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COMMUNITY SKILL — included under its original MIT license.
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Win/loss analysis
Analyze sales call transcripts to extract actionable insights on why deals are won, lost, retained, or churned. Cross-reference findings with ICP, firmographics, and competitive context to produce strategic recommendations.
Knowledge type: win-loss-analysis
Maturity on first run: emergent → validated after team review
Claude Code triggers
Invoke when user says:
- "Win/loss analysis"
- "Analyze sales calls"
- "Why did we win/lose"
- "Churn analysis"
- "Retention analysis"
- "Sales call insights"
- "Deal outcome patterns"
- "Customer feedback synthesis"
- "Analyze these transcripts"
- "What patterns in our sales calls"
Do NOT invoke when:
- User wants general transcript analysis → use a generic transcript skill
- User wants competitor research → use
competitor-research
- User wants a single customer interview write-up → use a transcript skill
- User wants sales enablement assets → use a sales-enablement skill
Input requirements
Required
| Input |
Description |
Source |
| Transcripts |
Sales call transcripts with customer name and outcome |
User provides |
| Outcome |
Win/Loss/Retention/Churn for each call |
User specifies or infer |
Optional (improve quality)
| Input |
How it helps |
| Website URL per customer |
Firmographics cross-reference |
| Product/ICP document |
Define in-scope product capabilities |
| Market/GTM document |
Positioning and competitive landscape |
| Sales notes column |
Additional context (stage, deal size) |
| Competitor names |
Pre-identify competitors to watch for |
Validation
Before proceeding: at least one transcript provided; outcome known or inferable from transcript; customer name identifiable.
If inputs are missing: ask the user for transcripts. Clarify if outcome should be inferred from transcript signals.
Transcript intake — normalize, redact, bind to evidence
Transcripts arrive in many shapes (Gong, Fireflies, Otter, Grain, Zoom/Avoma VTT, SRT, recorder JSON, or plain pasted text). Before Phase 1, normalize whatever you're handed into one shape — speaker-attributed turns with timestamps where present. Two rules apply to every transcript before analysis:
- Redact PII first. Mask end-client names, emails, and account numbers before processing; keep roles, company, and deal context. (Load-bearing for regulated industries.)
- Bind every claim to evidence. Every extracted pattern cites a verbatim quote plus the speaker; normalized, speaker-attributed turns make that attribution reliable.
Process
The analysis runs in 3 phases. Read references/process.md for the full step-by-step (4 transcript-processing steps, 4 aggregation steps, 4 synthesis steps, plus per-phase checkpoints and the process flowchart).
Phase summary:
- Transcript processing — classify outcome, identify speakers, extract customer context, pull verbatim quotes for the 6 dimensions
- Pattern aggregation — group by outcome, count frequency, rank patterns (3+ mentions), cross-reference by ICP/competitor/persona
- Insight synthesis — state pattern, provide evidence with frequency + confidence, identify opportunity, generate executive summary
Core frameworks
Analysis modes
| Mode |
When to use |
Output |
| Single call |
Deep analysis of one transcript |
Full insight extraction per dimension |
| Batch analysis |
Multiple transcripts (3-20 calls) |
Aggregated patterns with frequency counts |
| Comparison matrix |
Win vs. loss OR retention vs. churn |
Side-by-side pattern comparison |
Default to batch analysis mode when multiple transcripts are provided.
6 analysis dimensions
| # |
Dimension |
Win signals |
Loss signals |
| 1 |
Product |
"Exactly what we need," feature praised |
"Missing [feature]," "Doesn't do [X]" |
| 2 |
Messaging |
"Now I understand why this matters" |
"What does it actually do?" |
| 3 |
GTM/Sales |
"You really understand our problem" |
"Demo didn't address our needs" |
| 4 |
Pricing |
"Fair price," "good value" |
"Too expensive," "over budget" |
| 5 |
Competition |
"Chose you over [competitor]" |
"Going with [competitor]" |
| 6 |
Customer context |
"Need this now," deadline-driven |
"No rush," "maybe next year" |
Confidence scoring
| Level |
Definition |
When to apply |
| High |
3+ calls with consistent pattern |
Clear recurring theme |
| Medium |
2 calls or inferred from strong signals |
Emerging pattern |
| Low |
Single mention or indirect reference |
Possible outlier |
Outcome classification
| Outcome |
Definition |
Key signals |
| Win |
Deal closed, contract signed |
"We're moving forward," pricing confirmed |
| Loss |
Deal lost to competitor or no-decision |
"Going with [competitor]," "Not right now" |
| Retention |
Existing customer renewing/expanding |
Renewal discussion, expansion |
| Churn |
Existing customer leaving/reducing |
Cancellation, "not getting value" |
Output
Produce a single win/loss report markdown file. Template + iteration prompts library: references/output-format.md.
Pre-delivery quality checklist + worked example + anti-examples: references/quality.md.
Auto-update protocol (feedback signals, pattern detection, skill-update template): references/auto-update.md.
Anti-hallucination guardrails
- Quote verbatim. All insights must trace to specific transcript quotes.
- Never invent patterns. If a pattern appears in only one call, label it "Single mention — pattern unconfirmed."
- State frequency. Always note how many calls support each finding (e.g., "4 of 7 calls").
- Acknowledge gaps. If a dimension has no data, mark "Not discussed in transcripts."
- Distinguish roles. Tag who said what — prospect vs. sales rep vs. champion.
Gotchas
- Correlation as causation. Reports "deals with longer sales cycles were lost" as if cycle length caused the loss → always distinguish patterns from causes. Use "associated with" not "caused by".
- Small sample bias. Draws conclusions from 2-3 deals instead of waiting for sufficient data → flag sample size prominently. Minimum 5 wins and 5 losses for reliable patterns.
- Missing verbatim quotes. Summarizes what buyers said instead of extracting exact quotes → verbatim quotes are the primary deliverable. Summaries are secondary.
- Single-dimension analysis. Only looks at win/loss by competitor, missing dimensions like deal size, ICP segment, or sales cycle stage → cross-tabulate across at least 3 dimensions.
- Conflates product feedback with sales insights. Mixes "they wanted feature X" with "they didn't trust our team" → separate product gaps from sales execution issues. They feed into different downstream work.
Integration with other skills
| Skill |
Relationship |
Usage |
| transcript analysis |
Related |
Use for general transcripts, not sales calls |
| sales enablement |
Downstream |
Feed insights into battlecards and objection handlers |
| product messaging |
Downstream |
Update messaging based on win patterns |
| competitor research |
Related |
Cross-reference competitor mentions |
Reference files
Data integration
Level: 0 — Context (heavy pulls)
If you run win/loss inside a connected environment, pull transcripts and deal context fresh:
| Source |
What to pull |
When |
| Meeting recorder (Granola, Gong, Fireflies, etc.) |
Sales call transcripts and deal discussions |
Always |
| Team chat (Slack, etc.) |
Deal discussion threads and competitive intel |
Always |
Fallback (no integrations): user-provided call transcripts or recordings; manual deal review notes.
Changelog
| Version |
Date |
Changes |
| 2.0 |
2026-01-16 |
Refactored to v2.0 template: structured phases, evidence-ready insights, iteration prompts, auto-update rules |
| 1.0 |
Previous |
Initial skill creation with 6 dimensions |