Deals Won Value
Definition
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.
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 it's calculated
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. How to interpret it
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).
Source
imboard Editorial
Stage relevance
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Related KPIs
Count of opportunities that reached closed-won status during the period — the volume side of the period's sales output. Paired with closed_won_value gives the period's average won-deal size, a critical mix-shift indicator. Common pitfall: counting opportunity stage transitions rather than discrete deal closes (re-opened deals inflate the count). Boards read the trend over 4+ quarters to detect motion-volume stability — sharp drops while pipeline holds usually mean late-stage conversion has broken.
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.
The team's expected closed-won dollars for the current quarter — usually a sales-leader judgment call informed by weighted forecast but adjusted for deal-by-deal commit confidence. Distinct from weighted_forecast (which is mechanical, stage × probability). Boards read both: a quarterly_forecast materially below weighted_forecast means the team has explicit negative judgment on specific big deals; above it means they're calling deals stronger than the stage probabilities suggest. Common pitfall: anchoring the call to plan rather than reality — boards quickly learn to discount "we will hit plan" forecasts and reward calibrated commit-vs-actual track records.
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.
Annualized recurring revenue booked from net-new logos (first-time customers) during the period. This is the "hunt" line of the ARR waterfall — the output of the new-customer acquisition motion, distinct from expansion (existing-customer upsell) and from churn / downgrades. Common pitfall: counting renewals or expansion deals as new business inflates the new-logo conversion engine and hides a stalled acquisition motion. The KpiVarianceTable widget shows period forecast vs actual; downstream views compare it to S&M spend to derive new-business CAC and CAC payback.
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