What is RFM Analysis?

RFM analysis is a classic segmentation method scoring customers in three dimensions: Recency, Frequency, Monetary. Score 1-5 in each; the resulting three-digit code (e.g., 555 = best, 111 = worst) places each customer in a meaningful segment.

the three dimensions

• R (Recency): time since last order. 1 = long gone, 5 = recent purchase.
• F (Frequency): orders in window. 1 = rare, 5 = frequent.
• M (Monetary): total spend. 1 = low, 5 = high.

scoring method (quintile)

1. Sort customers by R; top 20% gets 5, bottom 20% gets 1.
2. Sort by F similarly, score 1-5.
3. Sort by M similarly, score 1-5.
4. Combine into 3-digit RFM code per customer.

segment map

• 555, 554, 545: Champions / VIPs · most valuable, most loyal.
• 5XX (high R): New / active customers.
• X4X-X5X high F, low R: At-risk loyal · proactive campaign.
• 11X, 12X (low R, low F): Lost · winback, then archive.
• 551, 541: New low-spend · upsell opportunity.
• 515, 514: One-big-purchase · recovery focus.

where RFM works

• E-commerce (always).
• Subscription / box services.
• Restaurant chains (with loyalty data).
• Banks / finance (transaction-based).
• SaaS partially · adapt with usage frequency + plan size.

modern RFM (RFM+)

• RFML · adds Length (relationship duration).
• RFMP · adds Profit (margin not just revenue).
• RFM + Predictive · adds future-purchase probability (CLV models).

after segmentation, then what

1. Calculate funnel and LTV per segment.
2. Prioritize high-value + at-risk segments.
3. Differentiate message, channel, offer.
4. Track segment movement monthly (who moved from VIP to At-risk).