ARR at Risk
Definition
Sum of ARR from customers flagged "at-risk" by the customer-success team — typically driven by usage decline, low health score, executive turnover at the customer, missed milestones, or explicit churn intent. The board reads this as the worst-case near-term churn exposure if no intervention happens. Common pitfall: the "at-risk" definition drifts across CSMs and quarters; standardize the criteria (e.g. health score below threshold OR 30-day usage drop > X% OR cancellation request received) and version-control the playbook so the absolute number is comparable period-over-period. Pair with `percent_arr_at_risk` for the proportional read.
Why it matters
Converts the qualitative CS pipeline into a board-readable dollar exposure. Forces the team to put a number on hand-wavy customer-health concerns and surfaces concentration risk (a single $500K at-risk account is a different conversation than fifty $10K accounts).
How it's calculated
arr_at_risk = Σ(ARR of customers flagged at-risk by CS team). The "at-risk" flag itself is a company-specific definition (typical components: health score below threshold, 30-day usage decline, executive churn at customer, missed onboarding milestones, explicit churn signal). Document the flag rule in `customer_definition_note` so the number is comparable across periods. How to interpret it
Always present alongside `percent_arr_at_risk` — $500K at-risk is a 5% problem at $10M ARR but a 0.5% problem at $100M ARR. There is no citation-grade industry benchmark for the absolute number; the >15% destructive threshold the `ArrAtRiskGauge` widget uses is internal heuristic, not an external standard. Trend month-over-month — sustained growth in `arr_at_risk` is the leading indicator that NRR will deteriorate next quarter.
Source
imboard Editorial
Stage relevance
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Related KPIs
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.
Named at-risk accounts, root-cause analysis of why they're at risk, and the mitigation plan in flight. Pairs with the quantitative `arr_at_risk` and `percent_arr_at_risk` and gives the board the names + the playbook. Common pitfall: listing the at-risk accounts without the diagnosis or the plan — the board reader needs to see what the team is doing about it, not just what the team is worried about. Also: avoid using this surface as a generic "things are bad" venting forum — keep it account-specific and action-specific.
Share of total ARR contributed by the top N customers — typically top 5 or top 10. Measures revenue concentration risk: a high concentration means losing one big customer would materially dent ARR. The board reads this alongside `arr_at_risk` and the customer list to gauge how much of the company's future is tied to a handful of accounts. Common pitfall: hiding parent-account aggregation — if three "customers" are subsidiaries of the same parent, true concentration is higher than the count-by-logo view shows; settle parent-rollup rules and document them in `customer_definition_note`.
Recurring revenue retained from the cohort of customers present at the start of the period, including expansion (upsell, cross-sell, price increases) and net of churn and contraction — but excluding revenue from net-new logos acquired in-period. Per the SaaS Metrics Standards Board (SMSB) NRR standard. NRR above 100% means the cohort grew faster than it lost — a hallmark of strong product-led expansion. The board reads NRR alongside GRR (`customers.gross_revenue_retention`) to separate the "keep + expand" signal from the "just keep" signal. Common pitfall: mixing GAAP revenue and ARR in numerator vs. denominator, or letting net-new logo revenue leak in — both inflate the number; SMSB is explicit that the cohort is closed at period start.
Recurring revenue retained from the cohort of customers present at the start of the period, excluding expansion — so the metric captures only churn and contraction. Per the SaaS Metrics Standards Board (SMSB) GRR standard. GRR is bounded at 100% (cannot exceed it) and reads as the "no-defense-against-churn" floor on retention. The board reads GRR alongside NRR (`customers.net_revenue_retention`) — the gap between them is the expansion contribution. Common pitfall: treating GRR and NRR as substitutes — they answer fundamentally different questions, and a healthy NRR with sliding GRR signals churn masked by upsell.
Annual Recurring Revenue — the value of all recurring subscription revenue normalized to a one-year run-rate as of the period close. The headline operating metric for a subscription business; every growth and efficiency ratio (NRR, GRR, magic number, CAC payback, Rule of 40) is calibrated against it. Excludes one-time fees, professional services, and non-contractual usage. Common pitfall: confusing ARR (contracted recurring) with revenue (recognized) or with CARR (contracted incl. not-yet-live) — the SMSB standard draws sharp lines between them, and boards expect the same discipline. The KpiVarianceTable widget surfaces forecast / actual / variance / status / future-forecast columns against the same field.
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