Refund amounts attributed to the date the refund was issued, showing when money actually left your account rather than when the original order was placed.
Refund Amount (by Refund Date) = SUM ( Refund Value ) GROUPED BY Refund Issue Date
| Metadata | |
|---|
| Type | Currency |
| Data Source | Shopify |
| Aggregation | Sum |
Example
Your store processed $18,450 in refunds during March, despite variable order volumes:
| Date | Refunds Issued | Amount | Notes |
|---|
| March 5 | 23 | $2,890 | Post-February sale returns |
| March 15 | 47 | $8,340 | Batch processing day |
| March 28 | 31 | $4,120 | End-of-month spike |
How It Works
This metric groups refunds by when they were processed, not when orders were placed. A January order refunded in March appears in March’s totals. This shows the actual cash flow impact of refunds on any given day or period.
When to Use
| Scenario | Action |
|---|
| Cash flow forecasting | Predict when refund outflows will hit your account |
| Refund processing monitoring | Detect unusual spikes in daily refund activity |
| Operations planning | Staff appropriately for high-refund processing days |
| Reconciliation | Match refund totals with bank statement debits |
| Metric | Relationship |
|---|
| Refund Amount (by Order Date) | Refunds attributed to original order date |
| Refund Amount | Total refund amount |
| Refund Count | Number of orders with refunds |
| Net Revenue | Gross revenue minus refunds and discounts |
