> ## Documentation Index
> Fetch the complete documentation index at: https://docs.upstackdata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# New Customer Refund %: Track First-Time Buyer Returns

> Measure the percentage of new customer orders that result in refunds. Identify product-market fit issues with first-time buyers and optimize acquisition quality.

<Tip>
  The share of new customer orders that resulted in a refund.
</Tip>

## Formula

<Info>
  **NC Refund %** = ( [**New Customer Refund Count**](/reference/metrics/orders/adjustments/new-customer-refund-count) ÷ [**New Customers**](/reference/metrics/orders/customers/new-customers) ) × 100
</Info>

### Formula Components

| Metric                                                                                           | Definition                                        |
| ------------------------------------------------------------------------------------------------ | ------------------------------------------------- |
| [**New Customer Refund Count**](/reference/metrics/orders/adjustments/new-customer-refund-count) | Number of new customer orders with refunds issued |
| [**New Customers**](/reference/metrics/orders/customers/new-customers)                           | Total orders placed by first-time buyers          |

| Metadata        |                             |
| --------------- | --------------------------- |
| **Type**        | Percentage                  |
| **Data Source** | [Shopify](/sources/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 |

***

## Related Metrics

| Metric                                                                                                 | Relationship                                       |
| ------------------------------------------------------------------------------------------------------ | -------------------------------------------------- |
| [New Customer Refunds](/reference/metrics/orders/adjustments/new-customer-refunds)                     | Dollar amount of refunds (this metric is the rate) |
| [New Customer Refund Count](/reference/metrics/orders/adjustments/new-customer-refund-count)           | Numerator in this formula                          |
| [Returning Customer Refund %](/reference/metrics/orders/adjustments/returning-customer-refund-percent) | Same metric for repeat buyers                      |
| [New Customer %](/reference/metrics/orders/customers/new-customer-percent)                             | Share of orders from first-time buyers             |

[See all Adjustments metrics →](/reference/metrics/orders/adjustments)