This n8n workflow automates the process of generating highly specific local search queries, scraping Google Maps for location-based data, extracting emails, and filtering URLs for targeted outreach. It begins with a manual trigger to initiate the process, then uses a language model (LLM) to create exhaustive search queries based on city neighborhoods and business types. The generated queries are structured and split into individual items for processing. The workflow visits each location on Google Maps via HTTP requests to scrape search results, filters URLs to exclude irrelevant content, and extracts emails from webpage data. It also identifies and filters out non-relevant URLs such as Google’s own links, then de-duplicates the data. This process is useful for local SEO, marketing campaigns, or outreach efforts where targeted, location-specific information is vital. Sticky notes guide users through the steps, highlighting the focus on generating search queries, scraping Google Maps, and collecting email data efficiently for outreach or research purposes.
Automated Local Search Query Generator and Web Scraper
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.outputParserStructured, code, filter, httpRequest, limit, manualTrigger, removeDuplicates, set, splitInBatches, splitOut, stickyNote, wait |
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