Skill

win-loss-dataset

Structures qualitative + quantitative win/loss insights with data models, tags, quotes, analytics dashboards, templates, and action tracking for sales/product teams.

data-engineering

From competitive-intelligence

Install

Run in your terminal

npx claudepluginhub gtmagents/gtm-agents --plugin competitive-intelligence

Tool Access

This skill uses the workspace's default tool permissions.

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Stats

Parent Repo Stars138

Parent Repo Forks24

Last CommitNov 19, 2025

Actions

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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

Data Model – deal metadata (segment, region, product, stage), outcome, competitor, primary driver, secondary driver, confidence.
Qualitative Tags – categories for pricing, product gaps, implementation, support, brand, relationships.
Quotes & Evidence – key quotes, call clips, doc references with consent + access controls.
Analytics Layer – dashboards for driver frequency, trendlines, influence on win rate, revenue impact.
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.