Pipeline Stage Metrics

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.

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.

Total pipeline value with each deal multiplied by its stage-based close probability — the canonical probabilistic forecast number. More forecasting-useful than raw pipeline value because it accounts for the conversion-likelihood mix across stages (early-stage deals weighted ~10–25%, mid-stage ~40–60%, late-stage ~70–90%). Common pitfall: using globally-flat probabilities (e.g. always 50%) instead of stage-specific calibrated ones — a reliable weighted forecast requires the stage probabilities to be back-tested against actual close rates from prior periods.

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.

Average number of days from opportunity creation to closed-won status — measured only on won deals (lost deals are tracked separately). The motion-velocity metric — directly determines how much pipeline coverage is needed, how quickly investment in new reps pays back, and how feedback loops on packaging or pricing experiments compound. Common pitfall: blending segment cycles (SMB and Enterprise often differ 5–10×) into a single average hides material trend signals — segment-cut the metric where deal-volume permits.

Container handle for the three-section quarter-over-quarter compare object that tracks average days-to-close trend (lastQuarter / thisQuarter / improvement). Renders via the QuarterToQuarterImprovementGrid widget with three slots. The "is the motion getting faster or slower" diagnostic — cycle length trend is one of the most reliable leading indicators of ICP fit and packaging quality. Common pitfall: comparing without controlling for deal-size mix — if up-market mix is shifting, a flat cycle is actually an improvement (because up-market cycles are inherently longer). Note the mix context in commentary if material.