Lead Pricing Complete Guide

Lead Pricing Complete Guide

Overview

LeadConduit provides a sophisticated, rules-based pricing system that handles both sides of lead transactions - what you pay sources (purchase pricing) and what buyers pay you (sale pricing). This guide covers every aspect of the pricing system.

What You'll Learn

Understanding the Pricing Model

Pricing Hierarchy

Pricing Structure:
  └── Flow Level (Default)
      ├── Source Level (Override)
      │   ├── Rule-Based Pricing
      │   └── Source-Submitted Pricing
      └── Delivery Level
          ├── Rule-Based Pricing
          └── Buyer-Provided Pricing

Key Concepts

Purchase Pricing Configuration

Flow-Level Pricing

Set default pricing for all sources:

1. Navigate to Flow → Sources tab
2. Click Flow Purchase Price
3. Configure base pricing:

Flow Purchase Price:
  Default Price: $5.00
  Currency: USD
  Apply To: All sources without specific pricing

Source-Level Pricing

Override flow defaults for specific sources:

Source Configuration:
  Name: Premium Partner
  Pricing Type: Custom
  Base Price: $8.00
  Override Flow Default: Yes

Rule-Based Purchase Pricing

Create dynamic pricing based on lead attributes:

// Example: Tiered pricing by lead quality
{
  "pricing_rules": [
    {
      "name": "High Quality Leads",
      "conditions": {
        "lead_score": { "operator": ">=", "value": 80 },
        "verified_phone": true
      },
      "price": 12.00
    },
    {
      "name": "Medium Quality Leads",
      "conditions": {
        "lead_score": { "operator": "between", "min": 50, "max": 79 }
      },
      "price": 8.00
    },
    {
      "name": "Base Quality Leads",
      "conditions": {
        "default": true
      },
      "price": 5.00
    }
  ]
}

Source-Submitted Pricing

Accept pricing from the source:

Source Pricing Configuration:
  Accept Source Price: Yes
  Price Field Name: price
  Validation:
    Minimum: $1.00
    Maximum: $50.00
  Fallback: Use flow default if invalid

Sale Pricing Configuration

Delivery Step Pricing

Configure what buyers pay:

1. Open delivery step configuration
2. Navigate to Pricing section
3. Set up sale pricing:

Sale Price Configuration:
  Base Price: $15.00
  Pricing Method: Rule-based
  Margin Target: 50%

Dynamic Sale Pricing Rules

Implement sophisticated pricing logic:

// Complex sale pricing example
{
  "sale_pricing": {
    "rules": [
      {
        "name": "Exclusive Leads",
        "conditions": {
          "exclusive": true,
          "deliveries_count": 0
        },
        "price": 25.00
      },
      {
        "name": "Semi-Exclusive",
        "conditions": {
          "deliveries_count": { "operator": "<", "value": 3 }
        },
        "price": 18.00
      },
      {
        "name": "Geographic Premium",
        "conditions": {
          "state": { "operator": "in", "value": ["CA", "NY", "TX"] }
        },
        "price": 20.00
      },
      {
        "name": "Time-Based Pricing",
        "conditions": {
          "age_minutes": { "operator": "<", "value": 5 }
        },
        "price": 22.00
      }
    ],
    "default_price": 15.00
  }
}

Buyer-Provided Pricing

Accept pricing from buyer responses:

// Buyer response with pricing
{
  "response": {
    "accepted": true,
    "price": 18.50,
    "lead_id": "abc123"
  }
}

// Configuration to accept buyer pricing
{
  "accept_buyer_price": true,
  "price_field": "price",
  "validate_price": {
    "min": 10.00,
    "max": 50.00
  }
}

Advanced Pricing Strategies

Strategy 1: Margin-Based Pricing

Maintain consistent profit margins:

// Automatic margin calculation
{
  "margin_pricing": {
    "enabled": true,
    "target_margin_percent": 40,
    "calculation": "sale_price = purchase_price * (1 + margin)",
    "constraints": {
      "min_sale_price": 10.00,
      "max_sale_price": 100.00
    }
  }
}

Strategy 2: Volume-Based Pricing

Reward high-volume partners:

// Volume tiers
{
  "volume_pricing": {
    "period": "monthly",
    "tiers": [
      {
        "min_volume": 0,
        "max_volume": 1000,
        "purchase_price": 5.00,
        "sale_price": 12.00
      },
      {
        "min_volume": 1001,
        "max_volume": 5000,
        "purchase_price": 6.00,
        "sale_price": 13.00
      },
      {
        "min_volume": 5001,
        "max_volume": null,
        "purchase_price": 7.00,
        "sale_price": 14.00
      }
    ]
  }
}

Strategy 3: Performance-Based Pricing

Price based on quality metrics:

// Performance pricing
{
  "performance_pricing": {
    "metric": "conversion_rate",
    "lookback_days": 30,
    "tiers": [
      {
        "min_rate": 0,
        "max_rate": 0.05,
        "price_multiplier": 0.8
      },
      {
        "min_rate": 0.05,
        "max_rate": 0.10,
        "price_multiplier": 1.0
      },
      {
        "min_rate": 0.10,
        "max_rate": 1.0,
        "price_multiplier": 1.2
      }
    ]
  }
}

Nested Pricing Rules

Create complex pricing logic with nested conditions:

// Sophisticated nested pricing
{
  "pricing_rules": [
    {
      "name": "Premium California Leads",
      "conditions": {
        "AND": [
          { "field": "state", "equals": "CA" },
          {
            "OR": [
              { "field": "income", "greater_than": 100000 },
              { "field": "home_value", "greater_than": 500000 }
            ]
          }
        ]
      },
      "purchase_price": 15.00,
      "sale_price": 35.00
    },
    {
      "name": "Business Hours Premium",
      "conditions": {
        "AND": [
          { "field": "business_hours", "equals": true },
          { "field": "lead_type", "equals": "live_transfer" }
        ]
      },
      "price_adjustment": {
        "type": "percentage",
        "value": 20
      }
    }
  ]
}

Pricing Fields and Variables

Available Pricing Variables

Use these fields in pricing rules:

Pricing Reports and Analytics

Default Pricing Reports

LeadConduit provides built-in pricing reports:

Stats Report by Source and Purchase Price:
  Columns:
    - Source Name
    - Lead Count
    - Total Cost
    - Average Price
    - Acceptance Rate
  Grouping: By Source, By Price
  Period: Customizable

Custom Pricing Analytics

Build advanced pricing reports:

-- Margin Analysis Report
SELECT 
  DATE(created_at) as date,
  source_name,
  buyer_name,
  COUNT(*) as lead_count,
  AVG(purchase_price) as avg_cost,
  AVG(sale_price) as avg_revenue,
  AVG(sale_price - purchase_price) as avg_margin,
  (AVG(sale_price - purchase_price) / AVG(purchase_price) * 100) as margin_percent
FROM leads
WHERE 
  delivery_outcome = 'success'
  AND created_at >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY date, source_name, buyer_name
ORDER BY date DESC, margin_percent DESC;

Key Pricing Metrics

Monitor these essential metrics:

Formula: SUM(purchase_price) / COUNT(leads)
Target: Market competitive
Trend: Monitor monthly

Formula: SUM(sale_price) / COUNT(sold_leads)
Target: > Purchase + overhead
Trend: Increase over time

Formula: (Sale - Purchase) / Sale * 100
Target: > 30%
Alert: < 20%

Formula: STDDEV(price) / AVG(price)
Target: < 25%
Review: High variance sources

Troubleshooting Pricing Issues

Common Problems and Solutions

Best Practices

1. Pricing Strategy

Strategic Guidelines:
  - Start with simple rules, add complexity gradually
  - Monitor margins daily
  - A/B test pricing changes
  - Document all pricing logic
  - Regular competitive analysis

2. Rule Organization

Rule Structure:
  - Order rules from most to least specific
  - Use clear, descriptive names
  - Group related conditions
  - Always include a default/fallback price
  - Test edge cases

3. Margin Protection

Margin Safety:
  - Set minimum acceptable margins
  - Alert on margin erosion
  - Review unprofitable sources
  - Negotiate better rates
  - Optimize delivery costs

Integration with Billing

How Pricing Affects Billing

Billing Integration:
  Purchase Prices → Accounts Payable
  Sale Prices → Accounts Receivable
  Net Margin → Gross Profit
  Volume × Price → Revenue

Reconciliation Process

Ensure accurate billing:

1. Daily Reconciliation

   • Match delivered leads to invoices
   • Verify pricing applied correctly
   • Flag discrepancies

2. Monthly Close

   • Generate source payment reports
   • Create buyer invoices
   • Calculate net revenue

3. Audit Trail

   • Track all price changes
   • Document rule modifications
   • Maintain pricing history

Advanced Pricing Scenarios

Scenario 1: Ping/Post Pricing

Different prices for ping vs. post:

{
  "ping_post_pricing": {
    "ping": {
      "price": 0.10,
      "conditions": ["initial_interest"]
    },
    "post": {
      "price": 15.00,
      "conditions": ["ping_accepted", "full_data_provided"]
    }
  }
}

Scenario 2: Exclusive vs. Shared

Premium for exclusive leads:

{
  "exclusivity_pricing": {
    "exclusive": {
      "multiplier": 2.5,
      "max_deliveries": 1
    },
    "semi_exclusive": {
      "multiplier": 1.5,
      "max_deliveries": 3
    },
    "shared": {
      "multiplier": 1.0,
      "max_deliveries": null
    }
  }
}

Scenario 3: Real-Time Bidding

Dynamic auction-based pricing:

{
  "rtb_pricing": {
    "auction_type": "second_price",
    "reserve_price": 5.00,
    "bid_timeout": 100,  // milliseconds
    "accept_highest": true
  }
}

Pricing Optimization

A/B Testing Prices

Test pricing strategies:

Price Test Configuration:
  Test Name: Q4 Pricing Optimization
  Variants:
    A: Current pricing (control)
    B: 10% increase
    C: Volume discounts
  Split: 33/33/34
  Duration: 2 weeks
  Success Metric: Total margin

Price Elasticity Analysis

Understand price sensitivity:

-- Price elasticity calculation
WITH price_changes AS (
  SELECT 
    source_name,
    DATE(changed_at) as change_date,
    old_price,
    new_price,
    (new_price - old_price) / old_price * 100 as price_change_percent
  FROM pricing_history
),
volume_changes AS (
  SELECT 
    source_name,
    DATE(created_at) as date,
    COUNT(*) as daily_volume
  FROM leads
  GROUP BY source_name, date
)
SELECT 
  pc.source_name,
  pc.price_change_percent,
  AVG(vc_before.daily_volume) as volume_before,
  AVG(vc_after.daily_volume) as volume_after,
  (AVG(vc_after.daily_volume) - AVG(vc_before.daily_volume)) / AVG(vc_before.daily_volume) * 100 as volume_change_percent
FROM price_changes pc
JOIN volume_changes vc_before ON 
  vc_before.source_name = pc.source_name 
  AND vc_before.date < pc.change_date
  AND vc_before.date >= pc.change_date - INTERVAL '7 days'
JOIN volume_changes vc_after ON 
  vc_after.source_name = pc.source_name 
  AND vc_after.date > pc.change_date
  AND vc_after.date <= pc.change_date + INTERVAL '7 days'
GROUP BY pc.source_name, pc.price_change_percent;

Next Steps

Additional Resources

• Pricing Calculator Tool
• Margin Analysis Template
• Video: Advanced Pricing Strategies
• Community Forum: Pricing Discussion