% ARR at Risk
Share of total ARR flagged as at-risk for churn or contraction — the proportional view that complements the absolute `arr_at_risk` dollar figure. Computed as `arr_at_risk ÷ total ARR`. The board reads this as the worst-case-near-term-NRR-impact ceiling: if every at-risk account actually churned in-period, NRR would drop by roughly this percentage (before expansion offset). Common pitfall: the "at-risk" definition is internal and varies by company — a 12% percent_arr_at_risk under a conservative flagging rule is a very different signal than 12% under an aggressive rule. Document the flag rule and hold it constant. — Customers KPI, I'mBoard-authored (editorial tier).
I'mBoard-authored (editorial tier)
No public third-party standard anchors this KPI yet, so I'mBoard authors and maintains the definition — transparently labeled as editorial tier. See the ontology methodology for the published vs editorial tier system and the back-attribution workstream.
Rogue ID: customers.percent_arr_at_risk
Type: Percentage (%)
Domain: Customers
Definition
Share of total ARR flagged as at-risk for churn or contraction — the proportional view that complements the absolute arr_at_risk dollar figure. Computed as arr_at_risk ÷ total ARR. The board reads this as the worst-case-near-term-NRR-impact ceiling: if every at-risk account actually churned in-period, NRR would drop by roughly this percentage (before expansion offset). Common pitfall: the "at-risk" definition is internal and varies by company — a 12% percent_arr_at_risk under a conservative flagging rule is a very different signal than 12% under an aggressive rule. Document the flag rule and hold it constant.
Formula
percent_arr_at_risk = arr_at_risk ÷ total ARR. The numerator inherits the company-specific "at-risk" flag definition documented on `customers.arr_at_risk`.Why it matters
Normalizes the at-risk dollar figure so it scales with the business. A 10% at-risk share is the same proportional threat at $5M ARR as at $50M ARR; the absolute figure alone hides that.
How to interpret
No citation-grade industry benchmark; widely-cited industry folk-wisdom (not citation-grade) flags >15% percent_arr_at_risk as a destructive threshold worth board escalation — the ArrAtRiskGauge widget uses this internally. Trend it month-over-month — sustained growth in this share predicts a downward NRR move next quarter even if no single account has churned yet.
Related KPIs
customers.arr_at_riskcustomers.churn_riskscustomers.top_customer_concentrationcustomers.net_revenue_retentioncustomers.gross_revenue_retentionsales.arr
Source
I'mBoard editorial — authored and maintained by I'mBoard, first published 2026-04-01. No third-party standard is cited for this KPI; when one emerges, the definition is back-attributed and promoted to the published tier (a minor version bump). Read the ontology methodology for the published vs editorial tier system, attribution rules, and dispute process.
Stage relevance
| Company stage | Priority |
|---|---|
| Series A | Core |
| Series B | Core |
| Series C+ | Core |
| Public | Core |
Suggested for stages: Series A, Series B, Series C+, Public.
Default owning functions
- Sales
Machine-readable
- This KPI as JSON:
/api/ontology/customers/percent_arr_at_risk.json - All Customers KPIs:
/api/ontology/customers.json - Full catalog:
/api/ontology/index.json
NPS Trend
Period-over-period change in NPS score — the trajectory signal that matters more than any single absolute score. A 5-point swing between adjacent quarters is usually more informative than a "good" or "bad" absolute label, because the methodology's noise floor is high enough that absolute comparisons across companies (or even across quarters with different sample sizes) are unreliable. The board reads this to spot deterioration early — a persistent multi-quarter decline is one of the leading indicators of pending churn. Common pitfall: comparing periods with very different sample sizes or response rates — a "decline" from 45 to 35 means very different things at n=30 vs. n=300. — Customers KPI, I'mBoard-authored (editorial tier).
Retention Insights
Free-form commentary from the CS / Sales leadership on retention trends, cohort behavior, and underlying drivers of loyalty (or its absence). Pairs with the quantitative retention KPIs (NRR, GRR, logo retention) and gives the board the "why" behind the numbers — which cohorts are strong, which are weak, what feature engagement correlates with retention, what onboarding changes are landing. Common pitfall: filler prose that restates the numbers without adding causal insight — a board reader should learn something here they could not infer from the metrics page alone. — Customers KPI, I'mBoard-authored (editorial tier).