RFM Segmentation model
What is RFM?
RFM is a classic customer analytics framework that scores each customer on three dimensions:
- Recency — How recently did they buy? (1–5, where 5 is most recent)
- Frequency — How often do they buy? (1–5, where 5 is most frequent)
- Monetary — How much do they spend? (1–5, where 5 is highest spender)
Each dimension is scored 1–5 based on where the customer falls in your store's distribution. A score of 5 means "top 20% of your customers".
The 8 RFM segments
| Segment | Profile | Recency | Frequency | Monetary |
|---|---|---|---|---|
| Champions | Best customers — bought recently, buy often, spend most | 4–5 | 4–5 | 4–5 |
| Loyal | Regular buyers who spend well | 2–5 | 3–5 | 3–5 |
| Potential Loyal | Recent buyers with growth potential | 3–5 | 1–3 | 1–3 |
| New Customers | Bought recently for the first time | 4–5 | 1 | 1–5 |
| Promising | Recent buyers but not yet consistent | 3–4 | 1–2 | 2–3 |
| At-Risk | Used to buy often but haven't recently | 1–2 | 2–5 | 2–5 |
| Hibernating | Low scores across the board — may be lost | 1–2 | 1–2 | 1–2 |
| Lost | Lowest scores — haven't bought in a very long time | 1 | 1–2 | 1–2 |
RFM vs. Churn score: A customer can be in the At-Risk RFM segment (Recency 1–2) but have a low churn score if the model predicts they typically take long gaps between purchases. The churn model accounts for each customer's personal rhythm, while RFM uses store-wide percentiles.
How RFM updates
RFM scores update daily after the nightly sync. A customer's segment can change as their behaviour evolves — for example, a Champion who stops buying will gradually move through Loyal → At-Risk over time.
Using RFM in audiences
RFM segment is one of the most powerful filters in the Audience builder. Common uses:
- Export "Champions" to a Klaviyo VIP list for early access campaigns
- Target "Former Champions now At-Risk" for personalised win-back outreach
- Filter "New Customers" (R=5, F=1) for second-purchase nurture sequences
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