Accounts scored
—
Active book of business
Avg. churn risk
—%
90-day predicted probability
High-risk accounts
—
Risk ≥ 60
MRR at risk
—
Σ (MRR × churn probability)
Customer risk scores
| Customer | Tenure | Usage | Tickets | Disc. | Top risk factors | Churn risk▼ |
|---|
What-if simulator
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—%
—
Drag a slider to re-score
Why this score — risk attribution
Feature importance
Global weights the model places on each signal, learned across the full book. The what-if panel shows how these translate into one account's risk. Drag a slider to spotlight its bar.
Risk distribution
Selected (what-if)
Selected (actual)
Portfolio skews low-risk with a heavy tail — where retention effort pays.
How the score is computed (transparent, no black box)
Each account's 90-day churn probability is a logistic function of four normalized risk signals. Every term is inspectable — nothing is hidden:
risk = σ( 5.5 × ( Σ wᵢ · fᵢ − 0.5 ) ) where σ(x) = 1 / (1 + e⁻ˣ)
fᵤₛₐ𝓰ₑ= (100 − usage) / 100 — lower engagement, higher risk · weight 34%fₜᵢ𝒸ₖₑₜₛ= min(tickets / 12, 1) — support friction · weight 28%fₜₑₙᵤᵣₑ= clamp((24 − tenure) / 24) — newer accounts churn more · weight 22%f_disc= discount / 60 — deep discounts flag price sensitivity · weight 16%