The share of new customer orders that resulted in a refund.
| Metric | Definition |
|---|
| New Customer Refund Count | Number of new customer orders with refunds issued |
| New Customers | Total orders placed by first-time buyers |
| Metadata | |
|---|
| Type | Percentage |
| Data Source | Shopify |
| Aggregation | Ratio |
Example
Your store had 8.2% New Customer Refund % this quarter:
| Metric | Value | Context |
|---|
| NC Refund Count | 164 | Orders refunded |
| NC Order Count | 2,000 | Total NC orders |
| NC Refund % | 8.2% | Above 5% benchmark |
How It Works
This metric divides the number of new customer refunds by total new customer orders, expressed as a percentage. A rising refund rate among first-time buyers often signals product-expectation misalignment, misleading ads, or quality issues that disproportionately affect acquisition.
When to Use
| Scenario | Action |
|---|
| Launching new products | Monitor if first-time buyers return items more often |
| Evaluating ad creative | High NC refund % may indicate misleading messaging |
| Comparing customer segments | Benchmark against Returning Customer Refund % |
| Optimizing acquisition channels | Identify which traffic sources drive low-quality buyers |
| Metric | Relationship |
|---|
| New Customer Refunds | Dollar amount of refunds (this metric is the rate) |
| New Customer Refund Count | Numerator in this formula |
| Returning Customer Refund % | Same metric for repeat buyers |
| New Customer % | Share of orders from first-time buyers |
