Lead Scoring

This builds lead scoring models that combine firmographic fit, behavioral signals, and intent data to help you prioritize which leads your sales team should call first. It walks you through setting up point values for company size, job titles, content engagement, and buying intent, then applies the model to score individual leads on a 0-100 scale with MQL thresholds. Based on HubSpot's methodology, it includes negative scoring for disqualifying signals like bounced emails or competitor domains. Most useful when you're drowning in inbound leads and need a systematic way to route hot prospects to SDRs within minutes instead of letting them sit in a queue. The scoring tables are opinionated but customizable to your ICP.

skills.sh installs: 226
GitHub stars: 150
last updated: Aug 21, 2026

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Install

$ npx -y skills add guia-matthieu/clawfu-skills --skill lead-scoring --agent claude-code

Installs into .claude/skills of the current project.

Files

Lead Scoring

Prioritize leads using a systematic scoring model that combines ICP fit, engagement behavior, and buying intent signals.

When to Use This Skill

Designing a new lead scoring model
Prioritizing inbound leads for SDR follow-up
Setting MQL thresholds for sales handoff
Analyzing lead quality by source
Optimizing marketing spend by lead score

Methodology Foundation

Based on HubSpot's Lead Scoring methodology and Forrester's B2B Buyer Journey research, combining:

Firmographic/demographic fit (who they are)
Behavioral scoring (what they do)
Intent signals (buying readiness)
Negative scoring (disqualification)

What Claude Does vs What You Decide

Claude Does	You Decide
Designs scoring model structure	Point values for your business
Calculates lead scores	MQL threshold for handoff
Identifies high-intent behaviors	Which behaviors matter most
Segments leads by score	Sales follow-up priorities
Suggests model improvements	Model weight adjustments