CRM Statistics Report

The CRM Statistics report provides valuable insights into your customer base by identifying key purchase activity within a selected date range. This allows you to recognise loyal customers, analyse spending behaviour, and tailor promotions effectively.

Report Options

When running the report, you can configure the following options:

Date Range
Choose the start and end dates for transactions to be included in the report. Only sales within this period will be analysed.

Min Visits
Specify the minimum number of visits a customer must have made within the selected date range.

Example: If set to 1, all customers with at least one purchase in the date range are included.

Channels
Select which sales channels to report on:

All Channels – Includes both store and e-commerce sales.

Store Sales – Includes only in-store transactions.

Ecomm Sales – Includes only online transactions.

Select Locations
(Optional) Limit the report to one or more store locations. If left blank, all locations are included.

Report Layout

The generated report provides the following customer information:

Member No. – The customer’s membership or account number.

Name – The customer’s full name.

Member Since – The date the customer was first registered.

First Purchase – The date of the first recorded purchase within the selected date range.

Last Purchase – The most recent purchase date within the selected date range.

Visits – Number of distinct transactions (visits) made in the date range.

Total Spend – Total value of all purchases in the date range.

Avg Spend per Visit – Average spend per visit (Total Spend ÷ Visits).

Contact Email – The customer’s recorded email address for follow-up or marketing.

Example Output

Below is an example of the CRM Statistics Report:

Usage Notes

This report is especially useful for identifying VIP customers who make repeated purchases or have high spending habits.

You can use the contact details provided to create targeted loyalty campaigns.

Filtering by channel and location enables deeper insights into customer behaviour in specific stores or online.