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Win Loss Analysis

skill-matteotitta-genesys-skills-win-loss · by matteotitta

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Install

$ agentstack add skill-matteotitta-genesys-skills-win-loss

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

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](./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:

  1. Transcript processing — classify outcome, identify speakers, extract customer context, pull verbatim quotes for the 6 dimensions
  2. Pattern aggregation — group by outcome, count frequency, rank patterns (3+ mentions), cross-reference by ICP/competitor/persona
  3. 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](./references/output-format.md).

Pre-delivery quality checklist + worked example + anti-examples: [references/quality.md](./references/quality.md).

Auto-update protocol (feedback signals, pattern detection, skill-update template): [references/auto-update.md](./references/auto-update.md).


Anti-hallucination guardrails

  1. Quote verbatim. All insights must trace to specific transcript quotes.
  2. Never invent patterns. If a pattern appears in only one call, label it "Single mention — pattern unconfirmed."
  3. State frequency. Always note how many calls support each finding (e.g., "4 of 7 calls").
  4. Acknowledge gaps. If a dimension has no data, mark "Not discussed in transcripts."
  5. 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

| File | Purpose | |------|---------| | [references/process.md](./references/process.md) | Full 3-phase step-by-step + flowchart | | [references/output-format.md](./references/output-format.md) | Win/loss report template + iteration prompts | | [references/quality.md](./references/quality.md) | Pre-delivery checklist + worked example + anti-examples | | [references/auto-update.md](./references/auto-update.md) | Feedback signal detection + pattern rules | | [references/extraction-patterns.md](./references/extraction-patterns.md) | Signal patterns for each dimension | | [references/output-template.md](./references/output-template.md) | Legacy report template (kept for reference) | | [references/example-analysis.md](./references/example-analysis.md) | Worked example with 5 transcripts |


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 |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.