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What Is the Order vs Return (Monthly) Report?
The Order vs Return (Monthly) Report groups every month into a single row and sets that month's order count next to its returned orders, then expresses the gap as two rates: a Return order % and a Return Value %. Instead of checking refunds order by order, you get one line per month and a clean trend you can read top to bottom.
The distinction most merchants miss is between the two rates. Return order % is a count (how many orders came back). Return Value % is money (how much revenue was refunded). A month can look fine on one and bad on the other, which is exactly why both sit in the report.
A second thing to know: a return is counted in the month it is processed, not the month the original order was placed. So a single month blends returns from current and earlier sales. That makes this a report you read as a trend across months, not a report you judge one month at a time.
You would use this report when the question is "is our return rate stable, climbing, or falling," rather than "which product or which order."
Which Fields Are Included in the Order vs Return (Monthly) Report?
These fields let you compare order volume against return volume and see both the count and value impact for each month.
You can customize the pre-made report by adding, removing, or rearranging columns, switching the grain from monthly to weekly or quarterly, or adding a calculated margin-at-risk column where product cost is set.
Important Insights You Can Find in This Report
Is your return problem in the count or the value?
Put Return order % next to Return Value % for the same month. When the value rate runs higher than the count rate, a small number of expensive orders are driving the losses, which points to a specific high-ticket product or a pricing and fit issue at the top end. When the count rate is higher, you have a volume problem across cheaper items, which points more to sizing, expectations, or a category-wide description gap. The rate that is higher tells you where to look first.
Is the return rate actually trending, or is one month just noise?
A single elevated month rarely means anything. Read three or more months in the same direction before you treat it as a real move. If the return rate has climbed for a quarter straight, that is a root-cause hunt worth starting. If it spiked once and settled, it was probably a batch of late returns landing together.
Does a bad return month line up with a strong sales month just before it?
Because returns are booked in the month they are processed, a heavy return month often trails a heavy sales or promo month. Line up each high-return month against the month or two before it. If the spike follows a big discount push or a seasonal peak, the returns are the tail of that event, not a new problem. If it follows a normal month, that is more concerning and worth tracing to products.
THE ANALYST'S READ: The Signal Most Merchants Miss
The trap in a monthly returns report is reacting to the wrong month. Because a return is counted when it is processed, a spike in, say, February can belong almost entirely to a January or December sales surge. Merchants who read each month in isolation end up investigating February's products when the real story is holiday buying that was always going to come back.
The read worth building is the lag. Look at whether return spikes consistently sit one to two months behind your sales spikes. If they do, your returns are event-driven and largely predictable, and the number to manage is the return rate around those events, not the raw count. If a return spike appears with no matching sales event before it, that is the month that deserves a real root-cause pass in the Refund Report. Separating event-driven returns from genuine quality drift is the single most useful thing this report can tell you, and it only shows up when you read across months.
How Can You Automate the Order vs Return (Monthly) Report?
Open Report Pundit in your Shopify admin, open the pre-made Order vs Return (Monthly) template, set your date range to twelve or more months so the trend is real, and Save. From there you can schedule it to send on a monthly cadence to finance, CX, or an owner, and choose the format: Excel, CSV, PDF, or a live push to Google Sheets so the trend charts itself. It runs on every Shopify plan, including the free Report Pundit plan, and does not depend on Shopify's native 13-month history cap.
Frequently Asked Questions
What is the difference between Return order % and Return Value %?
Return order % is the share of orders that came back, a count-based view. Return Value % is the share of revenue refunded, a money-based view. They can move apart: a few high-value returns can push the value rate up while the order rate still looks healthy. For margin, the value rate is usually the one that matters more.
Why might a return show up in a different month than the sale?
Returns are counted in the month they are processed, not the month the order was placed. So any month's rate blends returns from current and earlier sales. Read the trend across several months rather than reacting to a single period.
How is the value rate denominator calculated?
Return Value % divides the month's Returns Value by its Total Sales. Confirm with your template whether Total Sales here is net sales (gross minus discounts and returns) or the gross figure, since that changes how you read the percentage.
How is this different from the Product Return Rate report?
This report is organized by month and shows the store-wide return trend over time. The Product Return Rate report is organized by product and shows which items are returned most often. Use this one to see whether returns are rising; use Product Return Rate to find the products behind it.
How far back can I trend returns?
As far as your data allows. Shopify's native reporting caps history at roughly 13 months, so Report Pundit is what lets you build a longer returns trend and compare the same month year over year.
Can I change the report from monthly to weekly or quarterly?
Yes. The pre-made version groups by month, but you can switch the grain to weekly or quarterly if you want a tighter or broader view of the same return trend.