Transcript
Returns and the hidden margin killer
23 May 2026
20 min
The 90-Second Illusion
So you're sitting on your couch, scrolling on your phone, and you buy a jacket online.
Like we all do.
Right, exactly. And it looks great in the photos. But when it actually arrives a couple of weeks later, the fit is just wrong. The shoulders are tight, maybe the color's a little off in person.
It never quite matches the lighting in the picture.
Never. So you know the drill, you initiate a return.
Yeah.
And from your perspective as the customer, the experience is incredibly seamless.
Completely.
You click a few buttons on a website, print out a shipping label, drop the package off at the local post office, and a few days later you get your money back. It takes you maybe 90 seconds of actual effort. And it feels like magic.
That friction-free experience is entirely intentional. It's heavily engineered to make sure you don't get frustrated with the brand and abandon them for your next purchase.
But what actually happens after you drop off that package, that's what we're going on a mission today to answer. We're doing a deep dive into why that flawless 90-second customer experience is secretly this massive six-figure silent bleed for businesses.
It is basically a systemic failure hiding in plain sight. It just chews up profit margins in a way that, frankly, most company executives don't even realize is happening.
The Rube Goldberg Machine Behind Every Return
To guide us through the actual mechanics of this, we are looking at this fascinating May 2026 article published by a Stockholm-based tech firm called LightsOut.ai. The article is titled Returns, Complaints, and the Hidden Margin Killer. Their core argument is that fixing this massive financial leak requires a total shift in how companies think, treating returns as a continuous flow rather than an isolated event.
That distinction between an event and a flow perfectly captures the disconnect between the front-end customer illusion and the back-end corporate reality. The customer experiences a single, tidy event. But the business is about to experience a highly fragmented, incredibly messy flow of data.
I was actually thinking about how to visualize this disconnect. Returning that jacket online feels a bit like tossing a coin into a wishing well.
That's a good way to put it.
You just drop it in, you hear a little splash, your refund appears, and you walk away. But for the business, catching that coin is like dealing with a chaotic Rube Goldberg machine.
Yes. That dropped coin hits a lever, which releases a bowling ball, which triggers a pulley.
A whole cascade.
Exactly. It sets off this chain reaction touching five completely different systems and involving multiple employees before the coin finally lands in the bank.
That Rube Goldberg analogy is spot on, especially if we look at the actual mechanics of the friction. Because the issue isn't just that there are multiple steps, it's that the mechanisms connecting those steps are fundamentally broken or just entirely missing.
Tracing the Coin Through Five Siloed Systems
So while you think the return is done at the post office, let's look at the fragmented software systems your metaphorical coin is now bouncing through. First, you have the payment gateway, the system that actually communicates with the banks to issue a refund to your credit card.
Which is usually a third-party software handled by the finance team, right? Stripe or something.
Exactly. And then you have the WMS, the warehouse management system. The warehouse needs to know a package is incoming. And when it arrives, a human being has to literally open it and make a decision. Does this go straight back onto the picking shelf? Or does it need to go to an inspection station because the tag is missing or it looks worn?
So we have the payment gateway and the warehouse system. And I'm guessing the accounting department needs to know about this too.
They do. They rely on the ERP, the Enterprise Resource Planning system. The ERP acts as the central brain for the company's macro financials and inventory. It needs to officially log the credit note to balance the company's books.
So I'm looking at this and I'm thinking, wait. If I take a jacket back to a physical brick-and-mortar store, the cashier scans my receipt, takes the jacket, inspects it right there on the counter, and hands me my cash in about two minutes. Why is the digital version, which relies on all this advanced technology, so much clumsier?
What's fascinating here is the architecture of e-commerce itself. In a physical store, the cashier acts as the single point of integration.
That makes sense.
They are the WMS, the ERP, and the payment gateway all at once. But in e-commerce, those functions are separated across different physical locations and, much more importantly, different software ecosystems. Built by completely different vendors. You might have an ERP that was installed a decade ago running on legacy database logic, right alongside a shiny new cloud-based WMS in the warehouse and a modern third-party payment processor. And they don't speak the same language. They literally speak different coding languages.
So they don't actually talk to each other. In the Rube Goldberg machine, the bowling ball is physically disconnected from the accounting lever.
Exactly. A human being has to physically pick up the ball and move it to the next track.
And that manual movement is the absolute heart of the problem.
Because the people managing these systems have zero shared view of what the others are doing. The warehouse worker is looking at a WMS screen. The accountant is looking at a finance dashboard. They are both flying totally blind to the broader context of the customer's journey.
Return Portals Only Solve 30% of the Problem
But hold on. Let me challenge this a bit. The article from LightsOut.ai is from 2026. E-commerce is not a new industry. Don't businesses use those really slick return portals now, like Returnly or Loop or the built-in Shopify return interfaces? Every time I return something, I'm interacting with a portal that seems highly automated. Doesn't that layer of software bridge the gap between all these older systems?
It's a really logical assumption. Like, if the front door looks smart, the house must be smart. But the LightsOut.ai piece lays out a pretty harsh reality here. Those return portals only solve about 30% of the problem.
Wait, only 30%? That leaves a massive gap.
It's huge. They are fantastic at standardizing the customer-facing data collection. They give you a clean menu to select 'too small' or 'wrong color.' They spit out the shipping label. They log the tracking number.
The front-end stuff.
But that is exactly where the automated elegance stops. The portal is really just a data collector. It doesn't actually execute the back-end operational logistics.
So the portal essentially just feeds the Rube Goldberg machine.
Exactly.
When Exceptions Break Everything
To really understand how badly this breaks down, let's look at a slightly more complicated scenario. Let's say I didn't just return the jacket because it was too small. Let's say I'm returning it because the zipper is completely jammed.
So now it is no longer a standard return. It's a complaint. And exceptions, like complaints, are where these siloed systems truly fail. When you flag a broken zipper, your customer support team has to open a ticket, probably in a CRM system like Zendesk or Salesforce.
So that's another system.
They have to assess if this falls under a warranty policy. They might email you to ask if you prefer a refund or a replacement jacket.
And while that email thread is happening, I just drop the jacket with the broken zipper in the mail. And it arrives at the warehouse.
The warehouse worker scans the box. But because the systems are siloed, that worker's WMS screen does not show the Zendesk conversation. They have absolutely no idea that the support agent just promised you a brand new replacement jacket. The WMS just says 'return.'
So the warehouse might just process it for a standard refund, or worse, put a defective jacket back in the repair queue without telling support.
Exactly. And meanwhile, the finance department sees a notification from the WMS and starts processing a credit note, which is entirely unaware that a replacement item is being shipped out. That completely messes up the inventory valuation for the accountants. Resolving an exception requires context. Is it a manufacturing defect? Did the customer clearly just wear it out? That context lives scattered across the CRM, the WMS, and the ERP. And the person forced to make the final call almost never has all that information in one place.
The Hidden Operational Cost Multiplier
Here's where it gets really interesting. We've established the mechanical failure, the systems are deeply siloed. But on a macro level, why does it matter? As long as the customer eventually gets their money or their new jacket, why should a company care if the internal process is a little disjointed?
The LightsOut.ai source introduces this concept of the hidden operational cost multiplier. It really comes down to what businesses choose to measure. The article points out that essentially every e-commerce company tracks its macro return rate.
Like the overall percentage.
They know that 15% of their total sales volume comes back. And some might track how fast they issue refunds to monitor customer satisfaction. But almost nobody measures the total operational cost. The actual labor.
So they're tracking the volume of the problem, but not the actual weight of it.
That's a perfect way to phrase it. And when you actually calculate that weight, it is very uncomfortable.
How bad is it?
A standard return, which theoretically should just require a few seconds of automated API calls, ends up consuming between 20 to 45 minutes of actual human labor.
Wait, 45 minutes for one jacket?
Up to 45 minutes, yes. If you scale that up, the labor cost starts to eclipse the profit margin of the item itself.
Easily.
And it is crucial to understand why it takes 45 minutes. It is not because warehouse workers or accountants are working slowly. It is because humans are acting as the APIs. They are the glue trying to hold incompatible software together.
The duct tape of the internet.
Exactly. A worker has to manually check the portal, copy a tracking number, paste it into the ERP, switch to a Slack channel to ask a support agent about a warranty, wait 20 minutes for a reply, and then manually adjust a line item in the accounting software.
So the coordination is what takes all the time.
The Six-Figure Silent Bleed
Let's look at the math the source provides because it really grounds this abstract problem in reality. If a mid-sized brand processes just 500 returns a month, which is a fairly modest number in e-commerce.
Very modest.
And each of those takes up to 45 minutes of fragmented human intervention. We are talking about 150 to 350 hours of hidden labor every single month. You are essentially paying for one or two full-time employees to do absolutely nothing but untangle data messes and copy-paste information across tabs.
And when you factor in fully loaded salary costs, benefits, warehouse overhead, that easily translates into a six-figure annual expense.
Hundreds of thousands of dollars, completely vaporized. Yet it doesn't show up on a single financial report.
And if we connect this to the bigger picture, this is exactly why the authors term it a silent bleed.
And this is acutely dangerous for venture capital-backed startups or really any retail brand operating on tight margins. Just imagine a board of directors meeting.
Setting the scene.
The executives are looking at a high-level dashboard. They see the return rate holding steady at 12%. They nod and say, okay, we are matching the industry average. We're fine. They are completely blind to the 45-minute labor multiplier attached to every single one of those 12%.
Because it's buried. It's hiding under general operations salaries, basic customer support budgets, standard warehouse hourly wages. It's just baked into the overhead.
Exactly. There is no neat little line item on their quarterly profit and loss spreadsheet that says 'data entry and coordination overhead for returns, $150,000.'
The bleed is totally invisible to the people steering the ship.
From Event to Flow: The Three-Step Fix
So if the financial cost is this severe, there has to be a structural fix. You can't just realize you are bleeding six figures a year on administrative friction and accept it.
You'd go out of business.
But if those shiny front-end customer portals aren't the magic bullet, what actually is? Do companies need to rip out their entire software stack and spend millions building a monolithic, all-in-one platform from scratch?
The good news is no, they don't. The source emphasizes that you can actually keep your portal. The portal is a great storefront, but the real fix requires a fundamental shift in operational philosophy. Moving from treating a return as an event to treating it as a flow.
An event versus a flow. Let's dig into that mechanic.
When you treat it as an event, you treat it as an isolated incident for each department. The portal has its event. The warehouse has its event. Finance has its event. It's totally episodic. Treating it as a flow means recognizing that a single return is one continuous data stream that has to cross all of those boundaries without stopping. And to achieve this flow state, the source outlines a very practical three-step architectural solution.
Step One: Automate the Obvious
So if the problem is that humans are acting as the APIs, the first logical step has to be removing the human from the standard uncomplicated scenarios, right?
You nailed it. Step one is precisely that. Automate the obvious. The vast majority of returns are standard. The item is in good condition, the customer selected a clear reason code like 'wrong size,' and it is well within the 30-day policy window. For these clean cases, companies need to implement middleware, like rules engines that bridge those APIs automatically.
So a system that basically says if condition A and condition B are met, just trigger the refund, update the WMS, and ping the ERP to create the credit note.
Yes. One continuous flow of data across five systems with absolutely zero manual steps. The moment the warehouse scans the barcode and confirms the jacket is physically there and undamaged, the automation takes over and closes out the transaction in seconds.
Step Two: Escalate Exceptions With Full Context
So that handles the clean stuff. But that only clears the deck. What happens when it's messy, like the broken zipper example we talked about earlier? You can't really fully automate a judgment call about a warranty claim or a potentially fraudulent return.
You can't. Which brings us to step two. Escalate exceptions with full context. When a return falls outside those clean parameters, a defect, a high-value item, or maybe a customer who habitually returns 80% of what they buy, the system must route it to a human.
A human has to look at it.
But the critical difference is how it is routed. It must be routed with all the necessary context aggregated into a single view. No more forcing the worker to hunt through four different browser tabs and Slack histories just to piece the story together.
So what does that look like in practice?
The source notes that LightsOut.ai has built systems tracking order status across 11 distinct operational points. And they present it in a clear visual timeline. So the person handling the broken zipper exception looks at one screen and instantly sees the order history, the original payment method, the specific warranty policy for that SKU, and the entire email thread from the support agent promising a replacement.
Having a visual timeline of the jacket's entire life cycle completely eliminates that 45-minute scavenger hunt for data.
It really does. You look at the timeline. You make an informed judgment call. You click a button. And the system executes the remaining steps.
Step Three: Measure the Entire Chain
So we have automating the obvious and escalating exceptions with complete context. What rounds out the strategy?
The third step is measure the entire chain. You have to stop relying solely on the portal's front-end metrics. It is just not enough to know how many return labels were printed.
Because it doesn't tell you the cost.
Exactly. You need to architect your system to track the total elapsed time from the moment the customer clicks 'return' to the moment the financial ledger is updated. You need to measure the friction itself.
Like, track the number of times a ticket is handed off between different employees.
Or track the error rates where the WMS and the ERP disagree on inventory numbers. And most importantly, calculate the true operational cost per return broken down by category. Because once you have that specific data, your operational priorities become glaringly obvious. You stop guessing.
You can look at the dashboard and say, wow, we are spending 80% of our manual support labor just resolving complaints about broken zippers.
So the solution isn't to hire more support staff. The solution is to source better zippers or fully automate the zipper replacement policy. You bring the invisible bleed into the light so you can actually bandage it.
You transition from firefighting individual problems to engineering a smoother flow.
The Deeper Question: What Happens When Returns Cost Nothing?
So what does this all mean? When we zoom out and look at this entire landscape, from the illusion of that 90-second customer experience to the harsh 45-minute back-end reality, the blind spots, the six-figure hidden cost. The ultimate takeaway from LightsOut.ai is really about operational maturity.
It really is. The e-commerce companies that will actually survive and scale don't view returns merely as an annoying cost center to be minimized. They treat the entire process as an operational flow that they must architect and control. It requires building a dedicated operational layer that sits behind the storefront portal. That operational layer handles the routing, enforces the automation rules, and aggregates context for those escalations. One return, one integrated flow, one comprehensive view.
And as the article wisely advises at the very end, build what fits your specific reality. Do not just buy a generic one-size-fits-all SaaS product that fits the broad market and hope it solves your unique internal bottlenecks.
It won't. You need a system mapped to your specific Rube Goldberg machine so you can finally dismantle it piece by piece.
This raises an important question though, and it is something worth considering from a broader consumer perspective.
Let's hear it.
We've spent this time analyzing how businesses need to optimize these back-end operations to save labor and money. But let's imagine a future where they succeed completely. If these systems become so perfectly optimized, so flawlessly automated, that the operational cost of processing a return essentially drops to zero, will businesses simply stop caring about high return rates?
That is a really interesting thought.
Because right now, a 15% or 20% return rate genuinely hurts their margins, mostly because of the massive labor costs we just discussed. But if the friction disappears and it costs them fractions of a cent in server compute power to process a return, if companies no longer feel the financial pain of returns, they have absolutely no incentive to discourage them.
That's true. And if brands stop discouraging them, will that indirectly train us, the consumers, to treat physical goods as completely disposable?
If returning that jacket is truly frictionless for both us and the corporation, do we stop being thoughtful about what we actually buy? Do we essentially turn the retail economy into a massive, consequence-free rental system where we are just borrowing items for a week rather than truly owning them?
It fundamentally changes our psychological relationship with physical objects. If the clunky Rube Goldberg machine is replaced by a perfectly silent, invisible conveyor belt, the very definition of a purchase might shift entirely.
Well, that is definitely something to chew on. Thank you all for joining us on this deep dive. The next time you're sitting on your couch, packing up a cardboard box, and dropping a return package in the mail, take a second to think about the complex, invisible chain reaction you are about to start. Until next time.
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