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win-loss-analysis

win-loss-analysis

Analyze why deals are won and lost and turn it into an action plan. Use when asked to run a win/loss analysis, review closed-won and closed-lost deals, understand why the team is losing to a competitor, or summarize sales feedback into patterns. Produces a structured win/loss report with themes, win/loss rates by segment and competitor, representative quote…

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name: win-loss-analysis description: "Analyze why deals are won and lost and turn it into an action plan. Use when asked to run a win/loss analysis, review closed-won and closed-lost deals, understand why the team is losing to a competitor, or summarize sales feedback into patterns. Produces a structured win/loss report with themes, win/loss rates by segment and competitor, representative quotes, and prioritized actions for product, marketing, and sales."

Win/Loss Analysis Skill

Turn raw deal outcomes and buyer feedback into a clear picture of why you win and lose — and what to do about it. The output should let a product marketer or revenue leader act on patterns, not anecdotes.

What This Skill Produces

  • A win/loss report with the top reasons deals were won and lost, ranked by frequency and deal value
  • Win/loss rates cut by segment, deal size, competitor, and source where the data allows
  • Representative buyer quotes that make each theme concrete
  • A prioritized action list mapped to product, marketing, sales, and pricing owners

Required Inputs

Ask for these if not provided:

  • Deal data — a list of closed-won and closed-lost deals, ideally with amount, segment, competitor, and stage lost
  • Feedback source — win/loss interview notes, CRM closed_lost_reason fields, survey responses, or call transcripts
  • Time window and any segmentation you care about (segment, region, product line)
  • Primary competitors to track explicitly
  • The decision this feeds — a QBR, a roadmap review, a messaging refresh, an enablement push

If the data is thin, say so and analyze what exists rather than inventing outcomes.

Process

  1. Normalize the reasons — collapse free-text loss reasons into a consistent taxonomy (price, product gap, timing/no-decision, competitor, champion left, poor fit, etc.).
  2. Quantify — count wins and losses per reason; weight by deal value; compute win rate overall and by cut.
  3. Separate controllable from structural — a missing feature is controllable; a genuine no-budget is not. Focus action on the controllable.
  4. Pull evidence — attach 1–2 real quotes per major theme. Never fabricate quotes; mark [quote to add] if none is available.
  5. Isolate competitor dynamics — where you lose to each competitor and on what basis.
  6. Recommend actions — for each top theme, the single highest-leverage move and who owns it.

Output Format


Win/Loss Analysis — [Period]

Scope: [N won · N lost · total value] · Segments: [list] · Source: [interviews / CRM / survey]

Headline

[2–3 sentences: overall win rate, the biggest swing factor, and the one thing to fix first.]

Why We Win (ranked)

#Reason% of winsNotable in
1[Reason][%][segment/competitor]

Evidence: "[buyer quote]"

Why We Lose (ranked)

#Reason% of lossesControllable?Est. value at stake
1[Reason][%]Yes/No/Partly[$]

Evidence: "[buyer quote]"

Win Rate by Cut

CutWin rateRead
[Segment / competitor / deal size][%][what it means]

Competitive Read

  • vs [Competitor]: [where and why we win/lose, and the counter]

Actions

ThemeRecommended actionOwnerEffortExpected impact
[Theme][Specific move][Product/PMM/Sales]S/M/L[win-rate or deal-value effect]

Deeper Materials

Quality Checks

  • Every reason is backed by counts, not vibes
  • Losses are split into controllable vs structural
  • Each major theme has a real quote or an explicit [quote to add]
  • Actions name an owner and the highest-leverage single move
  • Competitor findings are specific enough to change a battlecard

Anti-Patterns

  • Do not treat "price" as a root cause without checking whether it's really value perception
  • Do not average away segment differences — a 60% overall win rate can hide a 20% enterprise rate
  • Do not fabricate buyer quotes or inflate sample size; state the n
  • Do not list 15 actions — rank ruthlessly and name the top few
  • Do not blame sales or product reflexively; let the data assign the theme

Example Trigger Phrases

  • "Run a win/loss analysis on last quarter's closed deals"
  • "Why are we losing enterprise deals to [Competitor]?"
  • "Summarize these win/loss interviews into themes and actions"
  • "Turn our CRM closed-lost reasons into a report for the QBR"
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