> ## 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.

# Average Days Between Orders: Purchase Frequency Metric

> Measure how many days pass between repeat purchases. Track customer buying frequency to optimize retention campaigns and predict reorder timing.

<Tip>
  The average number of days between a customer's consecutive orders.
</Tip>

## Formula

<Info>
  **Average Days Between Orders** = **Sum of Days Between Consecutive Orders** ÷ **Number of Repeat Purchase Intervals**
</Info>

### Formula Components

| Metric                        | Definition                                                     |
| ----------------------------- | -------------------------------------------------------------- |
| **Days Between Orders**       | Calendar days from one order to the next for the same customer |
| **Repeat Purchase Intervals** | Count of order pairs (2nd order, 3rd order, etc.)              |

| Metadata        |                             |
| --------------- | --------------------------- |
| **Type**        | Number                      |
| **Data Source** | [Shopify](/sources/shopify) |
| **Aggregation** | Average                     |

***

## Example

Your store's customers place repeat orders an average of **32 days** apart:

| Customer Segment    | Avg Days | Interpretation             |
| ------------------- | -------- | -------------------------- |
| Subscription buyers | 28 days  | Regular monthly cycle      |
| Consumables         | 35 days  | Product lifespan \~5 weeks |
| Apparel             | 62 days  | Seasonal buying patterns   |

***

## How It Works

Average Days Between Orders calculates the time gap between each customer's consecutive purchases, then averages across all repeat purchase intervals in your selected period. Only customers with 2+ orders contribute to this metric—first-time buyers are excluded since they have no interval to measure.

***

## When to Use

| Scenario               | Action                                                     |
| ---------------------- | ---------------------------------------------------------- |
| Setting email cadence  | Time win-back flows to trigger before the average interval |
| Subscription pricing   | Set billing cycles to match natural purchase frequency     |
| Inventory planning     | Forecast demand based on typical reorder timing            |
| Retention benchmarking | Compare segments to identify high-frequency cohorts        |

***

## Related Metrics

| Metric                                                                                 | Relationship                                              |
| -------------------------------------------------------------------------------------- | --------------------------------------------------------- |
| [Purchase Frequency](/reference/metrics/orders/performance/purchase-frequency)         | Orders per customer (inverse relationship)                |
| [Returning Customer %](/reference/metrics/orders/customers/returning-customer-percent) | % of customers who reorder (prerequisite for this metric) |
| [LTV 365](/reference/metrics/orders/ltv/ltv-365)                                       | Shorter intervals often correlate with higher LTV         |

[See all Performance metrics →](/reference/metrics/orders/performance)