Nomad Customer Leads

Lead generation system for Nomad Internet - a multi-source scraping and qualification platform designed to identify high-converting leads in rural and remote markets.

Overview

This system implements a tiered lead generation approach:

1. Tier 1: High-Intent Harvesting - Reddit, Twitter real-time signals from people actively seeking help
2. Tier 2: Structured Data - Property sales, job changes, business listings
3. Tier 3: Monitoring - Continuous monitoring for new mentions and signals

Key Features

• Multi-source scraping: Reddit, Twitter/X, real estate platforms, county records
• Signal stacking: Combines signals from multiple sources to qualify leads
• Lead scoring: BANT-style scoring (Budget, Authority, Need, Timeline)
• Deduplication: Intelligent merging of leads found across platforms
• CLI interface: Easy-to-use commands for scraping and lead management

Installation

# Clone the repository
git clone https://github.com/itsablabla/Nomad-customer-leads.git
cd Nomad-customer-leads

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -e .

Configuration

Copy the example environment file and configure your API credentials:

cp .env.example .env

Edit .env with your settings:

# Database
DATABASE_URL=sqlite+aiosqlite:///./nomad_leads.db

# Reddit API (https://www.reddit.com/prefs/apps)
REDDIT_CLIENT_ID=your_client_id
REDDIT_CLIENT_SECRET=your_client_secret

# Twitter API (https://developer.twitter.com/)
TWITTER_BEARER_TOKEN=your_bearer_token

# Coverage Areas (comma-separated)
COVERAGE_ZIPS=80301,80302,80303
COVERAGE_COUNTIES=08013,08031

Usage

Initialize Database

nomad-leads init

Run Scraping

# Full scrape of all sources
nomad-leads scrape

# Tier 1 only (high-intent, fastest results)
nomad-leads scrape --tier 1

# Tier 2 only (structured data)
nomad-leads scrape --tier 2

# Specific source
nomad-leads scrape --source reddit

Monitor for New Leads

# Start continuous monitoring
nomad-leads monitor

# Monitor specific sources
nomad-leads monitor --sources reddit,twitter

View Hot Leads

# Show leads requiring immediate action
nomad-leads hot

Search and View Leads

# Search leads
nomad-leads search "colorado"
nomad-leads search "starlink" --min-score 60

# View lead details
nomad-leads show <lead-id>

Export Leads

# Export to JSON
nomad-leads export --output leads.json

# Export hot leads to CSV
nomad-leads export --tier hot --format csv --output hot_leads.csv

View Statistics

nomad-leads stats

Lead Scoring

Leads are scored 0-100 based on:

Category	Points	Examples
Budget	+20 each (max 60)	Property >$500K, Director+ title, expensive RV
Need	+20 each (max 60)	Active complaint, remote work dependency
Urgency	+30 each (max 60)	Post <48hrs, "ASAP" language, recent move
Authority	+15 each (max 30)	Property owner, business owner
Geographic	+10 each (max 20)	In coverage zone, no fiber competition

Signal Stacking Bonus

• 2 signals: +10 points
• 3 signals: +25 points
• 4+ signals: +40 points (whale alert!)

Lead Tiers

• Hot (81-100): Call immediately
• Priority (61-80): Outreach within 24 hours
• Standard (31-60): Standard follow-up sequence
• Nurture (0-30): Add to nurture campaign

Project Structure

nomad-customer-leads/
├── src/
│   ├── cli/           # Command-line interface
│   ├── database/      # SQLAlchemy models and repository
│   ├── enrichment/    # Signal stacking and lead processing
│   ├── models/        # Pydantic data models
│   ├── scrapers/      # Platform-specific scrapers
│   │   ├── reddit.py
│   │   ├── twitter.py
│   │   └── realestate.py
│   ├── scoring/       # Lead scoring engine
│   └── config.py      # Configuration management
├── main.py            # Entry point
├── requirements.txt
└── pyproject.toml

Scraper Details

Reddit Scraper

• Monitors 20+ subreddits (Starlink, rural_internet, RVLiving, etc.)
• Uses targeted search queries for high-intent posts
• Extracts: username, location hints, provider complaints, urgency signals

Twitter Scraper

• Real-time search for crisis signals
• Tracks competitor mentions and complaints
• Identifies remote workers with connectivity issues

Real Estate Scraper

• Template for property sale data integration
• Supports Zillow, county records, MLS data
• Identifies recent buyers in coverage areas

Best Practices

1. Start with Tier 1 - Focus on high-intent signals first
2. Layer signals - A lead with 3+ signals converts at 10x the rate
3. Act fast - Leads decay 50% per week after initial signal
4. Track sources - Monitor which sources produce conversions
5. Deduplicate - The same person appears on multiple platforms

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src/
ruff check src/

# Type checking
mypy src/

License

MIT License - See LICENSE file for details.