Average Contract Value (ACV)
Average annualized contract value across the active customer base (or across new logos, depending on the board's convention — document which). Expressed in the reporting currency. The board reads ACV alongside total customers to disambiguate logo-led vs. value-led growth, and against `customers.prior_quarter_acv` to see whether deal sizes are trending up (enterprise mix shift) or down (SMB dilution). Common pitfall: mixing new-logo ACV and blended-base ACV across periods — they trend differently; pick one and hold it. — 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.avg_contract_value
Type: Currency
Domain: Customers
Definition
Average annualized contract value across the active customer base (or across new logos, depending on the board's convention — document which). Expressed in the reporting currency. The board reads ACV alongside total customers to disambiguate logo-led vs. value-led growth, and against customers.prior_quarter_acv to see whether deal sizes are trending up (enterprise mix shift) or down (SMB dilution). Common pitfall: mixing new-logo ACV and blended-base ACV across periods — they trend differently; pick one and hold it.
Formula
ACV = total annualized contract value ÷ customer count, over the chosen population (active base or new logos). Hold the population definition constant period-over-period.Why it matters
The unit-economics lever beneath ARR — rising ACV with flat logo growth signals a successful move up-market; falling ACV signals SMB dilution or discounting.
How to interpret
Trend against customers.prior_quarter_acv for direction. Absolute ACV bands are segment-specific (SMB vs. enterprise) — industry folk-wisdom, not citation-grade.
Calculation policy
How an AI agent should compute this KPI from messy company data. Free-text rules consumed at reasoning time — not a deterministic DSL. The most common ways to get this wrong are listed under Common miscomputations.
Inclusion rules
- Numerator: total annualized contract value across the chosen population (active base OR new logos — document which and hold it constant).
- Denominator: the customer-logo count over the SAME population, using the same counting unit as
customers.total_customers. - Use annualized contract value (multi-year divided by term in years), expressed in the reporting currency; point-in-time as of the period close.
Exclusion rules
- One-time fees, services, and setup — same exclusions as ARR; ACV is contracted-recurring per logo.
- Mixing new-logo ACV and blended-base ACV across periods — pick one population convention and hold it.
- Trials / $0 contracts in the denominator.
Required inputs
- Total annualized contract value for the chosen population, same period.
- Customer-logo count for that population (same logo unit as
total_customers). - The population-definition flag (active base vs. new logos).
Data-source priority
- Billing / subscription ledger (annualized contract value) ÷ the same logo source as
customers.total_customers. - CRM as a fallback — verify the population and logo unit match.
Edge cases
- A single very large enterprise deal pulls the mean up — surface median deal size alongside when one mega-deal masks the distribution.
- Multi-currency base: normalize to the reporting currency at a stable rate before averaging.
- Mid-period logo-unit change makes ACV non-comparable across the boundary — re-state.
Validation checks
- ACV = total annualized contract value ÷ customer count — recompute against any pre-computed value.
- ACV × customer count ≈ the population's total ARR within rounding.
- Compare to
customers.prior_quarter_acvonly when the population definition matches.
Common miscomputations
- Mixing new-logo ACV in one period with blended-base ACV in another — the trend becomes an artifact of the population swap, not a price move.
- Using TCV instead of annualized value — overstates by the contract term.
- Counting logos with a different unit than the numerator's population — produces nonsense.
- Letting a single mega-deal set the headline ACV without flagging the outlier.
Related KPIs
customers.prior_quarter_acvcustomers.total_customerscustomers.new_customers_addedsales.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 |
|---|---|
| Pre-Seed | Core |
| Seed | Core |
| Series A | Core |
| Series B | Core |
| Series C+ | Core |
| Public | Core |
Suggested for stages: Pre-Seed, Seed, Series A, Series B, Series C+, Public.
Default owning functions
- Sales
- Finance
Machine-readable
- This KPI as JSON:
/api/ontology/customers/avg_contract_value.json - All Customers KPIs:
/api/ontology/customers.json - Full catalog:
/api/ontology/index.json
ARR at Risk
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. — Customers KPI, I'mBoard-authored (editorial tier).
Churn Risks
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. — Customers KPI, I'mBoard-authored (editorial tier).