Refund Report Analyzer — Calculate Refund Rates by Product
A refund report analyzer calculates refund rate by SKU, groups reasons into categories, and shows net revenue after refunds when you upload refund exports from Shopify, Amazon Seller Central, or your payment processor. These exports contain order IDs, amounts, and reason codes but no summary of which products drive returns or what percentage of revenue you lose.
Upload your refund export and order history to see refund rates by product, grouped return reasons, and total revenue lost to refunds in one view.
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Upload your spreadsheet.xlsx .xls .csv — free to try, no accountWhat this export contains
| Order ID |
| Refund Date |
| SKU |
| Product Name |
| Refund Amount |
| Refund Reason |
| Original Order Date |
| Customer Email |
| Quantity Refunded |
| Payment Method |
| Refund Status |
| Currency |
Common questions
What is a refund report analyzer?
A refund report analyzer is a tool that calculates refund rates by product when you upload your refund export. It joins refund data to your order history to show refunded units divided by units sold per SKU, groups freeform return reasons into standard categories, and calculates total revenue lost to refunds.
How do I calculate refund rate from a refund report?
Refund rate is refunded units divided by units sold for the same SKU over the same period. You need both your refund export and your order export, then join them on SKU and date range. A refund report analyzer does this join automatically and shows the percentage per product.
Why do my refund totals not match my payment processor?
Ecommerce platforms export the refund amount before payment processing fees, while your bank statement shows the net amount after the processor takes their fee on the original sale but does not refund their fee. The platform export is correct for product-level analysis; the bank statement is correct for cash reconciliation.
Can I group return reasons automatically?
A refund report analyzer uses keyword matching to group freeform reasons into standard categories like sizing, quality, shipping damage, and buyer's remorse. You can adjust the groupings if your store uses non-standard wording.
What time period should I analyze for accurate refund rates?
Exclude orders placed in the past 30 days because most return windows are 30 days and recent orders have not had time to be returned. Analyzing orders from 30-90 days ago gives a stable refund rate that reflects true product performance.
How do I find which products lose the most money to refunds?
Sort by total refund amount per SKU, not refund rate. A product with a 2% refund rate but high volume and high price can cost more than a product with a 15% refund rate that sells infrequently. The analyzer shows both metrics so you can prioritize fixes by financial impact.
Try it with your own file
DataMimi reads the file you actually have — merged cells, headers below row one, totals pasted at the bottom — and shows which rows and columns every number came from.
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Every plan does everything — slides, written reports, cleaned exports, dashboards. They differ in how much work they cover.
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$24 /month
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$59 /month
5,000 credits a month