Lead Qualification Agent

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Overview

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What the Agent Needs to Accomplish

• Score leads based on multiple criteria
• Route leads to appropriate sales reps
• Prioritize high-value prospects
• Track lead conversion rates
• Identify lead quality trends
• Optimize routing rules

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How Pylar Helps

• Unified Lead View: Combining lead data, firmographics, and behavioral signals
• Real-time Scoring: Querying current lead data for instant scoring
• Multi-Source Integration: Joining lead data with CRM and marketing data
• Pattern Recognition: Identifying high-converting lead patterns
• Automated Routing: Intelligent lead distribution

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Without Pylar vs With Pylar

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Without Pylar

• ❌ Manual lead scoring
• ❌ Complex routing logic across systems
• ❌ Limited lead data integration
• ❌ Time-consuming qualification
• ❌ Inconsistent scoring

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With Pylar

• ✅ Automated lead scoring
• ✅ Real-time routing
• ✅ Unified lead data
• ✅ Pattern-based optimization

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Step-by-Step Implementation

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Step 1: Connect Data Sources

1. Connect Marketing Platform (Lead data, behavioral signals)
2. Connect CRM (Lead conversion, historical data)
3. Connect Firmographic Data (Company data, industry)

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Step 2: Create Lead Scoring Views

CREATE VIEW lead_scoring AS
SELECT 
  l.lead_id,
  l.email,
  l.company_name,
  l.industry,
  l.company_size,
  -- Behavioral signals
  l.page_views,
  l.download_count,
  l.webinar_attended,
  -- Firmographic score
  CASE 
    WHEN l.company_size >= 1000 THEN 30
    WHEN l.company_size >= 500 THEN 20
    WHEN l.company_size >= 100 THEN 10
    ELSE 5
  END as firmographic_score,
  -- Behavioral score
  (l.page_views * 2 + l.download_count * 5 + 
   CASE WHEN l.webinar_attended THEN 10 ELSE 0 END) as behavioral_score,
  -- Total score
  (CASE WHEN l.company_size >= 1000 THEN 30 ELSE 0 END +
   CASE WHEN l.company_size >= 500 THEN 20 ELSE 0 END +
   l.page_views * 2 + l.download_count * 5 +
   CASE WHEN l.webinar_attended THEN 10 ELSE 0 END) as total_score
FROM marketing.leads l;

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Step 3: Create MCP Tools

• score_lead(lead_id: string)

• route_lead(lead_id: string, territory: string)

• get_high_value_leads(min_score: number, limit: number)

• analyze_lead_quality(days_back: number, source: string)

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Example Agent Interactions

• Company: TechCorp (500 employees)
• Activity: 15 page views, 2 downloads
• Routed to: Sarah Johnson (Enterprise team)
• Recommended: Immediate outreach”

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Outcomes

• Qualification Speed: 80% faster
• Conversion Rate: 25% improvement
• Routing Accuracy: 40% better match
• Sales Efficiency: 2x more qualified leads per rep

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Next Steps

• Sales Assistant Example
• Marketing Campaign Optimizer Example