Deals Lost

Total dollar value of opportunities closed-lost during the period — the opportunity-cost view on the pipeline motion. Useful for sizing the "what we missed" gap and prioritizing post-mortem efforts on the highest-value losses. Common pitfall: post-mortems on small lost deals waste time relative to insight; tier the post-mortem cadence by value (e.g. every loss above the 80th-percentile deal size gets a written debrief). Boards expect the largest 2–3 losses to be explained explicitly in commentary.

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.

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.

Narrative read on competitive dynamics affecting the sales motion — material wins / losses to specific competitors, observed pricing or packaging moves in the market, new entrants, M&A in the competitive set. Boards use this surface to bring outside intelligence (their other portfolio companies, advisors) to bear on the competitive picture. Common pitfall: listing competitor names without quantifying how often they show up in deal cycles — a "Competitor X is being aggressive" entry without "we saw them in 8 of 20 active deals last quarter, up from 3 of 18" is too vague to act on.

Narrative listing the material risks to pipeline conversion or deal timing — specific deal slips, segment headwinds, budget freezes, competitive entry, ICP-fit misses on late-stage deals. Distinct from sales.key_concerns (which covers the whole sales motion) — this is specifically about the forecast / pipeline conversion math. Common pitfall: vague risks ("market is choppy") aren't actionable; a useful entry quantifies the at-risk dollar amount and names specific deals or segments. Renders side-by-side with sales.pipeline_assumptions in the TwoColumnTextarea widget.