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Generate personalized cold email icebreakers from LinkedIn or website data with GPT-4

n8nn8n18 modulesv1.0
Google SheetsOpenAILinkedIn

Multi-Channel Cold Email Generator (LinkedIn + Website Fallback) Description This workflow automates the generation of hyper-personalized cold emails. It intelligently switches between two data sources: LinkedIn Activity and Company Website. If the lead has recent LinkedIn posts, the AI generates an icebreaker referencing their specific thoughts or news. If no posts are found, the workflow falls back to scraping their company website and generating an angle based on their business proposition. H

At a glance

Generate personalized cold email icebreakers from LinkedIn or website data with GPT-4 is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects Google Sheets, OpenAI, LinkedIn. It's free to download. Follow the 5-step import below to go live in minutes.

Platform
n8n
Connects
Google Sheets, OpenAI, LinkedIn
Modules
18
Price
Free
Version
v1.0
Generate personalized cold email icebreakers from LinkedIn or website data with GPT-4 workflow diagram

About this workflow

Multi-Channel Cold Email Generator (LinkedIn + Website Fallback) Description This workflow automates the generation of hyper-personalized cold emails. It intelligently switches between two data sources: LinkedIn Activity and Company Website. If the lead has recent LinkedIn posts, the AI generates an icebreaker referencing their specific thoughts or news. If no posts are found, the workflow falls back to scraping their company website and generating an angle based on their business proposition. How it Works 1. Fetch Data: Pulls a list of leads from a Google Sheet. 2. Scrape LinkedIn: Uses Apify to attempt to scrape recent posts for the lead. 3. Conditional Logic: - Path A (Posts Found): Aggregates the posts, analyzes the context using GPT-4, and writes an email referencing the content. - Path B (No Posts): Scrapes the URL provided in companyWebsite, converts the HTML to Markdown, analyzes the company value prop, and writes an email based on that. 4. Save Results: Writes the generated Icebreaker, Intro, and CompanyType back to the original Google Sheet. Requirements - n8n: Self-hosted or Cloud. - Google Sheets Account: A sheet containing columns for emailfinal, linkedinurl, and companyWebsite. - Apify Account: You must have the LinkedIn Scraper actor (ID: A3cAPGpwBEG8RJwse or similar) configured and an API Token. - OpenAI API Key: Access to GPT-4 model is recommended for best quality. Setup Instructions 1. Import the JSON: Copy the provided JSON template and paste it into your n8n canvas. 2. Configure Credentials: - Set up your Google Sheets and OpenAI credentials in n8n. 3. Apify Token: - Locate the Apify LinkedIn Scraper node (HTTP Request). - In Header Parameters > Authorization, replace YOURAPIFYAPITOKEN with your actual Apify Bearer token. 4. Google Sheet Configuration: - Open the Fetch Leads node. Select your generic Sheet and specific Workbook. - Open both Update Row nodes (there are two: one for the Website branch, one for the LinkedIn branch) and ensure they point to the same Sheet/Workbook. 5. Customize AI Prompts: - Open the two Write Email Copy nodes. - In the system prompt, look for [YOURBUSINESSTYPE] and [YOURCOMPANYNAME]. Replace these with your actual business details to ensure the AI generates relevant outreach. Customization - Model Selection: You can switch the OpenAI model to gpt-3.5-turbo to save costs, though the quality of the "Icebreakers" may decrease. - Output Columns: The workflow currently outputs Icebreaker, intro, and companyType. You can modify the Update Row nodes to map these to different column headers in your sheet if needed.

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How to import this n8n workflow

  1. 1

    Download the workflow JSON file after purchase.

  2. 2

    Open n8n → click the menu → Import from File.

  3. 3

    Select the downloaded JSON and import.

  4. 4

    Set up credentials for each node that requires them.

  5. 5

    Click Execute Workflow to test, then activate.

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