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Google serp lead scraper

Skill Harmeet10000/skills/skills/marketing/google-serp-lead-scraper

Collection of my Agent Skills and books.

Install
npx -y skills add Harmeet10000/skills --skill google-serp-lead-scraper

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

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Google SERP Lead Scraper

Scrapes Google search results for local businesses, fetches their websites, extracts contact information using GPT-5, and stores structured leads in Google Sheets.

When to Use

  • Building lead lists for local service businesses (plumbers, electricians, roofers, etc.)
  • Prospecting for outreach campaigns targeting specific geographic areas
  • Populating CRM with enriched contact data

How to Call

Webhook URL (test mode):

GET https://nicksaraev.app.n8n.cloud/webhook-test/8aee83a4-ae72-4f96-a834-e1c6afd4d080

Production URL: TBD (deploy workflow to get production webhook)

No parameters required currently—query is hardcoded to "calgary plumber".

What It Does

  1. Google Search → Apify's google-search-scraper actor searches with:

    • Query: "calgary plumber" (hardcoded)
    • Country: Canada (ca)
    • Language: English
    • 5 pages × 10 results = up to 50 organic results
  2. Limit → Currently capped at 2 results (for testing). Remove or adjust the Limit node for full runs.

  3. Fetch & Convert → Each result URL is fetched and converted to markdown.

  4. GPT-5 Extraction → Extracts 100+ fields per lead including:

    • Company info (name, tagline, industry, keywords)
    • Owner/decision-maker details
    • Multiple emails with confidence scores and provenance
    • Phones normalized to E.164
    • Full address parsing
    • Social profiles (LinkedIn, Facebook, Instagram, Twitter, etc.)
    • Best contact method recommendation
    • Custom icebreaker line for outreach
  5. Google Sheets → Appends to Google SERP Scraping Database

Output Schema (Key Fields)

FieldDescription
company_nameBusiness name
owner_nameDecision-maker name (if found)
best_email_to_tryHighest-confidence email for outreach
best_phone_to_tryRecommended phone number
email_1, email_2, email_3All extracted emails
email_X_confidence0.0–1.0 confidence score
email_X_provenanceSource location (e.g., `/contact
phone_1_e164Phone in E.164 format
address_fullComplete address string
linkedin_company_urlCompany LinkedIn page
one_liner_for_icebreakerPre-formatted outreach opener

See the full 100+ field schema in the n8n workflow's GPT prompt.

Icebreaker Format

The extraction generates icebreakers in this format:

Hey {FirstName}. I work with a $2M/yr plumber out of Calgary (NE-specific),
pretty similar to {CompanyName}. Not sure if you have exposure to the NE,
but wanted to run something by you.

Confidence Scoring

Extraction uses tiered confidence based on source:

  • 1.0 — Schema.org structured data
  • 0.9 — OpenGraph/meta tags
  • 0.85 — /contact or /about pages
  • 0.8 — Footer/header blocks
  • 0.6 — Visible text near contact labels
  • 0.4 — Inferred/heuristic values

Fields below 0.6 confidence are flagged for manual review.

Current Limitations

  1. Hardcoded query — "calgary plumber" is baked into the workflow. To change:

    • Edit the Apify node's queries parameter in n8n
    • Or parameterize via webhook query string (requires workflow update)
  2. Test limit — Only processes 2 results. Remove the Limit node for production.

  3. No deduplication — Repeated runs may create duplicate rows. Consider adding a check against source_url or domain.

  4. Rate limits — Apify has usage limits; large batches may need pagination or scheduling.

Future Improvements

  • Accept query and location as webhook parameters
  • Add deduplication against existing sheet rows
  • Batch processing with progress tracking
  • Error handling for failed URL fetches
  • Deploy to production webhook URL

Related Files

  • Output: Google SERP Scraping Database
  • Workflow platform: n8n Cloud (nicksaraev.app.n8n.cloud)
  • Scraping service: Apify (google-search-scraper actor)

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