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Generate personalized sales outreach with GPT across LinkedIn, Email & WhatsApp

Aditya MalurAditya Malur
469 views
2/3/2026
Official Page

Overview

This workflow automates your entire sales outreach process across LinkedIn, Email, and WhatsApp using AI to create hyper-personalized messages for each prospect. Instead of spending hours crafting individual messages, the workflow analyzes your lead data and generates customized connection requests, emails, and WhatsApp messages that feel genuinely personal and researched.

The workflow includes a built-in approval mechanism, so you can review all AI-generated messages before they're sent, ensuring quality control while still saving massive amounts of time.

How It Works

The workflow follows a seven-step process:

Step 1: Data Collection The workflow starts by reading your lead data from a Google Sheet. Your sheet should contain information about each prospect including their name, title, company, industry, technologies they use, and any other relevant details that can be used for personalization.

Step 2: Batch Processing To prevent overwhelming APIs and ensure smooth operation, the workflow processes leads in batches. Each lead's complete data is prepared and formatted for the AI agent to analyze.

Step 3: AI Personalization This is where the magic happens. The AI agent receives all the prospect data and generates three distinct messages:

  • A LinkedIn connection request (under 300 characters) that references their specific role, company, or industry
  • A professional HTML email that demonstrates you've researched their business and explains how you can help
  • A casual WhatsApp message that's friendly and approachable

The AI is instructed to make these messages sound completely human, never generic or templated.

Step 4: Data Cleanup and Storage The AI's output is parsed and cleaned up, then written back to your Google Sheet in separate columns. This creates a permanent record of all generated messages for your review.

Step 5: Manual Approval Before anything gets sent, you receive an email asking for your approval. You can review all the generated messages in your Google Sheet, make any edits if needed, and then approve or reject the batch. This ensures you maintain full control over what goes out.

Step 6: LinkedIn Automation Once approved, the workflow triggers your Phantombuster agent to send LinkedIn connection requests using the AI-generated messages. Phantombuster handles the actual LinkedIn interaction safely within their platform's limits.

Step 7: Email and Notification Delivery Finally, the workflow sends out the personalized emails via Gmail and optionally notifies you via Telegram for each message sent. This happens sequentially to respect rate limits and maintain deliverability.

Setup Requirements

Before you can use this workflow, you'll need to set up several accounts and gather credentials:

Essential Services:

  • An n8n instance (cloud or self-hosted)
  • A Google account with Google Sheets access
  • A Gmail account for sending emails
  • An OpenAI account with API access (for the AI agent)
  • Phantombuster account (for LinkedIn automation)

Optional Services:

  • Telegram account and bot (for notifications)

Credentials You'll Need:

  • Google Sheets OAuth2 credentials
  • Gmail OAuth2 credentials
  • OpenAI API key
  • Phantombuster API key and agent ID
  • Telegram bot token and chat ID (if using notifications)

How to Use This Workflow

Initial Setup:

  1. Import this workflow into your n8n instance
  2. Add all required credentials in n8n's credential manager
  3. Create your Google Sheet with the following columns at minimum: First Name, Last Name, Title, Company Name, Personal Email, Industry, Website. Add three additional columns for output: Connection, AI Email, AI Whatsapp Message
  4. Copy your Google Sheet ID from the URL and update it in all Google Sheets nodes
  5. Open the AI Agent node and update the prompt with your personal information: your name, title, email, and LinkedIn URL
  6. Update the email addresses in the Gmail nodes to your actual email addresses
  7. Configure your Phantombuster agent for LinkedIn and add the API key and agent ID

Running the Workflow:

  1. Add your lead data to the Google Sheet (you can start with just 2-3 leads for testing)
  2. Click "Execute Workflow" in n8n to start the process
  3. Wait for the AI to generate messages (this takes a few seconds per lead)
  4. Check your email for the approval request
  5. Review the AI-generated messages in your Google Sheet
  6. Reply to the approval email with your decision
  7. If approved, the workflow will automatically send LinkedIn requests, emails, and WhatsApp messages

Best Practices:

Start small. Process 5-10 leads at a time initially to test the quality of AI-generated messages and ensure everything works correctly. Once you're confident in the output, you can scale up to larger batches.

Monitor your results. Keep track of response rates in your Google Sheet and adjust the AI prompt if certain types of messages aren't performing well.

Respect rate limits. Gmail allows 100-500 emails per day depending on your account type, and LinkedIn has strict limits on connection requests (typically 100 per week through automation tools). Stay well within these limits to avoid account restrictions.

Customizing This Workflow

The workflow is designed to be highly customizable to fit your specific use case:

Personalizing the AI Prompt:

The most important customization is in the AI Agent node's prompt. You can modify it to:

  • Emphasize different aspects of your value proposition
  • Change the tone from formal to casual or vice versa
  • Include specific pain points relevant to your target industry
  • Add your company's unique selling points
  • Adjust message length and structure

Modifying the Output:

You can change what the AI generates by editing the prompt. For example, you might want:

  • Different message types (Twitter DMs instead of WhatsApp)
  • Multiple email variations for A/B testing
  • Follow-up message sequences
  • Industry-specific templates

Adding Features:

The workflow can be extended with additional nodes:

  • Add time delays between sends to appear more natural
  • Include condition checks to segment leads by industry or company size
  • Connect to your CRM to automatically log activities
  • Add sentiment analysis to filter out negative-sounding messages
  • Implement response tracking by monitoring your inbox

Changing Tools:

If you prefer different services, you can swap out nodes:

  • Replace Phantombuster with other LinkedIn automation tools
  • Use SendGrid or Mailgun instead of Gmail for higher volume
  • Add Slack notifications instead of Telegram
  • Connect to WhatsApp Business API for official messaging

Data Source Alternatives:

Instead of Google Sheets, you could:

  • Connect directly to your CRM (HubSpot, Salesforce, Pipedrive)
  • Use Airtable as your database
  • Pull data from CSV files uploaded to cloud storage
  • Integrate with lead generation tools like Apollo or Hunter

Tips for Success

The quality of your AI-generated messages depends heavily on the data you provide. The more information you have about each prospect (their role, company size, technologies used, recent news, pain points), the more personalized and effective the messages will be.

Regularly review and refine your AI prompt based on the responses you're getting. If prospects aren't responding, your messages might be too sales-focused or not personal enough. Adjust the prompt to make messages feel more consultative and helpful.

Don't send to your entire list at once. Even with approval gates, it's wise to test with small batches, measure results, iterate on your approach, and then scale up gradually.

Always comply with email and LinkedIn best practices. Never spam, always provide value in your outreach, respect people's time and privacy, and make it easy for them to opt out if they're not interested.

This workflow is a powerful tool that can save you hours of work while actually improving the quality of your outreach through AI-powered personalization. Use it responsibly and watch your response rates improve.

Generate Personalized Sales Outreach with GPT Across LinkedIn, Email, and WhatsApp

This n8n workflow automates the process of generating highly personalized sales outreach messages using OpenAI's GPT model and then distributing them across multiple communication channels: LinkedIn, Email (via Gmail), and WhatsApp Business Cloud. It helps sales teams scale their outreach efforts while maintaining a personal touch.

What it does

This workflow streamlines your sales outreach by performing the following steps:

  1. Reads Contact Data: Initiates by reading contact information from a Google Sheet, which likely contains prospect details such as name, company, role, and potentially other personalized data points.
  2. Prepares Data for AI: Transforms the raw data from Google Sheets into a structured format suitable for the AI agent, likely mapping fields and setting up variables.
  3. Generates Personalized Outreach with AI: Utilizes an AI Agent (powered by an OpenAI Chat Model) to generate personalized outreach messages for each contact. This agent is configured to create tailored content for LinkedIn, Email, and WhatsApp, leveraging the provided contact data.
  4. Routes Messages by Channel: After generation, an "If" node checks if a specific communication channel (e.g., LinkedIn, Email, WhatsApp) is enabled or preferred for the current contact.
  5. Sends LinkedIn Messages: If LinkedIn is the chosen channel, it sends the personalized message via an HTTP Request node (assuming an external LinkedIn API integration).
  6. Sends Emails: If email is the chosen channel, it sends the personalized email using the Gmail node.
  7. Sends WhatsApp Messages: If WhatsApp is the chosen channel, it sends the personalized message via the WhatsApp Business Cloud node.
  8. Iterates for All Contacts: The "Loop Over Items" node ensures that the entire process is repeated for every contact read from the Google Sheet, enabling bulk personalized outreach.
  9. Provides Notes: Includes a sticky note for additional context or instructions within the workflow.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Google Sheets Account: To store and retrieve your contact list.
  • OpenAI API Key: For the OpenAI Chat Model to generate personalized messages.
  • LinkedIn API Access (or similar): The HTTP Request node will need to be configured with the appropriate API endpoint and credentials to send messages on LinkedIn.
  • Gmail Account: Configured as a credential in n8n for sending emails.
  • WhatsApp Business Cloud Account: Configured as a credential in n8n for sending WhatsApp messages.
  • Telegram Account (Optional): If the Telegram node is intended for notifications or approvals, a Telegram Bot token and chat ID will be needed.

Setup/Usage

  1. Import the Workflow: Download the provided JSON file and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your Google Sheets credential to access your contact spreadsheet.
    • Configure your OpenAI credential with your API key.
    • Set up your Gmail credential.
    • Set up your WhatsApp Business Cloud credential.
    • Configure any necessary credentials for the HTTP Request node if it requires authentication for LinkedIn or other custom APIs.
    • (Optional) Configure your Telegram credential if you plan to use it for notifications.
  3. Update Google Sheets Node:
    • Specify the Spreadsheet ID and Sheet Name where your contact data is located.
    • Ensure the column headers in your Google Sheet match the data expected by the "Edit Fields (Set)" and "AI Agent" nodes (e.g., name, company, role, email, linkedinProfile, whatsappNumber, preferredChannel).
  4. Review "Edit Fields (Set)" Node: Verify that the fields being set or transformed correctly map to your Google Sheet data and the inputs expected by the AI Agent.
  5. Configure "AI Agent" Node:
    • Ensure the prompt for the AI Agent is tailored to generate the desired personalized messages for each channel (LinkedIn, Email, WhatsApp).
    • Adjust model parameters (e.g., temperature, max tokens) as needed.
  6. Configure "If" Node:
    • Review the conditions in the "If" node to ensure it correctly identifies the preferred communication channel for each contact based on your data (e.g., {{ $json.preferredChannel === 'LinkedIn' }}).
  7. Configure Channel-Specific Nodes:
    • HTTP Request (LinkedIn): Update the URL, headers, and body to correctly interact with the LinkedIn API or a LinkedIn automation tool.
    • Gmail: Customize the subject and body of the email, referencing the AI-generated message.
    • WhatsApp Business Cloud: Customize the message template, referencing the AI-generated message.
  8. Activate the Workflow: Once all configurations are complete, activate the workflow. You can then trigger it manually or set up a schedule to run periodically.

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