Return Rate

Return rate is the percentage of sold items or orders that are returned by customers. It is a key indicator of product quality, accuracy of product descriptions, and customer satisfaction.

Also known as: product return rate, merchandise return rate

Formula

(Returned Orders / Total Orders) x 100

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Why It Matters

Returns are a double cost: you lose the sale revenue and you incur return processing, restocking, and often shipping expenses. For many ecommerce businesses, returns are the single largest drain on profitability. A 30% return rate does not just mean 30% less revenue - it means 30% of your fulfillment and shipping costs were wasted.

Return rate is also a powerful quality signal. High return rates for specific products indicate problems with sizing, quality, photography accuracy, or description clarity. Tracking returns by reason code reveals exactly what to fix - if "wrong size" is the top reason, your sizing guide needs work, not your product quality.

Reducing return rate has a multiplier effect on profitability. Lower returns mean higher net revenue, lower logistics costs, less inventory tied up in the returns pipeline, and better customer satisfaction (since customers who need to return items have a worse experience than those who keep their purchases).

How to Calculate

Divide the number of returned items (or orders with returns) by the total number of items sold (or total orders) in the same period. Multiply by 100. Track returns within a consistent window - typically 30 or 60 days from purchase - since returns can trickle in over weeks. Calculate both unit return rate and dollar return rate for the most complete picture.

Return Rate Calculator

(Returned Orders / Total Orders) x 100

Return Rate15.00%

Industry Applications

E-commerce

An apparel brand reduces its return rate from 35% to 22% by implementing a virtual try-on feature and improved sizing guides with customer measurements, saving $2.3M annually in return processing costs.

Benchmark: Ecommerce return rates: apparel 25-40%, electronics 10-15%, beauty 5-10%, furniture 5-8%

SaaS

A SaaS company tracking refund requests (the SaaS equivalent of returns) finds that customers who use the free trial fully before purchasing have a 60% lower refund rate than those who purchase impulsively.

How to Track in KISSmetrics

In KISSmetrics, track return events with properties including product ID, return reason, and return value. Connect returns back to the original purchase to analyze which acquisition channels, products, and customer segments generate the most returns. Use this data to identify patterns and implement preventive measures.

Common Mistakes

  • -Not tracking return reasons, which makes it impossible to distinguish between quality issues, fit problems, and buyer remorse
  • -Ignoring the cost of returns when calculating profitability - returns are not just lost revenue but also incur processing costs
  • -Setting return windows based on industry norms rather than analyzing the actual timeline of returns for your products
  • -Not connecting returns data to marketing data, missing the insight that certain channels produce higher-return customers

Pro Tips

  • +Require and analyze return reason codes to categorize returns into actionable buckets: quality, fit, description mismatch, changed mind
  • +Invest in better product photography and sizing tools to reduce "item not as described" returns
  • +Track return rate by SKU to identify specific products with quality or description issues
  • +Consider offering exchanges instead of refunds to retain the revenue while addressing customer needs
  • +Analyze the correlation between return behavior and lifetime value - serial returners may not be your target customer

Related Terms

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