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    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## Google Maps Extractor\n\nA web scraping Actor that extracts structured place-level data from Google Maps search results for location intelligence, lead generation, and local market analysis. It performs keyword, category, URL, or location-based searches (city, postal area, coordinates, polygons/circles), navigates Google Maps search pages and splits large regions into subregions to collect comprehensive place records. The Actor outputs structured place metadata including place name, address and neighborhood, geocoordinates, place identifier, website and phone contacts, ratings and review counts, opening hours, price information, category and tag data, photos count and image metadata, accessibility and promotional status, and additional place attributes. Optional enrichment modules add company contact extraction from business websites (including legal Impressum scraping for German/Austrian/Swiss sites), business lead discovery with names, job titles and professional profiles, email verification for discovered addresses, and social media profile enrichment with follower counts, descriptions, and verification status.\n\n## Use cases\n\n- Scrape Google Maps places by keyword, category, or direct Google Maps URL for targeted place discovery (e.g., restaurants, bars, parking lots)\n- Extract places within a city, postal code, country, or custom polygon/circle coordinates for geographic or market coverage analysis\n- Build enriched contact lists by scraping company websites for emails, phones, and social links\n- Generate employee and company leads with professional profiles, job titles, and LinkedIn links for sales and recruitment outreach\n- Verify discovered emails to improve lead quality and deliverability assessment\n- Enrich place results with social media profile metrics (followers, descriptions, verification) for social audience analysis\n- Compile structured datasets for mapping, location intelligence, competitive analysis, and local market research",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCTLaSIyNsX2oEO5MpgoOKvf7Wh2r62JCq+0aA5a+CdTqYS3wTtGfNKNgv1PtaEknN52mit+HTATRcuV65az6COzj32vd6P6bNdOzh3GVxMG69qq1lLybMZ8cxHMFatHAUy0OGnaOSvKrOKpGYuiNPQO02SOP115FYdo4aSMrJmjHxt1+aIzEKzqrgIEi65C0HoyGX+X9ucGEyd0qmn1REl1gBLk3E+lUjEh8cTaY0ee+8ayk/++2iNmyetDcWvyS2D1tuNPbjYu7NM/+mQPvZUYCi4W0ugMwpfnSoFdR+HFILnrLG2PvRo/R3Ef2J5jCYvxKdc9D0a1l5Fc8HRCn4L \n"
  }
}