revenue-operations

Solid

Analyzes pipeline coverage, tracks forecast accuracy with MAPE, and calculates GTM efficiency metrics for SaaS revenue optimization

AI & Automation 740 stars 135 forks Updated 4 weeks ago NOASSERTION

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Skill Content

# Revenue Operations Pipeline analysis, forecast accuracy tracking, and GTM efficiency measurement for SaaS revenue teams. ## Table of Contents - [Quick Start](#quick-start) - [Tools Overview](#tools-overview) - [Pipeline Analyzer](#1-pipeline-analyzer) - [Forecast Accuracy Tracker](#2-forecast-accuracy-tracker) - [GTM Efficiency Calculator](#3-gtm-efficiency-calculator) - [Revenue Operations Workflows](#revenue-operations-workflows) - [Weekly Pipeline Review](#weekly-pipeline-review) - [Forecast Accuracy Review](#forecast-accuracy-review) - [GTM Efficiency Audit](#gtm-efficiency-audit) - [Quarterly Business Review](#quarterly-business-review) - [Reference Documentation](#reference-documentation) - [Templates](#templates) --- ## Clarify First Before running the analysis, confirm these inputs. If any is unknown or vague, ASK — do not assume: - [ ] **Which analysis** — pipeline health, forecast accuracy, or GTM efficiency (selects the script and its input schema) - [ ] **Quota / target** — the number pipeline coverage and Magic Number are measured against - [ ] **Data export readiness** — deals with stage/value/age/close-date, or forecast-vs-actual periods (the tools consume specific JSON; forecast trend needs 3+ periods) - [ ] **Company stage + sales motion** — seed vs growth, PLG vs enterprise (benchmarks vary widely by stage and motion) Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assum...

Details

Author
borghei
Repository
borghei/Claude-Skills
Created
8 months ago
Last Updated
4 weeks ago
Language
HTML
License
NOASSERTION

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