Managing Returns and Exchanges

Killer graph. Out of the £130 billion online non-food purchases we make in the UK, £27 billion of them get sent back to retailers. Our research with ZigZag Global shines a spotlight on the significant challenge online returns cause in the industry, focusing on those consumers who consistently and intentionally over-order - the "serial returners". Key stats ➡️ Around 11% of online shoppers are serial returners (frequently over-ordering with the intention of returning many items) ➡️They account for 24% of all online returns ➡️Serial returners send back, on average, £1,400 worth of online orders per year, compared with an average of £650. ➡️ This amounts to £6.6 billion of returns. ➡️ Almost three-quarters of serial returners are under the age of 45, and they return more than 42% of all their orders. A 1/4 of serial returners admit to over-ordering just to reach a minimum order value (often to trigger free delivery) only to return goods they had no intention of keeping. The same proportion also said they had returned items after finding them cheaper elsewhere or on promotions. While 18% admitted to returning items having already used them for a short period. There is no silver bullet here that is going to fix this issue for retailers. A nuanced understanding of specific triggers and barriers is essential to effectively target returners through pricing and returns options. 💥 For many boardrooms debating whether they should charge for returns, my thoughts are: 💥 The returns equation transcends simple binary choices between free or paid. Retailers must architect differentiated returns propositions that align commercial realities with customer lifetime value. Smart retailers will segment their returns strategy by customer profitability metrics, leveraging AI to identify purchase patterns that predict long-term value. This enables dynamic returns pricing that protects margins while fostering relationships with truly valuable customers. The goal isn't to punish returns – it's to price them according to their true cost to serve, while rewarding profitable shopping behaviours. There's also a paradox at play where customer acquisition costs are optimised but customer profitability is compromised. Many retailers are essentially subsidising unsustainable shopping behaviours at the expense of margin, unknowingly targeting customers they could do without. The real opportunity lies in leveraging returns data as a predictive indicator of customer profitability. By applying advanced analytics to returns patterns, seasonal purchasing behaviours, and cross-category browsing and mining deep behaviour insights, retailers can enable proactive intervention before profitability erodes. This shifts the conversation from universal policies to personalised solutions that can turn returns from a pure cost centre into a strategic lever for customer engagement and loyalty. Full research is available to download here ⬇️ https://lnkd.in/e5paRNWC

Remember this for 2026  ⬇️ One of the clearest signals in commerce right now isn’t speed or conversion. It’s returns. Returns are expensive. They’re operationally messy. And they’re quietly one of the biggest environmental costs in retail: up to 24 million metric tons of CO2 emissions are attributed to ecommerce returns each year.  Most returns don’t happen because people shop carelessly. They happen because people are forced to decide without enough context. Last year, while growing Phia's user base to more than 900K users, this became hard to ignore for Sophia Kianni and me. When shoppers slow down, compare properly, and understand why something fits them, behavior changes. We’ve seen this show up clearly in the data. Phia users don’t buy the first time they’re shown something – they revisit, reassess, and buy when it feels right. And when they do, returns drop to under 12%, materially below typical apparel benchmarks. And resale insights play a big role here. Phia has driven over 98k secondhand purchases, contributing to an ~80% lower carbon impact compared to buying new. Seeing how an item holds value over time changes how people think about risk, longevity, and regret – not just price. Truth: Returns reduction isn’t about stricter policies or faster fulfillment, but about improving the quality of the decision before checkout. That’s the work ahead this year.

𝗛𝗲𝗿𝗲 𝗶𝘀 𝗮 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗿𝗲𝘃𝗶𝗲𝘄, 𝘄𝗵𝗲𝗻 𝗜 𝗱𝗶𝗱𝗻'𝘁 𝗴𝗲𝘁 𝘁𝗼 𝘂𝘀𝗲 𝘁𝗵𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁! So, this is what happened. For the first time, I ordered shoes online. Now, when it comes to shoes, I prefer a store for the look and fit factor. But this time I broke the trend! Let's be honest - their product video was pretty persuasive. 😜 So I ordered this pair of loafers from Yoho lifestyle, a young D2C brand. I ordered a 9, but that turned out to be too big for me. I placed an email request for an exchange. Got a reply on the same day to share a couple of pictures. After I did that, a return was booked. Within 2-3 days, the shoes were picked, and a pair of size 8 shoes were dropped at my place. Now, this again did not fit well for me. So, once again I sent out an email with a couple of pictures. The reply came within a few hours that a pickup had been booked. Again, within 2 days, the shoes were picked up. They informed me that they didn't have a size between 8 and 9, and hence a refund is being issued. Within a few hours, the complete refund hit my account. End of story? Not really! Because I will definitely check out their other products and if I get the same service, maybe even recommend the brand because I have the trust that if there is a concern, there are a group of people who are prompt, responsive and efficient in managing it. One of their products may not have been right for me, but they have got a crucial customer touchpoint covered and that makes me trust them. That's the thing with 𝗥𝗲𝘁𝘂𝗿𝗻𝘀 𝗮𝗻𝗱 𝗥𝗲𝗳𝘂𝗻𝗱𝘀. It is a very underrated element of the customer journey map, but it can make or break your customer relationship. Here is an easy framework (I call it A.S.R!) to optimize it: - - 𝗔𝗻𝘁𝗶𝗰𝗶𝗽𝗮𝘁𝗲: Be proactive about predicting possible concerns that may prompt customers to seek an exchange or refund. You may not get it 100% right but get started and keep updating it. - 𝗦𝘆𝘀𝘁𝗲𝗺��𝘇𝗲: Put in place clear systems and processes for returns and refunds. Empathy, Transparency, and Simplicity should be the three main areas of focus while designing the system. - 𝗥𝗲𝘀𝗽𝗼𝗻𝗱: Be prompt with a response, esp when it is regarding a return or a refund. Your customers are mostly in a triggered or at least unhappy mood when booking a return/ refund. Every minute delayed leads to stress and possible escalation. A well-crafted Return & Refund strategy can not only salvage your customer relationship but also elevate your brand. If you found this useful, consider re-posting, and help a fellow business owner nail their return strategy! 🧡 #customercentricity #customerexperience #customerservice #customerjourney #vinaypushpakaran

Indian Shoppers Love Free Returns — Brands Are Paying the Price (₹370 billion) Let’s break it down step-by-step: 1. The Big Picture GMV of Indian E-Commerce: ~$75 billion Average Order Value (AOV): ₹2,000 Estimated total number of orders/year: = $75B × ₹83/USD ÷ ₹2,000 ≈ 3 billion orders annually 2. Market Split by Category Let’s divide these orders by category: Apparel & Footwear: 50% share → 1.5 billion orders Electronics: 30% share → 0.9 billion orders Others (Home, Beauty, etc.): 20% share → 0.6 billion orders 3. Return Rates by Category - Apparel & Footwear: 25% - Electronics: 10% - Others: 20% Using category-level volumes and return rates: • Apparel: 25% of 1.5B = 375M • Electronics: 10% of 0.9B = 90M • Others: 20% of 0.6B = 120M Total Returns/year = ~585M (rounded to 600 million) - Overall return rate ≈ 20% 4. Cost Breakdown: 4 Major Return Costs a. Reverse Logistics • Assumption: ₹200/order • Cost = 600M × ₹200 = ₹120 billion This includes pickup, handling, transfer — and is usually free for the customer. b. Damaged Goods • Assumption: 20% of returns are unsellable • 20% × 600M = 120M items lost If the average inventory cost is 40% of AOV = ₹800 Cost = 120M × ₹800 = ₹96 billion → Rounded to ₹100B c. Faulty Goods & Reselling • 50% of returns need repair or markdown • 50% × 600M = 300M items Refurbishing/resale cost = 25% of AOV = ₹500 Cost = 300M × ₹500 = ₹150 billion 5. Total Estimated Cost - Reverse Logistics: ₹120B - Damaged Goods: ₹100B - Resale/Repair: ₹150B Total = ₹370 billion (~$4.5 billion) That’s 6% of the GMV being wiped out annually. But as a percentage of revenue (not GMV)? It’s much higher. Most platforms operate on thin take-rates (10–15%). So for every ₹100 earned, returns alone can eat up ₹30–60 40–45% of returns in fashion are driven by size and fit issues Most customers “bracket” — ordering multiple sizes with the intent to return Every return adds cost: pickup, re-inspection, repackaging, resale (if possible) If unsellable, the product is written off, instantly impacting margins Free returns = more orders, lower friction But they also mean: - Higher logistics volume - Lower inventory turnover - Shrinking profitability Platforms are responding: [1] Return fees for chronic returners [2] Shorter return windows (7–10 days) [3] Store credit incentives instead of full refunds [4] Free returns as loyalty perks, not a blanket policy Returns Aren’t the End — They’re a Second Market The refurbished goods market is booming: - Flipkart’s 2GUD, Amazon Renewed - $20B+ market projected in India over the next 6 years - Electronics, home appliances, and even fashion are seeing resale traction Returns are being converted into opportunity through resale, refurbishment, and recommerce.

1 under rated D2C hack no one is talking about. Disclaimer: only use this if you’re 100% sure your product delivers. When we launched Dr. Vaidya's by RPSG Group, I was obsessed with one question: “How do we get a first time customer to trust Ayurveda again?” Because in wellness, especially skincare or health, the biggest battle isn’t the product. It’s trust. And that’s why I’ve always respected founders who are willing to say: “Try it and if it doesn’t work, take your money back.” It gives the customer that last leg of validation to flip over the edge. I saw this mindset in action recently with Personal Touch Skincare on Shark Tank India. They left without a deal. But instead of doubling down on explanation, they went back and doubled down on conviction. They launched a no questions asked money back guarantee on their hero SKUs. The founder said he was confident on the results. And, it worked because: 1. It reduces friction. As consumers, we’re loss averse. Take that fear away, and people are more likely to try. We feel losses twice as intensely as gains (Prospect Theory). 2. It reinforces product quality. You can’t afford a refund model unless your product does what it says. 3. It deepens belief. When something works better than expected, and the customer had the option to return it, they become evangelists. And they’re not alone. I’ve seen brands across beauty, wellness and even food try this in India and around the world. What all of them understood is this - In saturated markets, trust outperforms targeting. It costs much less than a performance ad. If your product delivers, belief becomes your biggest moat. Have you bought something because of a money back guarantee? #D2C #strategy #skincare #business

Working in D2C fashion? Then you already know the two kinds of returns we deal with: 1. The honest ones (wrong fit, wrong size) 2. The “used it, flaunted it, now returning it” kind Reverse logistics is a not a blessing especially for new brands trying to win trust, It’s a double-edged sword! Yes, some argue that a strict return policy filters out the wrong audience. But here’s the truth no one likes to admit: It also repels the right audience- the ones who are genuinely unsure about fit, comfort, or styling. And in fashion, where every brand’s sizing chart is basically a new size chart, what do you expect from customers? If your return policy makes people feel like they’re on trial, you’re not protecting the brand, you’re burning bridges with potential loyalists. There’s no perfect solution here, but we need to find better middle grounds clearer sizing support, flexible returns. Because trust isn’t built on one purchase. It’s built on what happens after the purchase. After having worked with 12+ lifestyle brands let me share some suggestions: 1. Smarter Sizing Support Use size recommendation tools (AI-based if possible) that learn from past customer purchases and returns. Shopify has multiple such apps. Add real customer photos & UGC reviews that mention fit; peer-led guidance always trumps size charts. 2. Tiered Return Policies a) Reward repeat/genuine customers with more flexibility. b) New customers may have a slightly stricter window or policy but with clear communication, not confusion. 3. Fraud Pattern Tagging Track & flag repeat offenders, people who return 90% of their orders with wear signs. Don’t punish everyone for a few. Razorpay shopflo GoKwik all these guys have Fraud flagging feature in-built in them, please utilize. 4. Post-Purchase Engagement Use WhatsApp or email nudges asking “Need help with your fit?” or “Would you like to exchange instead of return?” you’d be surprised how many just need support, not a refund. TRAIN your customer support to converse well and solve the sizing problem. Eg; Size 40 for a kurta isn't the body measurement but a garment measurement; state this clearly and explain what it means to your team and to your customers. Unit economics in D2C is hard, I do understand but basics is something we can follow before calling D2C a lost cause or a leaky channel. #ecommerceinsights #fashionstartups #reverselogistics #customerexperience #returnpolicy #D2CMarketing

The returns data domino effect is real inside of brands. Many brands attribute high return rates purely to customers ordering multiple sizes. The reality is more complex. By diving deep into returns data, you uncover insights that will change how you think about returns. And what strategies you implement to reduce them. Common trends include: 👉 SKU-Level Reporting: Identifying products with excessive return rates can reveal issues with sizing, quality, or design. For instance, if a specific dress size is returned 65% of the time, it's a clear signal to revisit sizing charts or quality control processes. 👉 Stock Optimization: With returns taking up to 21 days to process, especially for international orders, having visibility into "stock in transit" is crucial. This data can help prevent unnecessary order cancellations and improve inventory management. 👉 Customer Behavior Analysis: By analyzing return patterns, brands can distinguish between serial returners and genuine product issues, allowing for more targeted solutions. 👉 Accurate Financial Reporting: Layering returns data over sales data provides a true picture of margins and profitability, essential for making informed marketing and business decisions. 👉 Cost Calculation: Understanding the average cost of returns, including courier fees and processing time, is vital for developing effective return policies and pricing strategies. We go deep on how to use data to analyse your return data in part 4 of our Paid Returns series in the Commerce Thinking newsletter. Read and subscribe below: https://lnkd.in/etvrkvWY

𝗛𝗼𝘄 𝟮𝟬–𝟯𝟬% 𝗥𝗧𝗢 𝗶𝘀 𝗦𝗶𝗹𝗲𝗻𝘁𝗹𝘆 𝗗𝗲𝘀𝘁𝗿𝗼𝘆𝗶𝗻𝗴 𝗩𝗮𝗹𝘂𝗲 𝗳𝗼𝗿 𝗚𝗹𝗼𝗯𝗮𝗹 𝗕𝗿𝗮𝗻𝗱𝘀 𝗶𝗻 𝗜𝗻𝗱𝗶𝗮 Did you know that 17.6% of all #ecommerce orders in India are returned to origin (RTO)? In high-risk categories like #fashion and #footwear, that rate can soar to 30–40%—and researchers warn brands could lose $20–30 billion in #revenue to returns by 2025 But returns aren't just refunds—they’re a hidden tax on growth Returns often stem from size or fit issues in apparel/footwear, accounting for about 40% of return cases The average return rate hovers around 17% across categories, resulting in losses of approximately ₹2 lakh crore annually. Amazon India alone refunded ~₹5,000 crore in 2024, Flipkart ~₹3,000 crore, and Myntra ~₹1,000 crore These numbers are especially painful for international brands entering India. Without local context, returns can obliterate forecasted margins before a campaign even launches 𝗪𝗵𝗮𝘁’𝘀 𝗗𝗿𝗶𝘃𝗶𝗻𝗴 𝗥𝗧𝗢 𝗶𝗻 𝗜𝗻𝗱𝗶𝗮? #COD Spikes: Nearly 75% of Indian e-commerce is COD-driven; RTO on COD can be 3× higher than prepaid orders. Fake or Suspicious Orders: Rampant in unverified flows—with many brands reporting RTOs as high as 50% from new audiences. Remote #Delivery Challenges: Logistics failures in Tier 2/3 zones further push returns unless addressed proactively. 𝗛𝗼𝘄 𝗙𝗼𝘅&𝗔𝗻𝗴𝗲𝗹 𝗛𝗲𝗹𝗽𝘀 𝗚𝗹𝗼𝗯𝗮𝗹 𝗕𝗿𝗮𝗻𝗱𝘀 𝗗𝗲-𝗥𝗶𝘀𝗸 𝗜𝗻𝗱𝗶𝗮 𝗘𝗻𝘁𝗿𝘆 1️⃣ Build #Prepaid Preference – COD kills margins. We design nudges like partial prepay, upsell incentives, and intent tests to shift buyers to prepaid. 2️⃣ Data-Driven Filters – High-risk pin codes drive 3× RTO. We use geodata to dial down COD in expensive return zones. 3️⃣ Warm Confirmations – WhatsApp/bot re-confirmations cut RTO by 40–60%, while building trust. 4️⃣ Size & Fit Confidence – For fashion/footwear, we add fit videos, try-ons, and reviews to slash expectation gaps. 5️⃣ Smarter Fulfilment – Shipping from Zone A vs. Zone C saves ₹12 per order and reduces RTO up to 3×. India’s e-commerce is booming—$160B GMV by 2025 with 342M active buyers—but RTO is the silent margin killer. So the real question for global brands isn’t: “How do we launch in India?” It’s: “How do we launch in India without bleeding margins?” 👉 Let’s talk if you’re ready to build a launch strategy that keeps your growth sustainable. Apppl Combine – AI, Marketing & Advertising Agency Brandwand – Marketing & Advertising Agencyy300FramessRanjan Das TalkssRaashi R Daass #IndiaMarketEntry #GlobalBrands #BusinessExpansion #MarketEntryStrategy #FoxAndAngel #EcommerceIndia #ConsumerInsights #CrossBorderGrowth #DigitalTransformation #RetailInnovation #HighGrowthMarkets #EmergingMarkets #GoToMarket #IndiaBusiness #MarketEntryAdvisory #CMOStrategy #GlobalExpansion #BrandGrowth #SustainableGrowth #InternationalBusiness

🌐 Behind Every Click is a Story I Let the Data Tell It. 📊✨ In a world where e-commerce brands pour thousands into campaigns and still struggle with cart abandonment, product returns, and low retention, the real question isn’t “What happened?” , it’s “Why did it happen?” and “How do we fix it?” 🔎 That’s where data comes in. 📈 And this is where Power BI becomes more than just a dashboard, it becomes a lens for clarity. Over the past few weeks, I built a full-scale, interactive e-commerce performance dashboard, touching every point from marketing campaigns to customer satisfaction. The goal? Make sense of the chaos. Turn complexity into simplicity. Drive action. 🧠 Here’s What I Discovered: ✅ Marketing Channels Instagram drove the most engagement, but Email had the best ROI. Billboard Ads, though expensive, performed poorly �� proof that visibility ≠ value. ✅ Cart Abandonment Patterns Over 15% of carts were abandoned. The biggest culprit? Cash on Delivery (COD) users. Fashion orders also had the highest failure and return rates — a clear sign to revisit fulfillment strategies. ✅ Customer Insights That Matter Females aged 35–44 were power buyers across categories Credit Card and PayPal users had smoother journeys. ✅ Returns & Dissatisfaction Top reasons for returns: 📦 “Item Not As Described” 💔 “Arrived Damaged” These aren’t just logistics issues — they’re missed chances to improve product listings and supply chain quality. 🚀 What This Dashboard Achieved: Instead of just dropping charts, I focused on building a narrative: 📌 A story of behavioral trends 📌 A story of missed revenue opportunities 📌 A story that guides business decisions with confidence Power BI didn’t just help me visualize — it helped me strategize. 💡 Final Takeaway Your data is always talking. But without the right tools and the right mindset, it just looks like noise. 📣 This project reminded me why I love data analysis — not just for the numbers, but for the stories they unlock and the decisions they inspire. Let’s connect if you’re building something cool in the analytics space — I’m always open to swapping insights and perspectives. Thanks to Jude Raji for your Help #Datafam #PowerBI #EcommerceAnalytics #MarketingROI #CustomerExperience #DataStorytelling #BusinessIntelligence #DashboardDesign #DataDrivenDecisions #DataStrategy #DataVIZ

𝗛𝗼𝘄 𝘁𝗼 𝗥𝗲𝗱𝘂𝗰𝗲 𝗥𝗲𝘁𝘂𝗿𝗻𝘀 𝗮𝗻𝗱 𝗥𝗲𝗳𝘂𝗻𝗱𝘀 𝗼𝗻 𝗬𝗼𝘂𝗿 𝗦𝗵𝗼𝗽𝗶𝗳𝘆 𝗦𝘁𝗼𝗿𝗲 Returns suck. You think you’ve made a sale, you celebrate a little… and then BOOM, refund request. Even worse? Some customers treat online shopping like a free trial. They buy, use, and send it back. But here’s the thing, most returns aren’t scams. They happen because something went wrong in the buying experience. Here’s how to fix that and keep more of your hard-earned revenue: #1 Stop Selling Surprises The #1 reason people return stuff? It’s not what they expected. ✅ Use real product photos (not just perfect studio shots) ✅ Add videos or 360° views so customers can see details ✅ Be brutally honest in descriptions, if the fabric is thin, say it’s lightweight, not “premium” One brand I worked with had crazy return rates on their clothing. Why? The sizing ran small, but they never mentioned it. We added a simple “Runs small, size up!” note, and returns dropped overnight. #2 Offer a Fit Guide (Not Just a Size Chart) Size charts are useless if they don’t make sense. ✅ Show “Fits Like” comparisons (e.g., “Runs like Nike shoes” or “Similar to Zara sizing”) ✅ Use real customer reviews to mention fit (“I’m 5’8”, 150 lbs, and M fits perfectly”) ✅ AI-powered fit finders work if they’re simple and accurate People hate returning clothes. Help them get the right size the first time. #3 Improve Your Product Descriptions If your product descriptions just list features, you’re setting yourself up for returns. ✅ Tell customers what to expect. Is the fabric stretchy? Is the color slightly different in real life? Say it. ✅ Answer objections. If a customer is hesitant about durability, mention the warranty. ✅ Use bullet points. No one reads long paragraphs. Example: Instead of saying “Made from high-quality fabric,” say “Soft, breathable cotton, perfect for summer.” #4 Make Shipping Expectations Crystal Clear If people expect 3-day shipping and get their order in 10, they’re already annoyed. ✅ Give accurate delivery estimates at checkout ✅ Send tracking updates (Shopify has built-in tools for this) ✅ Be upfront about delays, customers are more patient when they know what’s happening If shipping is slow and unpredictable, returns will skyrocket. #5 Stop Making Returns TOO Easy Yes, a good return policy builds trust. But if you make it effortless to return, people will abuse it. ✅ Offer exchanges before refunds ✅ Charge a small return shipping fee (this alone cuts abuse in half) ✅ Give store credit instead of refunds where possible Some brands intentionally make the return process a little annoying. Not impossible, just… inconvenient enough that only real issues get returned. Most returns aren’t a “customer problem.” They’re a store problem. Fix the expectation gap, and you’ll see fewer returns. More happy customers. And, of course, higher profits. 📌 Still dealing with crazy return rates? DM me “Fix” and let’s get started. #shopify