New Opportunities Added
Definition
Total dollar value of new opportunities entering the pipeline during the period — the top-of-funnel inflow line in the pipeline flow. The single best read on the marketing-and-SDR engine's output. Common pitfall: counting inflated, un-qualified opportunities (e.g. every demo request) overstates the engine's output; restrict to opportunities that pass a defined qualification stage (typically SQL or higher) before counting. Boards expect this number to track forward quota — a quarter's top-of-funnel should be ~1× the same quarter's quota for a normal sales-cycle business.
Why it matters
Marketing/SDR output measured in dollars — directly determines whether future periods will have sufficient pipeline coverage. Trending down with stable conversion = future-period miss baked in 1–2 cycles out.
How it's calculated
New Opportunities Added (Value) = Σ deal_value across opportunities that entered the pipeline during the period (using the same qualification-stage floor and value convention as upstream metrics). Excludes deals re-opened from closed-lost (those should be tracked separately to avoid double-counting top-of-funnel). How to interpret it
New opportunities added should run ~1× of the comparable-period quota at steady state (i.e. the period's top-of-funnel feeds roughly the same period's closes via the sales cycle). Sustained sub-quota top-of-funnel for 2+ quarters is the canonical signal to invest in marketing or SDR capacity.
Source
imboard Editorial
Stage relevance
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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.
Total pipeline value at the start of the period — the baseline against which the period's pipeline flow (+ new opportunities − won − lost = closing) reconciles. Equal to the prior period's closing pipeline by construction. Surfaces in sales.pipeline_flow as the `start` slot. Common pitfall: restating opening pipeline to retroactively "clean up" stale deals masks the hygiene problem rather than addressing it; cleanup should happen via explicit "old-deal scrub" lines in the flow, not by editing the opening baseline.
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.
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.
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.
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