What factors influence the deal scoring model?

The model evaluates six key factors: ICP Fit (20%), Champion (25%), Authority (20%), Need (15%), Timeline (10%), and Competition (10%).

What categories are used in this forecasting model?

The skill uses four primary categories: Commit (90% weight), Best Case (70% weight), Pipeline (30% weight), and Upside (10% weight).

What counts as a high-confidence commit in this framework?

In this model, a deal scoring between 85-100% on the weighted components is considered a high-confidence commit, while scores below 50% are flagged as at-risk.

How is the weighted pipeline calculated?

The weighted pipeline is calculated by multiplying the total Deal Value by the Stage Probability and a specific Confidence multiplier (e.g., 1.1x for high confidence).

Pipeline Forecasting

Name: Pipeline Forecasting
Author: majesticlabs-dev

bymajesticlabs-dev

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Productivity & Workflow

Implements standardized B2B sales forecasting models and deal scoring frameworks to improve revenue predictability.

About

The Pipeline Forecasting skill provides Claude with comprehensive frameworks for B2B sales management, including weighted pipeline calculations, deal scoring models based on ICP fit and stakeholder engagement, and structured weekly review templates. It enables sales teams and operations professionals to categorize deals accurately into Commit, Best Case, Pipeline, and Upside categories while applying quantitative metrics to assess forecast health. This skill helps eliminate guesswork by using a structured approach to analyze deal probability, buyer authority, and timeline urgency to generate more accurate revenue projections.

Key Features

Comprehensive deal scoring model based on ICP fit, authority, and need
Standardized forecast categorization (Commit, Best Case, Pipeline, Upside)
Forecast accuracy metrics for tracking commit and pipeline reliability
19 GitHub stars
Structured weekly forecast review templates for consistent reporting
Weighted pipeline calculation using stage probability and confidence multipliers

Use Cases

Creating a structured weekly pipeline report for sales leadership teams
Generating a weighted revenue forecast for an upcoming executive sales meeting
Auditing a specific deal's health using a quantitative scoring model

About

Key Features

Comprehensive deal scoring model based on ICP fit, authority, and need
Standardized forecast categorization (Commit, Best Case, Pipeline, Upside)
Forecast accuracy metrics for tracking commit and pipeline reliability
19 GitHub stars
Structured weekly forecast review templates for consistent reporting
Weighted pipeline calculation using stage probability and confidence multipliers

Use Cases

Creating a structured weekly pipeline report for sales leadership teams
Generating a weighted revenue forecast for an upcoming executive sales meeting
Auditing a specific deal's health using a quantitative scoring model