Audience Intelligence
Who converts, who stays, who's at risk
Rule-based synthetic segmentation with a transparent, illustrative scoring formula.
120 of 120 Eney customers Synthetic Demo Data — Not MacPaw Actuals
Engagement vs. propensity score
Each dot is a synthetic customer
Conversion vs. estimated LTV by segment
LTV = avg monthly revenue × margin / segment churn assumption
Segment comparison
| Segment | Size | Activation | Paid conversion | Avg score | Est. LTV | |
|---|---|---|---|---|---|---|
| High-intent power users | 10 | 100% | 50% | 89 | $150 | |
| Curious explorers | 39 | 44% | 0% | 42 | — | |
| Low-engagement trial users | 50 | 16% | 0% | 14 | — | |
| Retained subscribers | 14 | 100% | 100% | 86 | $238 | |
| At-risk customers | 7 | 100% | 100% | 26 | $53 |
How segmentation works
This page uses rule-based synthetic segmentation, not trained clustering. The score is an illustrative formula, not a fitted model.