Documentation Index
Fetch the complete documentation index at: https://docs.saletides.com/llms.txt
Use this file to discover all available pages before exploring further.
What are customer groups?
Customer groups let you see aggregated metrics for customers who share a common attribute — for example, all customers from Germany, all customers who made their first purchase in Q1, or all customers with a specific WooCommerce user role.
Navigate to Customers → Groups to access this view.
Grouping options
By billing attribute
Group customers by their billing address fields:
| Attribute | Example groups |
|---|
| Country | United States, United Kingdom, Germany, … |
| State / Region | California, Texas, New York, … |
| City | London, Chicago, Sydney, … |
| Postal code | Group by zip/postal area |
By shipping attribute
Same grouping options as billing, but based on the shipping address used on orders.
By purchase behavior
| Attribute | Example groups |
|---|
| First order month | Customers who first ordered in January 2024, February 2024, etc. |
| Order count | Customers with 1 order, 2–5 orders, 6–10 orders, etc. |
| Lifetime value tier | Customers spending 0–100, 100–500, $500+, etc. |
By product
Group customers by the first product they ever purchased, or by whether they have ever purchased a specific product. Useful for understanding which products drive the best long-term customers.
By WooCommerce user role
Group customers by their WordPress user role (e.g., Subscriber, Customer, Wholesale Customer) if your store uses role-based pricing or access.
Reading the group table
Each group row shows:
| Column | Description |
|---|
| Group | The attribute value (e.g., “United States”) |
| Customers | Number of unique customers in this group |
| Orders | Total orders from this group |
| Revenue | Total gross revenue |
| AOV | Average order value |
| Repeat Rate | % of customers who ordered more than once |
| Avg LTV | Average lifetime revenue per customer |
Sorting and filtering groups
Click any column header to sort. Use the date range picker to analyze a specific time period.
Use cases
- Geographic expansion — which countries are growing fastest?
- Cohort seeding — customers acquired in a specific month tend to have higher LTV?
- Product discovery — which first purchase leads to the most repeat buying?
- Role-based offers — are wholesale customers more valuable than retail?
