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Count of opportunities that transitioned to closed-lost during the period — the volume side of pipeline disqualification. The other half of the win rate denominator; without tracking it explicitly you cannot compute or benchmark win rate. Common pitfall: stale "open" deals that should be marked lost are left open, inflating pipeline value while suppressing the lost count — a hygiene problem that compounds because next-period coverage looks fine while win rates silently degrade. Every CRM hygiene policy should specify a max-age before deals auto-flag for lost-or-update review. — 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_lost_count Type: Number Domain: Sales

Definition

Formula

Closed-Lost Count = Count of distinct opportunities whose stage transitioned to closed-lost during the period. Store a non-negative count; subtract it when reconciling the open-pipeline bridge. Excludes "no decision" / paused opportunities (which should have a separate stage); excludes disqualified-pre-pipeline opportunities.

Why it matters

Denominator input for win rate and direct read on pipeline hygiene. Cluster analysis of loss reasons feeds product / pricing / positioning decisions that boards expect to see referenced in strategic_context.

How to interpret

Track loss-reason distribution quarter-over-quarter — concentration in "price" usually points to packaging; concentration in "feature gap" feeds product roadmap; concentration in "no decision" usually means lead-qualification is too loose. Pair count with value to spot mix-shift (e.g. losing more small deals while winning the large ones is a different motion problem than the inverse).

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

Count of distinct opportunities whose stage transitioned to closed-lost during the period.

Exclusion rules

"No decision" / paused opportunities — those belong in a separate stage, not in lost.
Disqualified-pre-pipeline opportunities (never bona-fide pipeline).
Closed-won opportunities (see sales.closed_won_count).

Required inputs

Opportunities with close date, final stage, and loss-reason code if available.
A stage convention that separates lost from no-decision / paused.

Data-source priority

CRM closed-lost report with loss-reason codes.
Rev-ops export as a fallback.

Edge cases

Stale "open" deals that should be lost are left open — this suppresses the lost count while inflating pipeline value; enforce a max-age lost-or-update review.
"No decision" lumped into lost — artificially depresses win rate; bucket it separately.

Validation checks

Count is a non-negative integer.
Denominator input for win rate alongside sales.closed_won_count.
Pair the count with sales.closed_lost_value to detect mix-shift (losing many small deals vs a few large ones).

Common miscomputations

Counting no-decision / paused outcomes as lost — distorts win rate.
Leaving stale deals open instead of marking them lost — silent win-rate degradation that compounds across periods.

sales.closed_lost_value
sales.closed_won_count
sales.win_rate
sales.competitive_alerts
sales.pipeline_risk_factors

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.