Pipeline Deal Count
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.
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 it's calculated
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. How to interpret it
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.
Source
imboard Editorial
Stage relevance
Typically owned by
Related KPIs
Sum of the dollar value of all active deals currently in the sales pipeline — unweighted (raw deal-value sum, not probability-weighted). Boards read this as the top-of-funnel sufficiency check: if pipeline coverage (pipeline value / forecast) drops below the historic conversion-rate-implied threshold, the forecast is at risk. Common pitfall: confusing pipeline value with weighted forecast — the unweighted number always exceeds the weighted, often by 3–5× depending on the stage mix. Always report both and the implied conversion ratio.
Mean dollar value across active pipeline opportunities (Pipeline Value / Pipeline Deal Count). Distinct from sales.avg_contract_value (ACV) which measures closed-won deals — average_deal_size is forward-looking pipeline-shape, ACV is realized output. Common pitfall: a few oversized deals materially skew the average — always inspect median_deal_size alongside; a large gap between average and median signals a few mega-deals that drive most of the projected number, which concentrates pipeline risk.
Median dollar value across active pipeline opportunities — the typical deal in the pipeline, robust against the few-big-deals skew that distorts the average. The honest read on the "core motion" deal-size; if the team is winning a few oversized deals but the median is shrinking, the underlying motion is degrading even though the topline numbers look fine. Common pitfall: omitting median in dashboards in favor of just the average lets concentration risk hide. A best-practice board pack always shows both.
Percentage of closed opportunities that resulted in closed-won (vs closed-lost) during the period. The single best read on bottom-of-funnel execution and the most direct input to pipeline-coverage math (required coverage = 1 / win rate). Common pitfall: computing win rate without disqualifying "no decision" outcomes inflates losses and depresses the rate artificially; the SaaS norm is to either bucket no-decisions separately or track a two-rate view (raw win rate vs ICP-fit win rate excluding no-decisions). Stage-segment cuts (SMB vs Enterprise) usually differ 2×–4× and should be reported separately when volume permits.
Container handle for the per-stage pipeline metrics grid — for each pipeline stage (qualification, discovery, evaluation, proposal, negotiation, closing) tracks dealCount, totalValue, closingProbability, winRateFromStage, and avgTimeToClose. The most diagnostic surface in the pipeline view: where deals are bunching, which stage is the bottleneck, where conversion math is breaking. Rendered via the StageMetricsGrid widget seeded from PipelineStageValues. Common pitfall: trusting unchanged stage probabilities even as the deal mix shifts — re-calibrate the per-stage close rates quarterly against actuals or the weighted forecast drifts unreliably.
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