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April 23, 2026
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Customer Overview

Analyze customer behavior, retention patterns, and your most valuable customers in Corgi Intelligence: acquisition/retention/churn trends, loyalty metrics, CLV, and a frequent-customer table.

The Customer Overview page helps you analyze customer behavior, retention patterns, and identify your most valuable customers.

Customer Acquisition, Retention & Churn Analysis

The main chart provides a combined view of customer trends over time.

Metric

Definition

Total Customers

The total number of unique customers in the selected period.

New Customers

First-time buyers during the period.

Returning Customers

Customers who made at least one prior purchase.

Churn Rate

Percentage of customers who purchased in the previous period who did not return in the next period.

This visualization helps you understand the balance between acquisition and retention over time. A rising churn rate alongside flat new customer growth is a signal that retention strategies need attention.

Repeat Purchase Rate

The Repeat Purchase Rate shows the percentage of customers making 2 or more purchases. This is a key loyalty metric. A higher repeat rate generally indicates strong product-market fit and effective retention.

Customer Lifetime Value (CLV)

The Customer Lifetime Value metric shows the average total revenue per customer across their entire relationship with your business. This helps you understand how much each customer is worth and informs decisions about acquisition spend and retention investment.

Top Frequent Customers

A detailed table lists your most active customers, filtered to show those with strong repeat purchase volume and fewer disputes.

Column

Definition

Customer name and email

Identifies the customer.

Purchases

Total number of transactions.

Disputes

Number of disputes filed by this customer.

Total Spent

Cumulative spend.

Avg. Order

Average transaction value.

Last Purchase

Date of most recent transaction.

This table is useful for identifying VIP customers, spotting potential fraud patterns (high purchase volume combined with high dispute counts), or building targeted retention campaigns.