Revenue Operations
Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization.
Before & after
Same prompt, same agent — the only difference is the skill.
Analyzing your sales pipeline and forecasting revenue requires looking at several dimensions. You'll want to understand how many deals are in each stage, how long deals typically spend in each stage, your historical close rates by stage, and what your average deal size is. You also need to consider seasonal patterns, historical forecast accuracy, and any changes in your sales team or process. Once you have that data, you can calculate your forecast confidence and identify where your pipeline might be weak or strong. If you can share some information about your current pipeline—number of deals by stage, average deal size, and your historical sales data—I can help you build out a more detailed analysis.
SALES PIPELINE HEALTH SCORECARD PIPELINE COVERAGE ANALYSIS -> Current MRR: $18,500 | Q4 target: $25,000 (need $6,500 gain) -> Requires: $7,500 pipeline (assuming 87% close rate) -> Current pipeline: $8,200 (healthy; 1.1x coverage ratio) -> Health: GREEN (above 1.0x) DEAL STAGE DISTRIBUTION Qualified Leads: 12 deals | $1,850 avg | $22,200 total | 8% close rate Proposal: 5 deals | $2,100 avg | $10,500 total | 45% close rate Negotiation: 2 deals | $3,400 avg | $6,800 total | 75% close rate -> Bottleneck: Qualified leads not converting to proposal (too many stalled) FORECAST ACCURACY Historical MAPE (Mean Absolute Percent Error): 18% Last 3-month prediction error: 12% (improving) Confidence level: 85% for Q4 forecast -> Action: Tighten Qualified stage criteria (reduce false leads) FORECAST WATERFALL (Q4) Pipeline → Assumed close: $8,200 × 0.87 = $7,134 Full-quarter recurring: $18,500 × 3 months = $55,500 Expansion deals (existing customers): +$2,800 (estimated) Q4 REVENUE FORECAST: $65,434 | Target: $75,000 | Gap: 12.8% -> Action needed: Accelerate lead gen or close negotiation deals early WEEKLY LEADING INDICATORS □ Proposal sends: 2+ per week (currently: 1.2/week; MISSING TARGET) □ Sales calls completed: 15+ per week (currently: 18/week; ON TRACK) □ Pipeline additions: 3-5 new deals weekly (currently: 2/week; BELOW TARGET)
About this skill
name: revenue-operations description: Use when Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization.
Revenue Operations
Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.
What you get
- Public GitHub repo (alirezarezvani/claude-skills)
- the revenue-operations skill folder with SKILL.md. Part of a 337-skill / 30-agent / 70-command install.
Customize your output
- Fork the repo and adapt the skill's instructions and references to your workflow.
Example output
Activates automatically when your request matches Revenue Operations; chains with the other skills, agents, and commands in the collection.
Best for
Creators, builders, and teams using Claude Code.
SKILL.md preview
---
name: revenue-operations
description: Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization.
version: 1.0.0
category: Business & Ops / Growth
author: AgentVolt
license: proprietary
tags:
- business-ops
- growth
---
# Revenue Operations
Turns raw pipeline and GTM data into a diagnostic on forecast accuracy, pipeline coverage, and sales efficiency, so leadership sees where revenue risk sits.
## When to use
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