/lead-scoring

name: lead-scoring
description: Build and apply lead scoring models combining firmographic fit, behavioral signals, and intent data for sales prioritization
license: MIT
metadata:
  author: ClawFu
  version: 1.0.0
  mcp-server: "@clawfu/mcp-skills"

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 |

What This Skill Does

1. **Model design** - Create scoring framework with fit + behavior + intent 2. **Score calculation** - Apply model to lead data 3. **Threshold setting** - Define MQL/SQL qualification levels 4. **Segmentation** - Group leads by score for routing 5. **Optimization** - Analyze score-to-conversion correlation

How to Use

For Model Design:

Help me create a lead scoring model for [Business Type].

Our ICP:
- Company size: [Range]
- Industries: [List]
- Titles: [Target titles]
- Geography: [Regions]

Key buying signals we track:
- [List website pages, content, actions]

Current conversion rates:
- Lead to MQL: X%
- MQL to SQL: X%
- SQL to Won: X%

For Lead Scoring:

Score this lead:

Company: [Name]
Size: [Employees]
Industry: [Industry]
Title: [Contact title]
Location: [Geography]

Behavior (last 30 days):
- [List pages visited, content downloaded, emails opened]

Instructions

Step 1: Define Fit Score (0-40 points)

**Company Firmographics:** | Criteria | Points | |----------|--------| | Company size matches ICP | +10 | | Industry in target list | +10 | | Geography in target regions | +5 | | Revenue in target range | +5 | | Company size too small | -10 | | Industry excluded | -20 |

**Contact Demographics:** | Criteria | Points | |----------|--------| | Title is decision maker | +10 | | Title is influencer | +5 | | Title is end user | +3 | | Student/Personal email | -15 | | Competitor domain | -40 |

Step 2: Define Behavior Score (0-40 points)

**Content Engagement:** | Action | Points | |--------|--------| | Pricing page visit | +15 | | Case study download | +10 | | Product demo video watched | +10 | | Blog post read | +2 | | 5+ pages in session | +5 | | Return visit within 7 days | +5 |

**Direct Engagement:** | Action | Points | |--------|--------| | Demo request form | +30 | | Contact sales form | +25 | | Free trial signup | +20 | | Webinar registration | +10 | | Newsletter signup | +3 | | Email opened | +1 | | Email clicked | +3 |

Step 3: Define Intent Score (0-20 points)

**Third-Party Intent:** | Signal | Points | |--------|--------| | Researching your category (Bombora/G2) | +15 | | Competitor comparison searches | +10 | | Job posting for related role | +5 | | Funding announcement | +5 | | Technology install matches | +5 |

Step 4: Apply Negative Scoring

| Signal | Points | |--------|--------| | Unsubscribed from email | -10 | | Bounced email | -20 | | No engagement 90+ days | -15 | | Marked as spam | -30 | | Competitor | -100 |

Step 5: Set Thresholds

| Score Range | Qualification | Action | |-------------|---------------|--------| | 80-100 | Hot MQL | Immediate sales call | | 60-79 | Warm MQL | SDR outreach 24hr | | 40-59 | Marketing Qualified | Nurture sequence | | 20-39 | Early Stage | Educational content | | 0-19 | Not Qualified | Monitor only | | Negative | Disqualified | Suppress |

Examples

Example 1: Scoring Model Design

**Input:**

Help me create a lead scoring model for B2B SaaS (marketing automation).

Our ICP:
- Company size: 50-500 employees
- Industries: Tech, E-commerce, SaaS
- Titles: VP Marketing, Director Marketing, CMO
- Geography: US, Canada, UK

Key buying signals:
- Pricing page, demo request, case studies
- Marketing automation category on G2

**Output:**

## Lead Scoring Model: Marketing Automation SaaS

### Fit Score (Max 40 points)

**Company Fit (20 points)**
| Criteria | Points |
|----------|--------|
| 50-500 employees | +10 |
| 500-1000 employees | +5 |
| <50 or >1000 employees | +0 |
| Tech/E-commerce/SaaS industry | +10 |
| Adjacent industry (Retail, Media) | +5 |
| Non-target industry | +0 |

**Contact Fit (20 points)**
| Criteria | Points |
|----------|--------|
| VP/Director Marketing, CMO | +15 |
| Marketing Manager | +10 |
| Marketing Coordinator | +5 |
| Non-marketing title | +0 |
| US/Canada/UK | +5 |
| Other geography | +0 |
| Personal email (@gmail) | -15 |
| Competitor domain | -40 |

### Behavior Score (Max 40 points)

**High-Intent Actions**
| Action | Points |
|--------|--------|
| Demo request submitted | +25 |
| Pricing page visit | +15 |
| Case study download | +10 |
| Product tour completed | +10 |

**Engagement Actions**
| Action | Points |
|--------|--------|
| 3+ pages in session | +5 |
| Return visit (7 days) | +5 |
| Webinar registered | +8 |
| Blog post read | +2 |
| Email clicked | +3 |
| Email opened | +1 |

### Intent Score (Max 20 points)

| Signal | Points |
|--------|--------|
| G2 category research | +10 |
| Competitor comparison | +8 |
| Marketing hire posting | +5 |
| Series A/B funding | +5 |

### Negative Scoring

| Sign