RFM Segment LTV (Concept Demo)
See why segmenting customers by recency/frequency/value before estimating churn beats one blended LTV number for the whole base.
live — runs in your browserOnlinePre + Post-campaign
Inputs
Results
RFM (Recency, Frequency, Monetary) segmentation is a decades-old, unpatented retail-analytics convention. What production systems add (see the patent reference below) is deriving each segment's churn rate from a trained model on real transaction data, then feeding retained-customer predictions into targeting — this demo skips the modeling and lets you type in segment stats directly, so you can see why the segment-first approach matters: high-value customers churn slower and are worth far more per head, and averaging everything together before dividing by churn understates that (or overstates it, depending on your mix) every time.
How this is calculated
High-value segment LTV
Source: LTV = annual revenue ÷ churn rate
Medium-value segment LTV
Low-value segment LTV
Blended LTV (segmented — the honest number)
Naive flat-average LTV (what you'd get without segmenting)
Same customer base, same total revenue — just averaged first instead of segmented first
Distortion from skipping segmentation
Every model runs locally in your browser. Nothing you type is sent anywhere.
Frequently asked questions
Is the RFM Segment LTV (Concept Demo) free?
Yes. It runs instantly in your browser with no signup, and the methodology behind it is documented on this page.