Return Rate
Last updated: Oct 22, 2025
What is Return Rate?
Return Rate measures the share of units sold that customers send back and your team accepts within the policy window. It focuses on item counts, not dollars. Use it to surface fit issues, fragile packaging, misleading product details, and fulfilment mistakes that drive avoidable returns. Track it by SKU, variant, size, and channel to see where problems cluster.
Return Rate Formula
How to calculate Return Rate
In October, you sold 25,000 items. Customers returned 1,500 of them within a 30-day window. Return Rate = 1,500 ÷ 25,000 = 6%
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What is a good Return Rate benchmark?
- Apparel and footwear: often 15% to 40% - Consumer electronics: often 5% to 10% - Beauty and personal care: often 2% to 5% - Home and hard goods: often 5% to 15% Ranges vary by channel, price point, and policy leniency. Track your 12?month median and target a steady downward trend rather than a one?time drop.
More about Return Rate
Return Rate, or Merchandise Return Rate, tells you how much of your unit volume comes back. High rates signal costs in reverse logistics, refunds, lost revenue, and potential churn. Tracking this metric over time lets you see the impact of merchandising, product detail page clarity, packaging, and carrier performance.
Notes on measuring this metric properly
Be explicit about dating logic and the allowed window.
- Attribution date: either the original order date or the date the return was processed. Use order date when you’re studying product or pre?purchase issues. Use return date when you’re planning staffing, cash flow, or warehouse workload.
- Return window: count returns that fall within your policy, for example 30 or 60 days from delivery. Late returns should be handled by a separate rule so the metric stays comparable.
Decide how to treat partial returns and exchanges:
- Partial returns: count only the specific units returned in the numerator. For bundles, expand to component SKUs if you track at that level.
- Exchanges: if a return leads to an immediate exchange of the same value, exclude it from value return rate to avoid overstating losses. Keep a separate “exchange rate” metric for visibility.
- Cancellations and chargebacks: do not include these in returns. Track them with their own metrics.
Recommended segmentations
Split your return rate by attributes that you can control or act on:
- Product and variant: SKU, style, size, colour, material
- Shopper and order context: new vs returning customer, first order vs repeat, basket size, payment type
- Channel and geography: marketplace vs direct, country, region, store
- Experience factors: delivery lead time, delivered late flag, packaging type, warehouse
- Reason codes: wrong size, damaged, not as described, changed mind
What good looks like
Overall e?commerce return rates typically range from 5% to 30% depending on category and channel. Apparel and footwear often sit at the high end due to fit. Beauty and consumables are usually low. Use category peers and your own history as the baseline, not a single industry average.
Ways to reduce returns
- Improve product detail pages: accurate sizing charts, multiple angles, true?to?life colour, fabric and material details, weight and dimensions.
- Tighten fulfilment: pick accuracy checks, tamper?evident packaging, protective materials for fragile items.
- Set expectations: clear delivery estimates and return policy, pre?purchase FAQs, size and fit guidance on the page.
- Use post?purchase nudges: care instructions, set?up guides, fit tips in the confirmation email.
- Analyze reason codes: prioritize fixes for the top two causes by items returned.
Return Rate Frequently Asked Questions
What is the difference between order return rate and item return rate, and when should you use each?
Order return rate counts the share of orders where any item was sent back. It tells you how many customers encounter a return experience. Item return rate counts the share of units sold that were returned. It pinpoints problematic products, variants, or sizes.
Use order return rate when you care about customer experience or operational touchpoints, such as how many return labels you process or the risk of churn after a return. Use item return rate when you’re diagnosing merchandising issues, like a shoe model that runs small or a fragile SKU. The two numbers can diverge. A store with many multi?item baskets can have a modest order return rate but a high item return rate if one SKU gets returned often. Track both, pick one as primary, and ensure your teams know when to reference each.
Should returns be dated by order date or return date?
Both approaches are valid. Tie returns to the original order date when you are studying pre?purchase factors and merchandising performance. This aligns returns with the campaigns, seasons, and on?site experiences that drove the purchase. Tie returns to the return processed date when you are managing operations, cash, or staffing. This aligns returns with the work they generate in the warehouse and support queue and with the cash outflow from refunds. Many teams keep two versions in the warehouse, labelled clearly, and default to one in dashboard views. The key is to be consistent inside each report and to disclose the dating rule.
How should you treat exchanges, store credit, and partial refunds in return rate?
Define rules upfront. If an exchange replaces the item with a different size or colour at the same value, exclude it from value return rate so you measure true revenue loss. Still count the item in the item return rate to reflect product issues. If store credit is issued, decide whether it offsets the return value metric. Some teams report both gross return rate and net return rate, where net subtracts exchanges and credit redemptions during the window. For partial refunds, count only the refunded portion in value return rate and the relevant quantity in item return rate. Document these choices in your metric catalog so finance, operations, and merchandising interpret the number the same way.