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)

Field	Description
company_name	Business name
owner_name	Decision-maker name (if found)
best_email_to_try	Highest-confidence email for outreach
best_phone_to_try	Recommended phone number
email_1, email_2, email_3	All extracted emails
email_X_confidence	0.0–1.0 confidence score
email_X_provenance	Source location (e.g., `/contact
phone_1_e164	Phone in E.164 format
address_full	Complete address string
linkedin_company_url	Company LinkedIn page
one_liner_for_icebreaker	Pre-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)