Customer Retention Metrics Every Repeat-Purchase Business Should Understand

The share of customers from a starting period who bought again in a later period.

Example: 400 customers bought in Q1, 260 of them bought again in Q2. Retention rate = 260 ÷ 400 = 65%.

The share of all customers with two or more orders.

Example: 1,000 customers, 350 with at least two orders. Repeat purchase rate = 35%.

Average orders per customer in a period: total orders ÷ unique customers.

Example: 1,800 orders from 1,000 customers = 1.8 orders per customer.

The number or share of customers with no purchase for a chosen period, measured to a fixed reference date. It is one of the earliest signals you can act on.

For reference, Revenow currently applies one fixed rule set (Generic 1.0) to every customer, counted from the analysis reference date: under 60 days since the last purchase is active, 60–89 days is at risk, and 90 days or more is inactive. These are Revenow's product settings, not an industry standard. The right windows for your own manual analysis depend on how often your customers normally buy.

Total historical revenue per customer, or average order value × number of orders. It helps you see which customers matter most to retain.

Example: average order $120 × 5 orders = $600 historical value.

An estimate of revenue tied to customers who are overdue but not yet inactive. It is an exposure figure, not a guaranteed loss. See how to calculate revenue at risk.

All examples on this page use hypothetical figures.

1. Track retention and repeat purchase rate over time to see the overall trend.
2. Use inactivity to find who needs attention now.
3. Rank those customers by revenue value.
4. Act on the top of the list first and measure what changes.

See how Revenow brings these together in customer retention analytics, or read how to analyze customer churn.