Weighted Feature Adoption
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. — Product 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: product.feature_adoption
Type: Percentage (%)
Domain: Product
Definition
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.
Formula
weighted_feature_adoption_pct = Σ (customer_arr × is_actively_using_feature) / Σ (customer_arr) × 100, where "actively using" is defined explicitly (e.g. ≥2 sessions in the last 4 weeks, or domain-appropriate usage threshold). Weight by ARR — not by customer count — to surface the strategic-account signal.Why it matters
Leading indicator of product-market fit for new capabilities. Adoption that does not reach a critical mass of ARR-weighted customers within 2–3 quarters is the strongest signal that the feature is either mis-targeted, mis-priced, or hidden in the UX. Drives roadmap continue-vs-cut decisions.
How to interpret
Industry folk-wisdom, not citation-grade: for a strategic feature, 30–50% ARR-weighted adoption within 6 months is healthy; below 20% after 6 months usually warrants a retrospective. The product-management literature (Marty Cagan, "INSPIRED"; Pendo / Amplitude product-analytics playbooks) consistently emphasizes the active-use definition over cumulative reach, but does not publish citation-grade numeric ranges by company stage. Always pair this with quality_churn_pct — high adoption that coincides with rising quality-churn means the feature is shipping pain alongside use.
Related KPIs
product.quality_churn_pctproduct.offensive_roadmap_pctproduct.portfolio_strategysales.arrcustomers.net_revenue_retention
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.
Industry benchmark
A reference distribution sourced from imboard Editorial (2026):
| Percentile | Value |
|---|---|
| 25th | 40% |
| Median | 60% |
| 75th | 75% |
Higher is better.
Stage relevance
| Company stage | Priority |
|---|---|
| Series A | Core |
| Series B | Core |
| Series C+ | Recommended |
| Public | Recommended |
Suggested for stages: Series A, Series B, Series C+, Public.
Default owning functions
- Product
Machine-readable
- This KPI as JSON:
/api/ontology/product/feature_adoption.json - All Product KPIs:
/api/ontology/product.json - Full catalog:
/api/ontology/index.json
Delivery Predictability
Percentage of committed deliverables shipped on or before the originally-promised date within a measurement window (typically a quarter). Surfaces whether the engineering organization can be trusted to hit commitments the company makes externally — to customers in contracts, to the board in quarterly plans, to GTM teams sequencing launches. Common pitfall: gaming. Teams over-deliver by under-promising (predictability climbs while velocity drops) or move the goalposts (re-baseline mid-quarter so "on-time" stays high). Boards should ask for "predictability against original commitment", not "against current plan", and pair with throughput trends. — Product KPI, I'mBoard-authored (editorial tier).
Innovation Capacity %
Percentage of R&D capacity (typically measured in engineering-weeks or story points over a quarter) allocated to net-new capabilities, as opposed to maintenance, bug fixes, internal tooling, or customer-support engineering. The "available bandwidth for offense" view. Common pitfall: confusing innovation capacity (input — how much team-time is available for new work) with `offensive_roadmap_pct` (output — what proportion of the planned roadmap is growth-oriented). A team can have 60% innovation capacity allocated entirely to defensive work if the roadmap demands it. Boards should look at both together. — Product KPI, I'mBoard-authored (editorial tier).