Latest / The Operations Podcast with Fexingo: Process, People, and Profit in Modern Business / How a Direct-to-Consumer Brand Cut Returns by 30 Percent
Transcript
- Lucas: Returns are the silent killer of e-commerce margins. The average online return rate hovers around 20 to 30 percent, and for apparel it's even worse — closer to 40 percent for some categories. But one direct to consumer brand, Everlane, managed to cut its return rate by 30 percent in less than a year without tightening its return policy. Luna: Wait — they didn't just make returns harder? That's usually the first lever companies pull. Lucas: Exactly. They went the opposite direction. They kept a generous 60-day return window and even covered return shipping. But they overhauled the operational process behind the scenes — from the moment a customer lands on a product page to the moment a returned item is back on the shelf. Luna: So they tackled root causes instead of symptoms. What was the first thing they changed? Lucas: Product descriptions. Everlane realized that a lot of returns were driven by mismatched expectations — the fabric didn't feel like what the customer imagined, or the fit was off. So they added detailed fabric composition, weight in grams, and even a 'hand feel' rating: stiff, medium, or soft. They also started showing models in multiple sizes, not just the standard small, and included real customer measurements from try-on sessions. Luna: That sounds like a lot of content per product. Didn't that slow down their product launch cycle? Lucas: It did cost more upfront. Each product page took about 30 percent longer to produce. But the payoff was immediate: return rates for products with the enhanced descriptions dropped by 18 percent compared to their old pages. And because fewer items came back, the team actually spent less time processing returns, so it freed up labor hours elsewhere. Luna: So better descriptions → fewer returns → less processing work. That's a virtuous cycle. Lucas: Exactly. But the bigger operational change was on the sizing side. Everlane integrated an ai based sizing tool called Fit Finder. It asks a few questions — height, weight, preferred fit — and recommends a size. They placed it right above the 'Add to Cart' button. Within three months, the tool reduced size-related returns by 22 percent. Luna: And I bet the tool also collects data on what sizes people actually order versus what they keep. That's gold for inventory planning. Lucas: Absolutely. Everlane feeds that data back into their buying and production decisions. If Fit Finder shows that 65 percent of customers who buy a certain dress end up sizing up, they adjust the cut for the next production run. That's a closed-loop feedback system that most brands don't have. Luna: Okay, but what about the actual return process once a customer decides to send something back? That's where a lot of operational friction lives. Lucas: Right. That's the second big piece. Everlane moved to a qr code based drop-off system. Instead of printing a label and packing a box, the customer generates a QR code on their phone, takes the item to a participating drop-off location — like a FedEx or UPS store — and scans the code. The label is printed at the counter. That cut the average time a customer spends initiating a return from about eight minutes to under two. Luna: And for the operations team, that means fewer customer service calls asking 'where's my label?' Lucas: Exactly. Their customer service ticket volume related to returns dropped by 40 percent. But the really big win was on the warehouse side. When a return comes in, the QR code links to the original order, so the warehouse knows exactly which item it is, which size, which color, and whether it's still in season. They can inspect it and put it back on the shelf in under five minutes — down from an industry average of about 15 minutes. Luna: That speed matters a lot for items that sell out quickly. A dress that's in high demand can be backlisted and sold again the same day it's returned. Lucas: Exactly. And that's where the financial math gets really interesting. Everlane calculated that the operational changes cost about $1.2 million in technology and process redesign over the year. But the 30 percent reduction in returns meant they saved roughly $4 million in return shipping costs, restocking labor, and inventory write-offs. That's a return on investment of over three to one. Luna: That's a no-brainer for a mid-sized brand. But I wonder — how much of this could a smaller, say, sub-ten-million-dollar brand pull off without that budget? Lucas: Great question. The product description improvements are basically free — just more work. The AI sizing tool, there are affordable SaaS options that start at a few hundred dollars a month. The QR code drop-off system, that's something that major carriers already support, so it's more about setting up the integration. I think smaller brands can pick two of these three levers and still see a meaningful improvement. Luna: It reminds me of something we've talked about on this show before — how operational improvements often compound. Better data on customer fit reduces returns, which improves inventory accuracy, which speeds up restocking, which makes customers happier, which builds loyalty. It's not just a cost-cutting play. Lucas: Exactly. And that's the lens we try to bring every episode. We're not here to pitch quick fixes. We're here to unpack the actual mechanics of how businesses get better. And we do that without running ads, because we think that keeps the conversation honest. Luna: Yeah, that matters. A lot of podcast listeners are used to being sold to every ten minutes. We keep it clean because we want the content to speak for itself. Lucas: Right. And if these conversations have moved your work forward in some small way, the best way to keep them ad-free is through listener support. There's a link at buy me a coffee dot com slash fexingo. No pressure, just a way to help if you find value here. Luna: Yeah. And now back to returns — because I want to flag one more thing. Everlane also tackled return fraud, which is a huge issue. People ordering multiple sizes and sending back the wrong one, or wearing something and then returning it. Lucas: Good point. They implemented an RFI tagging system — radio frequency identification tags sewn into the garment. When a return comes in, the warehouse scans the tag, and the system checks if that specific item was actually shipped to that customer. It caught about 5 percent of returns that were fraudulent, which doesn't sound huge, but on a $100 million revenue base, that's millions in savings. Luna: And the tags are reusable? That's important for cost. Lucas: Yes, they're designed to be removed and reused. The tag cost about 20 cents each, and they can survive about 10 cycles before wearing out. So the per-use cost is negligible. Luna: So the full playbook: better product info, AI sizing, QR returns, RFID fraud prevention. It's a system, not a single fix. Lucas: Exactly. And the key insight is that Everlane didn't try to do it all at once. They piloted the sizing tool on 20 high-return styles for three months, proved the concept, then rolled it out to the entire catalog. Same with the QR code system — they started in three major cities before expanding nationally. Luna: That phased approach makes it more replicable for smaller brands. Start with the highest-return products, prove the ROI, then expand. Lucas: Right. And one more thing — they also changed how they measure success internally. Instead of just tracking return rate, they started tracking 'net return rate' — which excludes exchanges. Because an exchange is actually a retained sale, not a loss. That shifted the team's mindset from 'returns are bad' to 'returns are a signal we can act on'. Luna: That's a subtle but powerful cultural change. It reduces the stigma around returns and encourages people to find operational solutions instead of just blaming customers. Lucas: Exactly the kind of thing we dig into on this show. I think there's a lesson here for any business that ships physical goods: the returns process isn't just a cost center — it's a source of data and a lever for improvement. Luna: And it doesn't have to be perfect from day one. Pick one piece — better descriptions, a sizing quiz, QR drop-off — and start there. Lucas: Absolutely. That's it for this episode. We'll be back next time with another deep dive into how real companies solve real operational problems.