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Google Maps to Airtable lead scraper with GPT contact extraction from impressum

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2/3/2026
Vision AIWebhook TriggerImage AnalysisPDF ProcessingGoogle Gemini
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How it Works

This workflow automates the process of discovering companies in different cities, extracting their contact data, and storing it in Airtable.

  1. City Loop (Airtable → Google Maps API)

    • Reads a list of cities from Airtable.
    • Uses each city combined with a search term (e.g., SEO Agency, Berlin) to query Google Maps.
    • Marks processed cities as “checked” to allow safe restarts if interrupted.

  2. Business Discovery & Deduplication

    • Searches for businesses via Google Maps Text Search.
    • Checks Airtable to avoid scraping the same company multiple times.
    • Fetches detailed info for each business via Google Maps Place Details API.

  3. Impressum Extraction (Website → HTML Parsing)

    • Builds an Impressum page URL for each business.
    • Requests the HTML and cleans out ads, headers, footers, etc.
    • Extracts relevant contact info using an AI extractor (OpenAI node).

  4. Contact Information Extraction

    • Pulls out:
      • Decision Maker (Name + Position in one string, if available).
      • Email address (must be valid, containing @).
      • Phone number (international format if possible).
    • Filters out incomplete results (e.g., empty email).

  5. Database Storage

    • Writes company data back into Airtable:
      • Company name
      • Address
      • Website
      • Email
      • Phone number
      • Decision Maker (Name + Position)
      • Search term & city used

Setup Steps

1. Prerequisites

  • Google Maps API Key with access to:
    • Places API → Text Search + Place Details
  • Airtable base with at least two tables:
    • Cities (with columns: ID, City, Country, Status)
    • Companies (for scraped results)
  • OpenAI API key (for decision maker + contact extraction).

2. Authentication

  • Configure your Airtable API credentials in n8n.
  • Set up HTTP Query Auth with your Google Maps API key.
  • Add your OpenAI API key in the OpenAI Chat node.

3. Configuration

  • In the Airtable “Cities” table, list all cities you want to scrape.
  • Define your search term in the “Execute Workflow” node (e.g., SEO Agency).
  • Adjust the batch sizes and wait intervals if you want faster/slower scraping (Google API has strict rate limits).

4. Execution

  • Start manually or from another workflow.
  • The workflow will scrape all companies in each city step by step.
  • It can be safely stopped and resumed — cities already marked as processed will be skipped.

5. Results

  • Enriched company dataset stored in Airtable, ready for CRM import, lead generation, or further automation.

Tips & Notes

  • Always respect GDPR and local laws when handling scraped data.
  • The workflow is modular → you can swap Airtable with Google Sheets, Notion, or a database of your choice.
  • Add custom filters to limit results (e.g., only companies with websites).
  • Use sticky notes inside the workflow to understand each step (mandatory for template publishing).
  • Keep an eye on Google Places API costs — queries are billed after the free quota. If you are still within the first 2 months of the Google Cloud Developer free trial, you can benefit from free credits.

**

Google Maps to Airtable Lead Scraper with GPT Contact Extraction

This n8n workflow automates the process of scraping business information from Google Maps search results, extracting contact details from company impressum pages using AI, and then storing this enriched data in Airtable. It's designed to streamline lead generation and data collection for sales, marketing, or research purposes.

What it does

  1. Triggers Manually: The workflow starts when manually executed.
  2. Scrapes Google Maps: It initiates a sub-workflow to scrape business listings from Google Maps based on a predefined search query.
  3. Processes Scraped Data: Each scraped item is then processed individually.
  4. Extracts Website from HTML: It extracts the company's website URL from the scraped HTML content.
  5. Filters for Valid Websites: It checks if a valid website URL was successfully extracted.
  6. Fetches Impressum: For businesses with a valid website, it attempts to fetch the "impressum" (legal notice) page.
  7. Extracts Contact Info with AI: It uses an OpenAI Chat Model to extract contact person, email, and phone number from the impressum content.
  8. Formats Data: The extracted information is then formatted into a structured JSON object.
  9. Stores in Airtable: Finally, the enriched lead data (including company name, address, website, and extracted contact details) is added as a new record to a specified Airtable base.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance.
  • Airtable Account: With a base and table configured to store lead data. You'll need an Airtable API Key and Base ID.
  • OpenAI API Key: For the OpenAI Chat Model to extract contact information.
  • Google Maps Scraper Sub-workflow: This workflow relies on a separate sub-workflow (likely named "Google Maps Scraper") to perform the initial scraping. You will need to ensure this sub-workflow is also imported and correctly configured.
  • HTTP Request Node: For fetching website content.

Setup/Usage

  1. Import the Workflow: Import this JSON workflow into your n8n instance.
  2. Configure Credentials:
    • Airtable: Set up your Airtable credentials (API Key) and configure the "Airtable" node with your Base ID and Table Name.
    • OpenAI: Set up your OpenAI credentials (API Key) for the "OpenAI Chat Model" node.
  3. Configure Sub-workflow:
    • The "Execute Workflow" node (ID: 111) is configured to call a sub-workflow. You will need to replace [YOUR_GOOGLE_MAPS_SCRAPER_WORKFLOW_ID] with the actual ID of your Google Maps scraper sub-workflow.
    • Ensure your Google Maps scraper sub-workflow outputs the necessary data (e.g., business name, address, website URL or HTML containing it).
  4. Customize Search Query: In the Google Maps scraper sub-workflow, configure the search query to target your desired leads (e.g., "restaurants in Berlin", "software companies in London").
  5. Customize AI Prompt: Review and adjust the prompt in the "OpenAI Chat Model" node (ID: 1153) to optimize contact information extraction for your specific needs.
  6. Execute: Once configured, you can manually execute the "When clicking ‘Execute workflow’" trigger to start the lead generation process.

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