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Total dollar value of all opportunities closed-won during the period — the period's realized bookings from the pipeline motion. Reconciles to (sales.new_business + sales.expansion) when split by deal type. Common pitfall: reporting TCV (total contract value) here when the rest of the dashboard uses ACV — pick one and apply it consistently across closed_won_value, weighted_forecast, and pipeline_value, or the dashboard math stops reconciling. — Sales 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: sales.closed_won_value Type: Currency Domain: Sales

Definition

Formula

Closed-Won Value = Σ (deal_value) across opportunities that transitioned to closed-won in the period. The "deal_value" convention (TCV vs ACV) must match the pipeline-tracking convention for the math to reconcile.

Why it matters

Realized bookings — the period's actual sales output. Sum across periods should reconcile to total new-customer + expansion CARR additions; gaps indicate either revenue-recognition policy or stage-data-quality issues.

How to interpret

Closed-Won Value / Quota gives the period's attainment percentage — > 100% is over-plan, 80–100% is the typical "acceptable" band, < 80% triggers the post-mortem cycle. Read alongside Win Rate to identify whether misses are pipeline-driven (low value but normal win rate) or execution-driven (normal value, depressed win rate).

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

Σ deal_value across opportunities that transitioned to closed-won in the period — the realized bookings from the pipeline motion.
Use ONE value convention (TCV or ACV) and apply it consistently with sales.pipeline_value and sales.weighted_forecast.

Exclusion rules

Closed-lost value (see sales.closed_lost_value).
Recognized or invoiced revenue — closed-won value is bookings (signed), NOT earned revenue (sales.total_revenue) and NOT an annualized run-rate (sales.arr).
Re-opened-then-re-won double counts.

Required inputs

Closed-won opportunities with deal_value and close date.
The value convention (TCV vs ACV) in force.

Data-source priority

CRM closed-won report for the period.
Finance bookings ledger as a cross-check.

Edge cases

TCV-vs-ACV: pick one — reporting TCV here while the rest of the dashboard is ACV breaks reconciliation.
Multi-year deals: the convention decides whether the full TCV or the annualized value lands on this line.
When split by deal type, closed-won value reconciles to sales.new_business + sales.expansion (the live-ARR subset). Cross-reference those already-hardened ARR-movement lines; do NOT restate their waterfall here.

Validation checks

closed_won_value ≥ 0.
Sum across periods reconciles to total new-customer + expansion CARR additions; persistent gaps indicate revenue-recognition policy or stage-data-quality issues.
closed_won_value / quota = the period attainment percentage.

Common miscomputations

Reporting TCV here while using ACV elsewhere — breaks the dashboard math.
Conflating closed-won bookings with recognized revenue (sales.total_revenue) or with the ARR run-rate (sales.arr).
Double-counting re-opened / re-won deals.
Duplicating the ARR-movement waterfall (sales.new_business / sales.expansion) on this line instead of cross-referencing it.

sales.closed_won_count
sales.weighted_forecast
sales.quarterly_forecast
sales.win_rate
sales.new_business

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.