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

--search

--limit

--location

--sheet-url

--sheet-name

--workers

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

/staff

/people

/meet-the-team

/leadership

/management

/founders

/who-we-are

/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)