Skill

variance-analysis

Attributes revenue forecast vs actual deltas to drivers like volume, conversion, price/mix, churn; analyzes root causes and recommends remediation actions with owners. For forecast reviews and board updates.

data-engineering

From revenue-forecasting-pipeline

Install

Run in your terminal

npx claudepluginhub gtmagents/gtm-agents --plugin revenue-forecasting-pipeline

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

View Source View Plugin View on GitHub View README

Revenue Variance Analysis Skill

When to Use

Preparing forecast reviews or board updates that require variance explanations.
Investigating misses/exceeds across segments, products, or channels.
Prioritizing remediation plays tied to specific variance drivers.

Framework

Driver Taxonomy – classify deltas into volume, conversion, price/mix, churn, expansion, currency.
Attribution Logic – define formulas for each driver and maintain consistent baselines.
Root Cause Layer – connect drivers to operational issues (pipeline quality, capacity, enablement, macro).
Action Mapping – translate each root cause into specific plays with owners and expected impact.
Feedback Loop – update forecasting assumptions once variance is understood.

Templates

Variance waterfall chart setup instructions.
Driver worksheet (metric → delta → driver → root cause → owner → due date).
Remediation tracker with status and forecast impact.

Tips

Keep a glossary so stakeholders interpret drivers consistently.
Combine quantitative attribution with qualitative context from GTM leaders.
Feed learnings back to forecast-modeling to tighten assumptions next cycle.