Bailey Newton

“It feels like texting a friend.” That’s how one of our partners described @fratereturns' support. Not a ticket, not a bot, not “we’ll get back to you in 2–3 business days.” A real human, on Slack, solving any issues with you. We truly believe support is not just a department. It’s part of the product and can separate you from the rest. Our partners get: - Direct Slack access, meaning no ticketing system - Our Director of Support, Jim (ex-Shopify), is in direct contact - Some of our engineers are in the channel, as they’re the ones solving the technical issues - You can huddle us. Ping us. Message us - All product updates go into your channels. Nothing is opaque - Constant feedback back and forth Is it scalable? Not really. Is it hard work? Absolutely. But is it worth it? No doubt. We built Frate to solve returns. But what keeps brands around? It’s trust. And trust is built in conversation.

@MacCoyMerkley frate.com. Migrated Caraway, Monos, Honeylove and others this year from some of the expensive alternatives

Is there a returns software that doesn't cost 100k year????

@eliweisss Let’s go!

I’ll be in Toronto for a few hours this Wednesday! Pls join me. We’ll be chatting AI in ecom: → Where AI creates biggest CX impact → Live examples from brands scaling personalized experiences → Workflow changes that move the needle events.gorgias.com/gorgiasaiworks…

@andrewjenningsx @shipessential

DTC gang. What's the best US 3PL these days? Small and cost efficient. I don't want a big name. Thank you please

@johnhickey1970 @austinkreinz

All right. 3pl. I’m trying to pick a Midwest 3pl We ship about 8k orders a month out of la. So we figure half that from Midwest but we grew 94% this month compared to June of 2024 What should I know about three PL’s folks ?

@ArijanJanes Monos

You should be studying winning brands every single day. Here are for inspo: 1. Oats Overnight 2. True Classic 3. Norse Organics 4. Javy 5. PetLabCo 6. Earth Breeze 7. Solawave 8. Hydrant 9. Comfrt 10. Omnilux 11. Buoy 12. Caraway

@mprkhrst Early access

Today, we’re announcing Antimetal’s $20M Series A. Writing code is no longer the hard part. Maintaining it is. We’re automating everything that happens after you deploy. We have 60 spots available. Reply for early access.

The Frate Returns engineering team has been shipping fast, and often. And we're hiring another Software Engineer to help move even quicker. Here's a snapshot of what we released to our merchants in the last 6-weeks: ✅ "Action mode" to review returns quicker ✅ Fully revamped analytics dashboard ✅ 3x'ed portal speed ✅ Added context for AI image verification ✅ Advanced dashboard filtering with full search ✅ Create or edit return labels within dashboard ✅ Six new workflow conditions and four new actions ✅ Customize email font, color, reply-to ✅ Gift returns fully supported ✅ Five new warehouse integrations ✅ Enhanced Two Boxes integration If you want to build tools merchants actually use every day, apply here: lnkd.in/ewDiW_CA

Most return policies are designed for customers. Almost none are designed for the business. Let me explain. If a product costs you $40 landed and sells for $70, you’re making ~$30 in margin. Now imagine this: - The customer returns it. - You pay $8 in return shipping. - Another $4 to process it. - It’s been opened, so it’s no longer resellable at full price. - You refund the full $70 anyway. You didn’t just lose the margin. You’re now down $22 on that order. This happens thousands of times across mid-sized brands every year. And nobody audits it. Because it’s “just part of doing business.” Because returns are siloed from finance. Because ops teams are drowning. Returns are treated like a CX policy. But they’re a P&L lever. And a dangerous one when left unchecked. Smart brands are starting to rethink this. Not by being stricter. But by being smarter about which returns are worth accepting in the first place.

Return fraud doesn’t look like fraud. It looks like: “Ordered two sizes to see which one fits.” “Worn once, tags still on.” “Didn’t like it, but the box opened like a crime scene.” “Claimed never delivered—but tracking says otherwise.” Most brands don’t call this fraud. They call it “normal.” Because it’s uncomfortable to admit that some of your best-paying customers are also quietly bleeding your margins. But here’s the truth: Every brand has serial returners. And most systems can’t see them. Payment fraud? Sure. But returns fraud? It slips through because it's behavioral, not transactional. The top operators I know don’t just tighten policies. They’re building quiet, behind-the-scenes defenses. Tools that catch patterns, not just exceptions. That’s what we think about all day at Frate. How do you filter out the 1% of customers causing 30% of your return losses without making life worse for the other 99%? I'd love to learn how you're tackling this today.

@debgotwired @Shopify @gilgNYC @dovsmail @ShopifyDevs Awesome man!

On my way to Toronto for @Shopify Editions and it's an honor to host a roundtable with @gilgNYC and @dovsmail on building apps with AI. Thanks for this amazing opportunity @ShopifyDevs 🙌

Returns are breaking ecommerce ops, and no one’s talking about it. Before building @fratereturns, I assumed returns were just a logistics cost center. I was wrong. Returns are a data blind spot, a customer experience trap, and a margin killer, all rolled into one. Here’s what I’ve learned working with high-growth brands: 1. Most return data is garbage. Brands don’t know why products are being returned, just that they are. “Too big” could mean 10 different things. 2. The returns workflow is duct-taped. WMS, 3PL, customer support tools, and frontend return portals don’t talk to each other. Ops teams are stitching spreadsheets weekly just to make sense of what’s happening. 3. Returns are rarely challenged. Even obviously fraudulent or damaged returns get accepted. Why? Because the default playbook is: “Take the hit. Save the customer.” I’m building Frate to solve this; not by automating labels, but by helping brands avoid bad returns altogether. If you’re stuck refunding what should’ve been rejected or buried under RMA chaos, we should talk.

Returns are breaking ecommerce ops, and no one’s talking about it. Before building @fratereturns, I assumed returns were just a logistics cost center. I was wrong. Returns are a data blind spot, a customer experience trap, and a margin killer, all rolled into one. Here’s what I’ve learned working with high-growth brands: 1. Most return data is garbage. Brands don’t know why products are being returned, just that they are. “Too big” could mean 10 different things. 2. The returns workflow is duct-taped. WMS, 3PL, customer support tools, and frontend return portals don’t talk to each other. Ops teams are stitching spreadsheets weekly just to make sense of what’s happening. 3. Returns are rarely challenged. Even obviously fraudulent or damaged returns get accepted. Why? Because the default playbook is: “Take the hit. Save the customer.” I’m building Frate to solve this; not by automating labels, but by helping brands avoid bad returns altogether. If you’re stuck refunding what should’ve been rejected or buried under RMA chaos, we should talk.

Returns are breaking ecommerce ops, and no one’s talking about it. Before building @fratereturns, I assumed returns were just a logistics cost center. I was wrong. Returns are a data blind spot, a customer experience trap, and a margin killer, all rolled into one. Here’s what I’ve learned working with high-growth brands: 1. Most return data is garbage. Brands don’t know why products are being returned, just that they are. “Too big” could mean 10 different things. 2. The returns workflow is duct-taped. WMS, 3PL, customer support tools, and frontend return portals don’t talk to each other. Ops teams are stitching spreadsheets weekly just to make sense of what’s happening. 3. Returns are rarely challenged. Even obviously fraudulent or damaged returns get accepted. Why? Because the default playbook is: “Take the hit. Save the customer.” I’m building Frate to solve this; not by automating labels, but by helping brands avoid bad returns altogether. If you’re stuck refunding what should’ve been rejected or buried under RMA chaos, we should talk.

Returns are breaking ecommerce ops, and no one’s talking about it. Before building @fratereturns, I assumed returns were just a logistics cost center. I was wrong. Returns are a data blind spot, a customer experience trap, and a margin killer, all rolled into one. Here’s what I’ve learned working with high-growth brands: 1. Most return data is garbage. Brands don’t know why products are being returned, just that they are. “Too big” could mean 10 different things. 2. The returns workflow is duct-taped. WMS, 3PL, customer support tools, and frontend return portals don’t talk to each other. Ops teams are stitching spreadsheets weekly just to make sense of what’s happening. 3. Returns are rarely challenged. Even obviously fraudulent or damaged returns get accepted. Why? Because the default playbook is: “Take the hit. Save the customer.” I’m building Frate to solve this; not by automating labels, but by helping brands avoid bad returns altogether. If you’re stuck refunding what should’ve been rejected or buried under RMA chaos, we should talk.

Returns are breaking ecommerce ops, and no one’s talking about it. Before building @fratereturns, I assumed returns were just a logistics cost center. I was wrong. Returns are a data blind spot, a customer experience trap, and a margin killer, all rolled into one. Here’s what I’ve learned working with high-growth brands: 1. Most return data is garbage. Brands don’t know why products are being returned, just that they are. “Too big” could mean 10 different things. 2. The returns workflow is duct-taped. WMS, 3PL, customer support tools, and frontend return portals don’t talk to each other. Ops teams are stitching spreadsheets weekly just to make sense of what’s happening. 3. Returns are rarely challenged. Even obviously fraudulent or damaged returns get accepted. Why? Because the default playbook is: “Take the hit. Save the customer.” I’m building Frate to solve this; not by automating labels, but by helping brands avoid bad returns altogether. If you’re stuck refunding what should’ve been rejected or buried under RMA chaos, we should talk.

Returns are breaking ecommerce ops, and no one’s talking about it. Before building @fratereturns, I assumed returns were just a logistics cost center. I was wrong. Returns are a data blind spot, a customer experience trap, and a margin killer, all rolled into one. Here’s what I’ve learned working with high-growth brands: 1. Most return data is garbage. Brands don’t know why products are being returned, just that they are. “Too big” could mean 10 different things. 2. The returns workflow is duct-taped. WMS, 3PL, customer support tools, and frontend return portals don’t talk to each other. Ops teams are stitching spreadsheets weekly just to make sense of what’s happening. 3. Returns are rarely challenged. Even obviously fraudulent or damaged returns get accepted. Why? Because the default playbook is: “Take the hit. Save the customer.” I’m building Frate to solve this; not by automating labels, but by helping brands avoid bad returns altogether. If you’re stuck refunding what should’ve been rejected or buried under RMA chaos, we should talk.

We don't make many customer announcements anymore, but we felt this one was too important not to mention. We're thrilled to welcome @MonosTravel as our newest @fratereturns partner. Monos has quickly become a legendary Canadian brand and is one of the fastest-growing travel lifestyle names in the world. Previously using a different returns solution, Monos made the switch to Frate to help eliminate returns fraud, streamline exchanges, and unify in-store and online returns. We’re excited to build with the incredible Monos team and support their continued growth as a global leader in the travel space!

Last week, I posted about this new concept called "Return Value Efficiency" (RVE), our new North Star metric at @fratereturns. RVE = (Retained Revenue + Generated Revenue) / (Returned Revenue + Return Costs) It tells you how much value you’re squeezing out of your returns. The closer to 100%, the better. But a lot of people asked: “What’s the fastest way to improve RVE?” One lever we’re focused on right now is what we call Exchange Efficiency, which helps move the needle on the Retained Revenue metric. Here’s the idea: Let’s say "size too big" or "too small" makes up for 70% of return reasons. But only 25% of your customers actually exchange for a different size. That leaves a 45% gap of people who likely still wanted the product, but didn’t follow through with an exchange. We call that the Delta. And the smaller your Delta, the better your return experience is at retaining revenue. Of course, the Delta will never be zero, as sizes could be out of stock or they could choose that return reason by default, but decreasing that Delta as much as possible is the goal. So we’ve started benchmarking Exchange Efficiency across all our brands. Our average Delta? 29%. We do this through simplifying the variant exchange experience (fewer clicks the better), and intelligently recommending products to customers. As Sam Beqaj (our Head of Partnerships) says in his demos, if a customer wants a new size, "JUST GET THEM A NEW DAMN SIZE!" I'd urge brands to take a look at their analytics page. Pull up your return reasons and your exchange %, and see what that Delta is. And if it's higher than our average, I'm here to chat and show you what we're doing to close that gap.

@debgotwired Thanks!

@baileyatfrate Agreed!

The warehouse shouldn’t be your returns department. But for most ecommerce brands—it is. Here’s the pattern I see over and over again: - Customer sends something back. - Warehouse receives it. - Only then do you realize it’s damaged, unsellable, or not even the right product. - The ops team is left scrambling, refund already processed, margin gone. By the time you inspect the return, it’s too late. The damage—literally and financially—is already done. Returns aren’t just a reverse logistics problem. They’re a trust-at-scale problem. You’re trusting a random customer to: - Follow instructions - Repack it correctly - Not game the system In most cases, you have zero line of defense until it shows up in a bin two weeks later. There’s a better way: bring intelligence to the front of the return flow (with tools like @fratereturns). - Catch patterns. - Score risk. - Flag edge cases before anything ships back. Not with rules—but with real-time signals and smarter systems. The warehouse should be the last resort. Not the first checkpoint.