> For the complete documentation index, see [llms.txt](https://docs.rafflex.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rafflex.io/downloads-and-reports/downloads/new-vs-returning-customers.md).

# New vs Returning Customers

Compare how new and returning customers contribute to your sales over time. See customer counts, orders, revenue and average order values for both groups, day by day, week by week or month by month.

***

The New vs Returning report splits your sales into two groups: customers buying from you for the very first time, and customers who have bought before. For each day, week or month in your chosen period, it shows how many customers were in each group, how many orders they placed, how much they spent, and what share of your buyers were new.

It helps you answer questions like:

* Is my advertising bringing in new customers, or am I mostly selling to the same people?
* Do returning customers spend more per order than new ones?
* Did last month's launch or giveaway attract new buyers?

***

### How to Generate the New vs Returning Report

1. Log in to your admin panel.
2. Click **Analytics** in the left-hand menu.
3. At the top of the Analytics page, click **Download Reports**. This opens the Downloads page.
4. Click **Generate Report**.
5. Choose **New vs Returning** from the list.
6. Choose your **Date Range**.
7. Choose how to split the results in **Group By**: **Daily**, **Weekly** or **Monthly**.
8. Click **Submit**.

You will see a **Download Started** message. The report is built in the background and you will receive an email when it is ready. You can also stay on the Downloads page and watch the **Status** column. When it shows complete, click **Download** on that row to save the CSV file. In your downloads list and in the email, this report is called **New vs Returning Customers Report**.

{% hint style="info" %}
**Cannot see Download Reports?** If you do not see the Download Reports button on Analytics, contact Rafflex support. If you are a staff member and cannot see **Analytics** at all, your account may have the **Restrict Financials** restriction. See [Staff Accounts and Access](/managing-your-site/customers/staff-accounts-and-access.md).
{% endhint %}

***

### Filters

#### Date Range

The period of orders to look at.

* Choose a quick option: **Last 1 Day**, **Last 3 Days**, **Last 5 Days**, **Last 7 Days**, **Last 14 Days**, **Last 30 Days** (the default), or **Last 60 Days**.
* Or choose **Custom** and pick a **From Date** and **To Date**. A custom range can cover up to 3 months.

#### Group By

How the rows are split. The default is **Daily**.

| Option      | Each row covers                | How the Period column looks               |
| ----------- | ------------------------------ | ----------------------------------------- |
| **Daily**   | One day                        | **2026-03-14** (year, month, day)         |
| **Weekly**  | One week, starting on a Monday | **2026-W11** (year, then the week number) |
| **Monthly** | One calendar month             | **2026-03** (year, then month)            |

{% hint style="success" %}
**Which grouping should I use?** Use **Daily** to look closely at a short campaign or launch week. Use **Weekly** to smooth out busy and quiet days. Use **Monthly** with a custom range of up to 3 months to compare whole months side by side.
{% endhint %}

{% hint style="info" %}
With **Weekly**, the first few days of January can show as week **00** when they fall before week 1 of the new year begins. This is normal.
{% endhint %}

***

### How Customers Are Sorted into New and Returning

Rafflex looks at each customer's **whole order history**, not just the date range you picked.

* An order is a **new customer** order if it is that customer's very first completed order on your site.
* Every completed order after that is a **returning customer** order.

So if someone first bought from you last year and buys again this week, they count as **returning** this week, even though last year is outside your date range.

**Example:** Sam places their first ever order on Monday and a second order on Thursday of the same week. In a **Daily** report, Sam is a new customer on Monday and a returning customer on Thursday. In a **Weekly** report, both orders fall in the same week, so Sam is counted once as new and once as returning in that week's row.

Only completed orders count. Failed, abandoned and cancelled orders are ignored, so a customer whose first attempt failed becomes "new" on the day their first order goes through.

***

### What's Included

Each row is one day, week or month, in date order. Days, weeks or months with no completed orders are left out, so you may see gaps.

| Column                             | What it shows                                                                 |
| ---------------------------------- | ----------------------------------------------------------------------------- |
| **Period**                         | The day, week or month the row covers (see Group By above).                   |
| **New Customers**                  | How many customers placed their first ever completed order in this period.    |
| **Returning Customers**            | How many different customers placed a repeat order in this period.            |
| **Total Customers**                | New Customers plus Returning Customers.                                       |
| **New Customer Orders**            | How many first orders were placed. This normally matches New Customers.       |
| **Returning Customer Orders**      | How many repeat orders were placed. One returning customer can place several. |
| **New Customer Revenue (£)**       | The total value of first orders.                                              |
| **Returning Customer Revenue (£)** | The total value of repeat orders.                                             |
| **New Customer AOV (£)**           | The average order value for first orders.                                     |
| **Returning Customer AOV (£)**     | The average order value for repeat orders.                                    |
| **New Customer Rate (%)**          | New Customers as a percentage of Total Customers.                             |

**AOV** stands for average order value: the revenue divided by the number of orders.

{% hint style="info" %}
**Total Customers can count someone twice.** As in the example above, a customer who places their first and second order in the same period is counted once as new and once as returning. On a busy launch day this can make Total Customers slightly higher than the number of different people who bought.
{% endhint %}

{% hint style="info" %}
Revenue figures are based on each order's total. When an order was paid partly with site credit and partly by card, only the card part is included. For a full breakdown of card and credit spend per customer, use the [Customer Value Report](/downloads-and-reports/downloads/customer-value-report.md).
{% endhint %}

***

### Reading the Results

* **A rising New Customer Rate** usually means your advertising or social posts are reaching new people.
* **A low New Customer Rate** means most sales come from existing customers. That is a sign of a loyal audience, but you may want to invest more in reaching new players.
* **Returning Customer AOV higher than New Customer AOV** is common. Regular players often buy more tickets once they trust your site.
* **Compare with your marketing.** Run the [Customer Acquisition](/downloads-and-reports/downloads/customer-acquisition-attribution.md) report for the same dates to see which links brought those customers in.

***

### Related Reports

{% content-ref url="/pages/dJInV360gKqSr3n4t4Fh" %}
[Customer Acquisition Attribution](/downloads-and-reports/downloads/customer-acquisition-attribution.md)
{% endcontent-ref %}

{% content-ref url="/pages/88xRsNIX5DIr3My4RxYg" %}
[Inactive Customers Report](/downloads-and-reports/downloads/inactive-customers-report.md)
{% endcontent-ref %}