Gmaps Lead Generation

Google Maps Lead Generation

Generate high-quality B2B leads from Google Maps with deep contact enrichment.

Overview

This pipeline scrapes Google Maps for businesses, then enriches each result by:

1. Scraping their website (main page + up to 5 contact pages)
2. Searching DuckDuckGo for additional contact info
3. Using Claude to extract structured contact data from all sources

Tested at scale: 50+ leads per run, 68 total leads across plumbers, electricians, HVAC, and roofing contractors.

When to Use

• Building outbound sales lists for local service businesses
• Generating leads for B2B services (contractors, medical, legal, etc.)
• Researching businesses in a specific geographic area
• Creating prospecting lists with verified contact info

Inputs

Execution

# Basic usage - creates new sheet
python3 execution/gmaps_lead_pipeline.py --search "plumbers in Austin TX" --limit 10

# Append to existing sheet (recommended for building lead database)
python3 execution/gmaps_lead_pipeline.py --search "dentists in Miami FL" --limit 25 \
  --sheet-url "https://docs.google.com/spreadsheets/d/..."

# Higher volume run
python3 execution/gmaps_lead_pipeline.py --search "roofing contractors in Austin TX" \
  --limit 50 --workers 5

Output Schema (36 fields)

Business Basics (from Google Maps)

• business_name, category, address, city, state, zip_code, country
• phone, website, google_maps_url, place_id
• rating, review_count, price_level

Extracted Contacts (from website + web search + Claude)

• emails - All email addresses found (comma-separated)
• additional_phones - Phone numbers from website
• business_hours - Operating hours

Social Media

• facebook, twitter, linkedin, instagram, youtube, tiktok

Owner/Key Person Info

• owner_name, owner_title, owner_email, owner_phone, owner_linkedin

Team Contacts

• team_contacts - JSON array of team members with name, title, email, phone, linkedin

Metadata

• lead_id - Unique identifier (MD5 hash of name|address, for deduplication)
• scraped_at - ISO timestamp
• search_query - Original search term used
• pages_scraped - Number of pages fetched (1 main + up to 5 contact pages)
• search_enriched - Whether DuckDuckGo search was used (yes/no)
• enrichment_status - success/partial/error

Pipeline Steps

1. Google Maps Scrape - Apify compass/crawler-google-places actor returns business listings with basic info
2. Website Scraping - Fetches main page + up to 5 prioritized contact pages (/contact, /about, /team, etc.)
3. Web Search Enrichment - DuckDuckGo search for "{business}" owner email contact + scrapes first relevant result
4. Claude Extraction - Claude 3.5 Haiku extracts structured contacts from all gathered content
5. Google Sheet Sync - Appends new leads, automatically deduplicates by lead_id

Contact Page Patterns (22 total, priority-ordered)

High priority: /contact, /about, /team, /contact-us, /about-us, /our-team Medium: /staff, /people, /meet-the-team, /leadership, /management, /founders, /who-we-are Lower: /company, /meet-us, /our-story, /the-team, /employees, /directory, /locations, /offices

Cost Considerations

For 100 leads: ~$1.50-2.50 total

The pipeline maximizes value per Apify dollar by scraping 6+ pages + web search per business.

Dependencies

apify-client
httpx
html2text
anthropic
gspread
google-auth
google-auth-oauthlib
python-dotenv

Files

• execution/gmaps_lead_pipeline.py - Main orchestration script
• execution/scrape_google_maps.py - Google Maps scraper (standalone)
• execution/extract_website_contacts.py - Website contact extractor (standalone)

Troubleshooting

"No businesses found"

• Check search query is valid
• Include location in query (e.g., "plumbers in Austin, TX" not just "plumbers")

403 Forbidden errors

• ~10-15% of sites block scrapers with 403/503 errors
• These are handled gracefully and marked as errors in enrichment_status
• The lead is still saved with Google Maps data (phone, address, etc.)

"Could not fetch website"

• Some sites have broken DNS or are offline
• Marked as error in enrichment_status
• Reduce --workers if seeing many timeouts

"APIFY_API_TOKEN not found"

• Ensure .env file has valid Apify token
• Check token hasn't expired at apify.com

Google Sheet auth issues

• Delete token.json and re-authenticate
• Ensure credentials.json is valid OAuth client

Duplicate detection

• Pipeline uses lead_id (MD5 of name|address) to skip existing leads
• Running same search twice will show "No new leads to add (all duplicates)"

Learnings

• Google Maps actor returns website field directly - no need to scrape for it
• Contact pages commonly use /contact, /about, /team URL patterns
• Claude Haiku is sufficient for extraction and costs 10x less than Sonnet
• ~10-15% of business websites return 403/503 errors - this is normal
• Facebook URLs always fail with 400 errors (blocks scrapers)
• Some sites have broken DNS - handled gracefully as errors
• DuckDuckGo HTML search is free and doesn't block (unlike Google)
• stringify_value() helper needed because Claude sometimes returns dicts instead of strings
• Deduplication by lead_id prevents re-adding existing businesses across runs
• 50 leads takes ~3-4 minutes with 3 workers

Production Sheet

Active lead database: https://docs.google.com/spreadsheets/d/1ATrOiq3wfph8Or5BE8VCybgvqK5gh7hVPWiSlgb3QiU

Contains: plumbers, electricians, HVAC contractors, roofing contractors (Austin TX)