How to Track Refund Rate and Return Rate on Shopify

Refund rate is the share of sales you gave money back on; return rate is the share of what you sold that customers sent back. Each can be measured by orders, by units or by value, and the three give different answers, so choose one of each and state it. This guide sets out the definitions, the breakdowns worth having, how to handle the delay between a sale and its return, and how to feed what you learn back into product pages.

What is the difference between a refund and a return?

A return is goods coming back. A refund is money going back. They overlap heavily, and they are not the same event.

• Refund without a return: an order cancelled before dispatch, a goodwill refund for a late parcel, a partial refund for a minor fault, a refund of the shipping charge alone.
• Return without a refund: an exchange for another size, or a return settled with store credit.

Track both. Exchanges are clear evidence of a sizing problem and vanish if you only count refunds; cancellations before dispatch point to stock problems and deserve their own line.

Should you measure by orders, units or value?

Use all three at least once, then settle on the one that suits the decision.

• By orders: orders with at least one returned item, divided by all orders. This is the customer's view: how many purchases led to the bother of sending something back.
• By units: units returned divided by units sold. This is the product view, and the right basis for comparing one product or size with another.
• By value: value refunded divided by sales. This is the finance view, and it is the one that links to net sales.

Here is an example with made-up round figures. Say a store ships 1,000 orders in a month, containing 1,500 units, for $60,000 of sales. Later, 90 of those orders have something returned: 105 units in all, with $3,600 refunded.

• By orders: 90 divided by 1,000, or 9%.
• By units: 105 divided by 1,500, or 7%.
• By value: $3,600 divided by $60,000, or 6%.

All three are correct. The order rate is highest because an order with three items counts as a return even if only one comes back. The value rate is lowest here because the returned items were cheaper than average.

How should you handle the lag between sale and return?

Match each return to the month of the original sale, and wait until the return window has closed before calling a month final.

There are two ways to date a return, and they answer different questions:

1. By return date. This month's returns divided by this month's sales. It is simple, and it is how returns reduce net sales in Shopify's reports, as our guide to gross sales, net sales and total sales explains. It misleads when sales are changing fast: after a big promotion month, the following month shows a high rate because it carries the promotion's returns against its own smaller sales.
2. By sale date. Returns from orders placed in a month, divided by that month's orders, whenever those returns arrive. This is the true rate for the month, a product or a campaign. Its drawback is that recent months are incomplete.

Use the first for cash and finance, and the second for judging products. When using the second, do not compare last month with a month from half a year ago until last month has had the same time to collect its returns.

Which breakdowns are worth having?

A store-wide rate tells you whether there is a problem. Breakdowns tell you where.

• By product. Rank products by units returned and by unit return rate together. A high rate on a product that sells five units a month matters less than a moderate rate on your bestseller.
• By size or variant. If one size comes back far more than the others, the cut or the size chart is off at that point in the range.
• By reason. Collect a reason with every return, from a short fixed list: too small, too large, not as pictured, faulty, arrived damaged, arrived late, changed mind. Free-text reasons cannot be counted.
• By payment method. Some methods show different refund behaviour; see our guide to sales by payment method.

How do you feed returns back into product pages?

Read each reason as a statement about the gap between what the page promised and what arrived, then fix the page.

• Too small or too large on one product: add measured dimensions and a plain fit note, and correct the size chart for that item.
• Not as pictured: replace flattering images with accurate ones, add close-ups of texture and colour in natural light, and describe the material precisely.
• Arrived damaged: this is a packaging matter. Change the packing for that product and watch the rate.

After each change, watch the same product's return rate by sale date for the following weeks. Our article on why returns are a product problem makes the case for treating reasons as product research.

Rules on returns and refunds differ by market. Keep your policy in line with the law where you sell, and take advice if you are unsure.

Where do the numbers come from?

As the guide to Shopify analytics and their gaps describes, returns reduce net sales in the built-in reports, but the product, size and reason view takes extra work.

Marka Metrics shows refund and undelivered rates on its free plan and reports returns by product, size and reason, so the ranking described above is already built.

A short checklist

1. Track refunds and returns as separate measures.
2. Pick a basis, orders, units or value, and state it every time.
3. Judge products on returns matched to the sale date.
4. Wait for the return window to close before finalising a month.
5. Collect a reason from a fixed list on every return.
6. Rank by product and size, then fix the page for the worst offender.
7. Recheck that product's rate after the change.

A return rate is most useful as a list of specific pages to improve. To see refunds and returns by product, size and reason from your Shopify data, try Marka Metrics.