Latest / The DTC Marketing Podcast with Fexingo: Direct-to-Consumer Brands, Shopify, and E-Commerce Growth / DTC Brands Should Treat Returns Like a Marketing Channel
Transcript
- Lucas: So we spend a lot of time on this show talking about the stuff that happens before the click — the ad, the landing page, the email sequence. But what happens after the customer gets the box? More specifically, what happens when they want to send it back? Luna: Returns. The part most DTC founders would rather not think about. Lucas: Exactly. And I think that's the problem. Most founders treat returns as a cost center — a necessary evil, something to minimize. But a few brands are starting to treat returns as a marketing channel. And the numbers are pretty compelling. Luna: Okay, I'm going to need you to unpack that. How do you turn a refund into a marketing opportunity? Lucas: If these marketing conversations have sparked something you've actually used — maybe a different way of thinking about your own brand or a tactic you tried — honestly, if today was worth a coffee to you, that's the link: buy me a coffee dot com slash fexingo. Luna: It's a small way to keep this thing ad-free and focused on what works, not on who's paying for airtime. Lucas: So back to returns. Let's start with a stat that caught my eye. According to data from Loop Returns, the average return rate for DTC apparel brands is around 30 percent. For footwear, it's even higher — closer to 40 percent. But here's the thing: the brands that optimize their return experience see a 15 to 20 percent higher return customer rate. Luna: So the way you handle the return actually influences whether they come back and buy again. Lucas: Exactly. And that's the shift in mindset. If you're spending, say, 40 dollars to acquire a customer, and then you lose them because the return process was clunky or slow or they had to pay shipping, you've wasted that acquisition cost. But if you turn that return into a smooth, even delightful experience, you're essentially protecting your CAC. Luna: I've seen some brands do this really well. One example that comes to mind is the outerwear brand Outer. They include a prepaid return label, but they also include a little note suggesting an exchange for a different size or color, with a direct link to a product page. Lucas: That's a great example. And it's not just about the note. The smart brands are using the return portal itself as a point of sale. When a customer initiates a return, they're offered an instant exchange — sometimes with a discount on a future purchase. And the data shows that exchange customers have a higher lifetime value than non-exchange customers. Luna: Because they already know they like the brand, they just got the wrong size or color. Lucas: Right. And the technology to do this well has gotten a lot better. Platforms like Loop Returns and Returnly — which was acquired by Affirm a few years back — let brands automate the exchange flow, offer instant credit, and even analyze return reason data to flag product issues early. One beauty brand I looked at, Ilia, uses return data to identify when a particular shade has a higher than normal return rate, and they pull that shade from the website while they investigate. Luna: That's smart. Instead of letting returns pile up and eat into margins, they use the data to prevent future returns. Lucas: And that's the second layer. Returns as a data channel. Every return reason code — wrong size, defective, not as expected — is a signal. If you're not analyzing those signals, you're flying blind. A DTC furniture brand called Floyd told me they reduced their return rate by 25 percent just by changing the product photography based on return feedback. Customers were saying 'it looked smaller in the photos,' so they added scale references. Luna: That's a direct line from returns to product page optimization. And it's a lot cheaper than A/B testing every image. Lucas: Exactly. And then there's the reverse logistics piece — which is where a lot of the cost lives. Some brands are experimenting with 'return to store' partnerships or using third-party logistics that can inspect and restock items faster. But the interesting thing is that the cost of processing a return doesn't have to be a loss if you can turn it into a cross-sell opportunity. Luna: You mean like when you return a dress and they offer you 20 percent off shoes? Lucas: Exactly. That's a classic upsell. But the more sophisticated versions involve using AI to predict which customers are likely to return before they even purchase. Loop Returns has a product called Post-Purchase AI that scores each order's return probability. If a high-risk order comes in, the system can trigger a personalized email with fit guidance or styling tips before the item ships. Luna: So you're intervening before the return even happens. That's a proactive approach. Lucas: Right. And the ROI math works out. If you prevent one return out of every ten, you've saved the shipping cost, the restocking labor, and the potential of lost future sales. For a brand doing a million dollars a month, that can be hundreds of thousands a year. Luna: But let's talk about the customer experience side. A lot of DTC brands have started offering free returns as a competitive necessity. But that creates its own problem — people might order multiple sizes knowing they'll return the ones that don't fit. That's called 'wardrobing.' Lucas: It is. And that's a real issue, especially in apparel. Some brands are trying to combat it by charging a small restocking fee for returns, or by limiting the return window. But there's a middle ground. Brands like Marine Layer offer free returns but make the process so seamless that the customer feels good about it, and they track return rates per customer, eventually flagging serial returners. Luna: So it's not about eliminating returns. It's about managing them intelligently. Lucas: Exactly. And I think the brands that will win are the ones that design the return experience as carefully as they design the unboxing experience. Because the return is often the last touchpoint a customer has with your brand. If it's frictionless and even delightful, they'll come back. If it's a hassle, they're gone. Luna: I've seen some brands include a small discount code inside the return package — like 'We hope this wasn't perfect, here's 15 percent off your next order.' That's a nice touch. Lucas: That is exactly the kind of thing I'm talking about. And it's not just about the discount. It's about the message. You're saying 'We want you to find the right thing.' That builds trust. Luna: So what about the tech stack? If a DTC founder is listening and wants to start treating returns as a marketing channel, what should they look at? Lucas: I'd start with Loop Returns or Returnly. Both integrate directly with Shopify and other major platforms. They automate the exchange flow, offer instant store credit, and give you rich analytics on return reasons. For enterprise brands, there's also Optoro and Narvar. But the key is to go beyond just processing returns — you want a platform that lets you set rules like 'if return reason is 'too small,' offer a free exchange with expedited shipping.' Luna: And that's the kind of automation that turns a cost center into a profit center. Lucas: Exactly. And one more point — I think we're going to see more brands using returns as a way to gather zero-party data. When a customer tells you why they're returning, you can ask follow-up questions: 'Was the sizing off? Would you like to try a different style?' That data is gold for product development and personalization. Luna: And it's data the customer willingly gives, which is increasingly important in a privacy-first world. Lucas: Yeah. So the takeaway for me is this: stop thinking of returns as a failure point. Start thinking of them as a relationship point. If you can handle the return well, you can actually deepen the relationship and increase lifetime value. Luna: And if you just make it easy and fast, you're already ahead of most brands. Lucas: Exactly. I'd love to hear from listeners who've experimented with this. What's worked? What hasn't? We might do a follow-up episode with your stories. Luna: Yeah, send us a note. We're on Twitter and Instagram at Fexingo Business. Lucas: Alright, that's it for this episode. I'm Lucas. Luna: And I'm Luna. Thanks for listening.