How to Identify Inactive Customers From Purchase Data

An inactive customer has bought from you at least once but has not purchased for longer than you would reasonably expect. "Inactive" is a label you define with a time threshold; it describes past behavior and does not prove the customer has left for good.

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.

At minimum, one row per order with:

• A customer identifier (name, email or customer ID)
• The order date
• The order revenue

If your data needs cleaning first, see how to prepare customer data.

Pick a fixed reference date, usually the last date covered by your export, not today's date. Using today can make every customer look older than they are if the export is a few weeks old. For each customer, find their most recent order and count the days between it and the reference date.

Group customers by days since last purchase, for example:

Illustrative example with hypothetical customers.

Then add context: how many orders each customer placed and how much they spent in total.

• Counting the same customer twice because their name is spelled differently
• Measuring from today instead of the end of the data period
• Treating one-time buyers and loyal regulars as the same group
• Using a threshold that ignores how often your customers normally reorder

Sort inactive customers by historical spend and order count, then decide who to contact first. Our reactivation guide covers outreach. To automate the detection step, see inactive customer detection.