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win-loss-dataset

verified

Structure for capturing qualitative + quantitative win/loss insights

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gtm-agents

gtmagents/gtm-agents

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competitive-intelligence

strategy

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gtmagents/gtm-agents
60stars

plugins/competitive-intelligence/skills/win-loss-dataset/SKILL.md

Last Verified

January 22, 2026

Install Skill

Select agents to install to:

Scope:
npx add-skill https://github.com/gtmagents/gtm-agents/blob/main/plugins/competitive-intelligence/skills/win-loss-dataset/SKILL.md -a claude-code --skill win-loss-dataset

Installation paths:

Claude
.claude/skills/win-loss-dataset/
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Instructions

# Win/Loss Dataset Skill

## When to Use
- Running structured win/loss programs.
- Aligning qualitative interviews with CRM metrics.
- Sharing insights across product, sales, pricing, and marketing teams.

## Framework
1. **Data Model** – deal metadata (segment, region, product, stage), outcome, competitor, primary driver, secondary driver, confidence.
2. **Qualitative Tags** – categories for pricing, product gaps, implementation, support, brand, relationships.
3. **Quotes & Evidence** – key quotes, call clips, doc references with consent + access controls.
4. **Analytics Layer** – dashboards for driver frequency, trendlines, influence on win rate, revenue impact.
5. **Action Tracking** – link insights to backlog items, status, owner, and due date.

## Templates
- Interview note template with pre-defined tags + drop-downs.
- Dataset schema (CSV/Sheet/BI) with validated fields.
- Dashboard layout for driver trends + revenue impact.

## Tips
- Keep raw qualitative notes but publish sanitized, anonymized snippets for broader sharing.
- Standardize driver taxonomy every quarter to avoid drift.
- Pair with `run-win-loss-program` command for automatic dataset updates.

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