RFM Analysis
RFM analysis scores customers on recency, frequency, and monetary value, mapping the list into actionable segments.
What RFM analysis is
RFM analysis scores customers on three behaviors: recency of last purchase, frequency of purchases, and monetary value spent, then groups them by the combination.
Why RFM matters
It turns a flat customer list into a map: champions buying often and recently, big spenders going quiet, newcomers worth developing, low-value segments not worth discounting. Each group gets its own play instead of the same blast.
How RFM gets used
- Score each dimension in bands, from your own data’s spread
- Champions: early access and appreciation, not discounts
- High-value-going-quiet: the win-back priority list
- Low-R low-F: suppress from paid retargeting spend
Frequently asked questions
Why these three dimensions?
They’re behavioral, universal, and already in the order history: no surveys, no modeling. Recency predicts responsiveness, frequency predicts habit, monetary sizes the relationship.
How often should RFM scores refresh?
On a cadence matching your purchase cycle: monthly for frequent-purchase categories, quarterly for slower ones. Stale scores mail win-backs to people who bought last week.
Related terms
Segmentation · Customer Lifetime Value · Customer Retention · Cohort Analysis