Docs

Win / Loss Analysis

Question it answers: Why do we win? Why do we lose? Who do we lose to, and what patterns distinguish won deals from lost ones?
Cadence: Monthly
GTM owner: PMM

Data sources

Internal: deals filtered to Closed Won and Closed Lost in the past rolling period. deal_qualification — specifically the competition dimension (who we competed against), binding_constraint on lost deals, and outcome_score at close. cluster_search scoped to interactions on closed-lost accounts — what themes appeared in those conversations. deal_stakeholders — champion/EB coverage on won vs. lost deals.

External: external_search { action: enrich_company } on a sample of closed-lost accounts — to understand the firmographic profile of companies we lose and whether there's a pattern (size, industry, tech stack, funding stage).

Living Document

A monthly deep analysis of wins and losses. This is one of the most important strategic documents for PMM and leadership. Sections:

  • Win/loss summary — counts, win rate, average deal size for won vs. lost, average sales cycle length for each
  • Why we win — top 3–5 differentiators that appear in won deals: themes from calls, qualification dimensions that were strongest, champion/EB coverage patterns
  • Why we lose — top 3–5 loss reasons: what binding constraints remained unresolved, which competitors took the deal, what themes surfaced in lost-account conversations
  • Competitor analysis — who we're losing to most often, what deals they tend to win (size, industry), and what the competitive conversation looks like in transcripts
  • ICP signal — firmographic patterns in won accounts (from enrichment + deal data) vs. lost accounts; where our ICP assumptions are validated or challenged
  • One deal deep dive — a single representative win and loss examined in detail
  • Recommended messaging or process changes based on the patterns

Page

A live view of won/lost deal data for ongoing monitoring between monthly reports.

Stats row:

  • Win rate (last 90 days)
  • Avg deal size — won vs. lost
  • Most common competitor in lost deals

Funnel chart: Deal count by outcome (won / lost / no-decision / open) for the last 90 days.

Bar chart: Loss reasons by binding_constraint type — shows which constraint category (functional / commercial / technical) kills the most deals.

Bar chart: Win/loss rate by competitor mentioned in deal_qualification.competition.

Table: Closed deals list — company, outcome, deal value, competitor (if any), binding_constraint, champion confirmed, EB confirmed, close date. Filterable by won vs. lost.

Scatter chart: Outcome_score at close (X) vs. deal value (Y), colored by won/lost — shows whether the model was predictive.