This workflow automates the process of scraping LinkedIn profiles, extracting relevant data, and generating personalized outreach messages. Starting with a schedule trigger or spreadsheet input, it fetches LinkedIn profile URLs or IDs from a Google Sheet, interacts with PhantomBuster to scrape LinkedIn data via API calls, and then processes this data using OpenAI’s GPT-4 models integrated through Azure. The GPT-4 models analyze profile data, extract key information, and generate personalized messages based on templates. These messages are then stored back into Google Sheets for use in outreach campaigns. The workflow is designed for sales teams, recruiters, or marketing professionals aiming to automate outreach by leveraging real-time data extraction and AI-driven personalization.
Automated LinkedIn Data Extraction & Personalised Outreach
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatAzureOpenAi, @n8n/n8n-nodes-langchain.outputParserStructured, googleSheets, httpRequest, scheduleTrigger, stickyNote, wait |
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