Pipeline Deal Count
Total number of active opportunities in the pipeline (open stages only — excludes closed-won and closed-lost). The volume side of pipeline coverage; paired with pipeline_value gives the average deal size and the deal-count vs deal-size ratio that characterizes the motion shape. Common pitfall: counting non-bona-fide opportunities (orphaned trials, demo requests that never converted to a real evaluation) inflates the number — apply a stage-floor cutoff (e.g. SQL or higher) so the count reflects committed evaluation activity. — 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.pipeline_deal_count
Type: Number
Domain: Sales
Definition
Total number of active opportunities in the pipeline (open stages only — excludes closed-won and closed-lost). The volume side of pipeline coverage; paired with pipeline_value gives the average deal size and the deal-count vs deal-size ratio that characterizes the motion shape. Common pitfall: counting non-bona-fide opportunities (orphaned trials, demo requests that never converted to a real evaluation) inflates the number — apply a stage-floor cutoff (e.g. SQL or higher) so the count reflects committed evaluation activity.
Formula
Pipeline Deal Count = Count of opportunities currently in any open stage (qualification through proposal / negotiation). Applies the same stage-floor convention quarter-over-quarter so trend is comparable.Why it matters
Volume-side health of the funnel — when value rises with falling count, deal sizes are growing (often deliberate up-market motion); when count falls without value compensation, top-of-funnel is the problem.
How to interpret
Read alongside average_deal_size and median_deal_size to characterize the motion shape: many small deals (high count / low size) implies a velocity / inside-sales motion; few large deals (low count / high size) implies an enterprise motion; mismatch between intended motion and observed shape is a strategic signal.
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 currently in any open stage (qualification through proposal / negotiation) — a point-in-time count.
- Apply a stage-floor (typically SQL or higher) so the count reflects committed evaluation activity, held constant across periods.
Exclusion rules
- Closed-won and closed-lost opportunities.
- Non-bona-fide opportunities below the stage floor (orphaned trials, unconverted demo requests).
- Splitting one multi-product opportunity into several deals — count the opportunity once (hold the counting unit constant).
Required inputs
- Open opportunities with stage at the snapshot date.
- The stage-floor convention.
Data-source priority
- CRM pipeline report at the snapshot date.
- Rev-ops export as a fallback — verify stage hygiene.
Edge cases
- Stale open deals inflate the count just as they inflate pipeline value — apply the same max-age hygiene rule.
- Parent / child or multi-product opportunities: pick a counting unit (opportunity vs account) and hold it constant with
sales.pipeline_value.
Validation checks
- Count is a non-negative integer.
- Identity:
sales.pipeline_value/ pipeline_deal_count =sales.average_deal_size— sanity-check the three together. - Trend should be smooth at steady state; step-changes usually mean a CRM cleanup or stage-floor change, not real-world motion.
Common miscomputations
- Counting sub-floor opportunities (every demo request) — inflates the funnel.
- Stage-floor drift across periods — produces phantom count growth / shrinkage.
- Counting closed-won or closed-lost deals in the open-pipeline count.
Related KPIs
sales.pipeline_valuesales.average_deal_sizesales.median_deal_sizesales.win_ratesales.pipeline_stage_metrics
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 |
|---|---|
| Series A | Recommended |
| Series B | Recommended |
| Series C+ | Recommended |
| Public | Recommended |
Suggested for stages: Series A, Series B, Series C+, Public.
Default owning functions
- Sales
Machine-readable
- This KPI as JSON:
/api/ontology/sales/pipeline_deal_count.json - All Sales KPIs:
/api/ontology/sales.json - Full catalog:
/api/ontology/index.json
Pipeline Context Notes
Container handle for the side-by-side contextual notes — pairs sales.pipeline_assumptions (left slot) with sales.pipeline_risk_factors (right slot) in the TwoColumnTextarea widget. Visually positions the "what we're assuming" narrative directly next to the "what could break those assumptions" narrative, forcing the team to write them in concert (rather than as two independent surfaces that drift apart over quarters). Common pitfall: writing assumptions without their corresponding risks (or vice versa) means the forecast is incomplete — every assumption should pair to a risk factor that captures the failure mode. — Sales KPI, I'mBoard-authored (editorial tier).
Pipeline Flow
Container handle for the additive / subtractive pipeline-flow bridge — reconciles opening pipeline to closing pipeline through the period's adds, wins, and losses (opening + new_opps − closed_won − closed_lost = closing) with dual count + value columns. Renders via the FlowSubform widget. The audit trail of the pipeline motion — without this, period-over-period pipeline changes are unexplained. Common pitfall: a "scrub" line (deals reclassified from open to lost mid-period) is needed to keep the math reconciling when CRM hygiene happens; without it the flow appears not to balance and trust in the underlying numbers erodes. — Sales KPI, I'mBoard-authored (editorial tier).