Lead Intelligence Skill

Use this skill to perform deep lead qualification, property research, and predictive analysis for Jorge Salas' real estate business.

Core Capabilities

1. Public Records Research: Use get_public_records to fetch property details.
2. Predictive Analytics: Use detect_life_event_triggers and predict_propensity_to_sell to identify high-intent leads.
3. Lead Scoring Framework: Apply the 28-feature pipeline logic to categorize leads.

Lead Scoring Guidelines (28-Feature Pipeline)

When analyzing a lead, evaluate these core factors:

1. Budget Qualification (25%)

• Stated budget vs. market reality.
• Pre-approval status.
• Down payment availability.

2. Timeline Urgency (20%)

• Stated timeline to purchase/sell.
• Current housing situation.
• Market timing awareness.

3. Engagement Level (20%)

• Response rate to communications.
• Website interaction patterns (if available via CRM).
• Property viewing requests.

4. Geographic Focus (15%)

• Preferred area specificity.
• Realistic area expectations.

5. Behavioral Indicators (20%)

• Communication style and tone.
• Question quality and specificity.

Scoring Grades

• A-Grade (9-10): Hot leads ready to transact.
• B-Grade (7-8): Warm leads needing nurturing.
• C-Grade (5-6): Qualified prospects with longer timeline.
• D-Grade (3-4): Requires significant qualification.
• F-Grade (1-2): Not qualified or likely unviable.

Workflow Integration

• Use the enterprise-hub MCP tools to fetch live data.
• Store results in the PostgreSQL database for long-term tracking.
• Update the active-session.md when a significant lead milestone is reached.