CMO · Calculator · Intermediate · Saves 40+ hours
Lead Scoring Model Builder
A complete system for building, validating, and maintaining a lead scoring model that actually predicts conversion. Based on scoring models that achieved 3x+ improvement in MQL-to-SQL conversion.
What's included
- Scoring Model Template
- Demographic scoring criteria
- Firmographic scoring criteria
- Behavioral scoring criteria
- Engagement scoring criteria
- Negative scoring factors
- Weighting Calculator
- Data-driven weight determination
- Conversion correlation analysis
- Score threshold optimization
- Validation Framework
- Model accuracy testing methodology
- A/B testing approach
- Continuous calibration process
- Implementation Guide
- HubSpot implementation instructions
- Salesforce implementation instructions
- Marketo implementation instructions
- Custom platform guidance
Best used when
- Building initial lead scoring
- Fixing broken lead scoring
- Improving MQL-to-SQL conversion
- Sales-marketing alignment initiatives
- Marketing automation optimization
Why this is Gold
Most lead scoring models are based on guesses. This framework uses your actual conversion data to set weights, includes validation methodology, and provides platform-specific implementation guides.
The template
PART 1: SCORING CRITERIA DESIGN
Demographic Scoring (Who They Are)
| Criterion | Value | Points | Negative Points |
|---|---|---|---|
| Job Title | |||
| C-Level/VP | Exact match | +20 | |
| Director | Close match | +15 | |
| Manager | Acceptable | +10 | |
| Individual Contributor | +5 | ||
| Student/Intern | -20 | ||
| Department | |||
| Primary buyer | Exact match | +15 | |
| Influencer | Adjacent | +10 | |
| Non-buyer | -10 |
Firmographic Scoring (Company Fit)
| Criterion | Ideal | Points | Negative Points |
|---|---|---|---|
| Company Size | |||
| Enterprise (1000+) | If target | +20 | |
| Mid-market (200-999) | If target | +15 | |
| SMB (50-199) | If target | +10 | |
| Too small (<50) | If not target | -15 | |
| Industry | |||
| Primary verticals | Exact match | +15 | |
| Secondary verticals | Good fit | +10 | |
| Non-target | Poor fit | -15 | |
| Revenue | |||
| Ideal range | In range | +15 | |
| Acceptable | Adjacent | +5 | |
| Outside target | -10 |
Behavioral Scoring (What They Do)
| Behavior | Points | Decay | Notes |
|---|---|---|---|
| High Intent | |||
| Demo request | +50 | None | MQL trigger |
| Pricing page view | +30 | 30 days | |
| Contact sales | +40 | None | MQL trigger |
| Medium Intent | |||
| Case study download | +15 | 60 days | |
| Product page visit (3+) | +20 | 30 days | |
| Webinar attendance | +20 | 60 days | |
| Low Intent | |||
| Blog visit | +2 | 90 days | |
| Email open | +1 | 30 days | |
| Email click | +5 | 30 days | |
| Social engagement | +3 | 30 days | |
| Negative Signals | |||
| Unsubscribed | -30 | None | |
| Bounced email | -20 | None | |
| 90 days no activity | -25 | Score decay |
PART 2: SCORE THRESHOLDS
MQL Threshold Calculation
| Minimum Threshold | Maximum Threshold | Lead Stage |
|---|---|---|
| 0-29 | Cold lead | |
| 30-59 | Warm lead | |
| 60-89 | Hot lead | |
| 90+ | MQL |
MQL Threshold: 90 points (adjust based on conversion data)
Score Categories
| Score Range | Behavior | Routing |
|---|---|---|
| 90+ | MQL - Ready for sales | SDR immediate |
| 60-89 | Accelerate nurture | Fast-track programs |
| 30-59 | Standard nurture | Regular cadence |
| 0-29 | Early stage | Awareness content |
| Negative | Review/remove | Data hygiene |
PART 3: IMPLEMENTATION CHECKLIST
HubSpot Implementation
- Create demographic score property
- Create behavioral score property
- Create total score (calculated)
- Build workflow for MQL notification
- Set up score property reporting
Salesforce Implementation
- Create lead score fields
- Build Process Builder/Flow for scoring
- Create MQL assignment rules
- Configure reporting dashboards
Marketo Implementation
- Create scoring program
- Build smart campaigns for behaviors
- Set demographic scoring
- Configure MQL sync to SFDC
PART 4: VALIDATION FRAMEWORK
Monthly Calibration
| Metric | Target | Actual | Action |
|---|---|---|---|
| MQL-to-SQL rate | >30% | Adjust if <25% | |
| SQL-to-Opp rate | >40% | Adjust criteria | |
| Avg score of closed-won | Benchmark | ||
| Avg score of closed-lost | Comparison |
Feedback Loop Questions
Ask Sales Weekly:
- Are MQLs the right quality?
- What's missing from scoring criteria?
- What leads should have been MQLs but weren't?
Frequently asked questions
What is the Lead Scoring Model Builder?
A complete system for building, validating, and maintaining a lead scoring model that actually predicts conversion. Based on scoring models that achieved 3x+ improvement in MQL-to-SQL conversion.
Who is the Lead Scoring Model Builder for?
It is built for CMOs and their teams working on Demand Generation. The AI coach adapts it to your company, stage, and goals.
What's included in the Lead Scoring Model Builder?
4 working sections: PART 1: SCORING CRITERIA DESIGN; PART 2: SCORE THRESHOLDS; PART 3: IMPLEMENTATION CHECKLIST; PART 4: VALIDATION FRAMEWORK.
How long does the Lead Scoring Model Builder take to use?
It saves roughly 40+ hours versus building from scratch. Our AI coach can tailor the calculator to your situation in minutes, then hand you a step-by-step plan.
Is the Lead Scoring Model Builder free?
Yes. You can read the full calculator and start getting coached through it for free. Sign in to save your tailored version and track your next steps.
How does the AI coach help with the Lead Scoring Model Builder?
The coach teaches you the framework, asks a few questions about your business, tailors the calculator to you, and gives you measurable next steps to execute.