Churn from Quality Issues

Percentage of customers (weighted by ARR) actively using a defined set of strategic features within a measurement window. The "ARR-weighted" framing matters: a feature used by 30% of customers covering 70% of ARR is a different signal than 30% of customers covering 5% of ARR. Common pitfall: defining adoption as "ever used" rather than "actively using" (returning use in the measurement window) — the first metric only goes up and tells the board nothing. Boards should require an active-use definition (e.g. used in 2 of the last 4 weeks) and a per-feature breakdown for the strategic feature set.

Percentage of the planned roadmap allocated to defensive work — platform reliability, security/compliance, scalability rearchitecture, table-stakes parity with competitors, customer-retention features. The complement of `offensive_roadmap_pct`. Common pitfall: defensive work is chronically under-funded (less visible to customers, harder to demo) until a quality-churn or scalability event forces a reactive surge. Boards should treat sustained zero or near-zero defensive allocation in a maturing product as a leading indicator of future quality issues — per the standard product-management argument (Marty Cagan and similar product-leadership writing), a healthy roadmap pays both growth and platform-health rent.

Months of system capacity remaining at the current growth rate before the platform requires major (not incremental) infrastructure investment — typically driven by the binding bottleneck (database, message bus, single-tenant compute ceiling, regional capacity, or compliance-driven re-architecture). Surfaces the "scale runway" alongside the financial runway. Common pitfall: a single number hides which bottleneck binds. Boards should require the bottleneck to be named ("database shard hot-spot binds at ~150K accounts at current growth, ~4 months out"), not just the headline months — a named bottleneck makes the investment decision concrete.

Share of customer logos lost during the period — the inverse of logo retention. Numerator is logos that churned during the period; denominator is logos present at period start. Per the KBCM/Sapphire Private SaaS Company Survey definition (treated as the de-facto private-SaaS reporting convention). The board reads this as the simplest churn signal — independent of revenue-weighting. Common pitfall: confusing annualized vs. period-rate (monthly churn × 12 ≠ annualized churn for a compounding base) — be explicit about the time window and annualization method.

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.