The total dollar amount refunded to new customers (first-time buyers).
New Customer Refunds = SUM ( Refund Amount ) WHERE customer_type = new | Metric | Definition |
|---|
| Refund Amount | The dollar value refunded to customers |
| customer_type = new | Filters to orders from first-time customers with no prior purchases |
| Metadata | |
|---|
| Type | Currency |
| Data Source | Shopify |
| Aggregation | Sum |
Example
Your store refunded $2,847 to new customers in March across 43 refunds:
| Week | New Customer Refunds | Refund Count |
|---|
| Week 1 | $542 | 8 |
| Week 2 | $1,203 | 18 |
| Week 3 | $687 | 11 |
| Week 4 | $415 | 6 |
How It Works
This metric sums all refund amounts from orders placed by first-time customers. A customer is classified as “new” based on their order history in Shopify—their first completed order marks them as a new customer. High values may indicate product quality issues, unmet expectations from marketing, or sizing/fit problems affecting first impressions.
When to Use
| Scenario | Action |
|---|
| Evaluating acquisition quality | High refunds from new customers suggest targeting or messaging issues |
| Identifying product problems | Compare to returning customer refunds to isolate new buyer issues |
| Analyzing marketing campaigns | Check if specific campaigns drive higher first-purchase refunds |
| Measuring onboarding experience | Track alongside customer feedback to improve first-order satisfaction |
| Metric | Relationship |
|---|
| New Customer Refund Count | Number of refunds (this metric sums their values) |
| New Customer Refund % | Share of new customer orders refunded |
| NC Refund Per Order | Average refund amount per new customer order |
| Returning Customer Refunds | Compare new vs. returning customer refund behavior |
| Refund Amount | Combined refunds across all customer types |
