SKILL

Win Loss Dataset

Structure for capturing qualitative + quantitative win/loss insights with consistent tagging.

Published by @gtmagents·from gtmagents/gtm-agents·0 agent reads / 30d·0 saves·

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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