory. A major hurdle to processing returns quickly is the cost and time associated with assessing whether a returned product can be resold. Estimates suggest that only about 60% of returns are resellable, while the rest may need to be donated, heavily discounted, or sold through secondary channels.
This creates two key issues: first, the financial loss from unsellable inventory, and second, the high operational costs tied to processing returns. In many cases, the expense of managing and processing a return can exceed the original cost of fulfilling the sale, effectively causing retailers to pay for the same item twice. Addressing these challenges requires a data-driven approach to optimize returns management, minimize losses, and streamline operations.
Having actionable data can help brands identify return patterns early enough to make meaningful improvements to their inventory. With better data visibility, retailers can analyze why certain products are being returned more frequently. They could also detect trends — such as seasonal return patterns — and make more informed decisions. While most retailers generally anticipate higher sales and returns during holidays, they often lack granular insights into specifics, like which items, sizes, colors, or styles are returned most.
This is particularly important in industries like fashion and apparel, where returns are influenced by factors such as fit, color preferences, and changing trends. By leveraging data and analytics, retailers can identify these patterns, improve forecasting, refine inventory planning, and ultimately reduce returns.
Accessing data earlier in the process can significantly impact a retailer’s ability to optimize returns management and improve overall business performance. For example, identifying sizing issues early allows retailers to adjust their product offerings or provide better size guidance on their websites, reducing returns caused by fit problems.
Data also helps retailers better understand their customer base — identifying patterns, such as which customers return more frequently. This allows businesses to tailor their approach, keeping loyal customers happy while addressing potential trouble areas, such as new customers needing more education.
In addition, data insights can enhance the post-return process by helping retailers determine how much value can be recouped from returned items and how quickly those items can be processed and restocked. Faster restocking reduces inventory sitting idle in warehouses, allowing products to be resold and minimizing losses.
Making strategic decisions, like deciding where returns should be processed and redistributed, illuminates the need for visibility into returns and how they can interact with inventory operations. For instance, if winter jackets are being returned late in the season, it would make sense to send them to the East Coast distribution centers rather than the West Coast, as the former is more likely to sell that inventory before winter ends and would be the first region to need them again when fall sets in.
Understanding the returns flow helps companies running an omnichannel strategy decide whether to direct returns to distribution centers or physical storefronts running out of the same SKU. This approach streamlines restocking and creates opportunities for exchanges, upsells, or additional purchases when customers visit the store. Incentivizing in-store returns allows businesses to improve customer satisfaction while maximizing sales opportunities and minimizing shipping costs.
While the holiday peak season is eventful for the higher-than-usual sales volume, the weeks following the season also witness higher-than-usual returns flowing back. A chunk of this is due to gift purchases that didn’t meet expectations in size, style, or preference, as well as impulse buys made during seasonal promotions. This can strain supply chains, especially when popular items sell out during peak demand, even as a wave of resellable inventory is coming back through returns.
By processing returns swiftly, brands can quickly inspect and relist them as available inventory. Such fast turnarounds help reduce idle inventory while simultaneously restocking popular items that sold out during peak season. This ensures businesses can meet ongoing demand without over-ordering fresh stock.
For this, real-time or near-real-time access to data is crucial. Data-driven returns management allows businesses to make faster decisions about reordering, pricing adjustments, and inventory management. Operationally, significant value is tied to returned inventory and the costs of processing it through the reverse supply chain. Investing in the right tools and systems will provide brands the visibility to handle returns more efficiently. Ultimately, this will result in better inventory management, while maximizing sales opportunities from returned items.
JAN 2025
State of the eCommerce Industry 2025