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Lead Generation System: LinkedIn Hyper Personalized Outreach

Overview

This document outlines the automated system for generating personalized leads using LinkedIn job posts. The process involves scraping job posts, identifying decision-makers, retrieving contact information, and creating personalized first lines for outreach.

System Workflow

Step 1: Scrape LinkedIn Job Posts

1. Input Requirements: Gather inputs for the search query, including:

✳️Location
✳️Job Title
✳️Number of job posts to return

2. Automation Process:

✳️Use a form to collect the query inputs.
✳️Feed these inputs into a scraping tool (e.g., Apify) to extract job posts.
✳️Save the scraped data into a Google Sheets file.

3. Output:

✳️A spreadsheet containing the scraped job posts, including job title, company name, and other relevant details.

Step 2: Identify Decision Makers

1. Input Requirements: Company names from the job post spreadsheet.

2. Automation Process:

✳️Use the company name to perform a Google search for the CEO’s name.
✳️Extract the decision-maker’s name using AI analysis of the search results.
✳️Update the spreadsheet with the decision-maker’s name.

3. Output:

✳️A spreadsheet with the decision-makers’ names added to the corresponding job posts.

Step 3: Find Company Domains

1. Input Requirements: Company names from the job post spreadsheet.

2. Automation Process:

✳️Perform a Google search using the company name to find the domain.
✳️Extract the domain using AI.
✳️Update the spreadsheet with the domain name.

3. Output:

✳️A spreadsheet with company domains added.

Step 4: Retrieve Email Addresses

1. Input Requirements:

✳️Decision maker’s name
✳️Company domain

2. Automation Process:

✳️Make an HTTP request using the format: "Decision Maker Name + @ + domain"
✳️Extract the HTML from the search and convert it to text.
✳️Use AI to identify and extract the decision maker’s email address.
✳️Update the spreadsheet with the email address.

3. Output:

✳️A spreadsheet with decision-makers’ email addresses.

Step 5: Create Personalized First Lines

1. Input Requirements:

✳️Scraped job description
✳️Company details
✳️Information retrieved via Google search

2. Automation Process:

✳️Feed the scraped data into AI with context to create personalized first lines.
✳️Update the spreadsheet with the created first lines

3. Output:

✳️A spreadsheet containing personalized first lines for outreach.

Automation Tools Used

➡️Apify: For scraping LinkedIn job posts.
➡️Google Sheets: For storing and updating data throughout the workflow.
➡️OpenAI: For analyzing text, identifying decision-makers, extracting email addresses, and generating personalized first lines.
➡️HTTP Requests: For retrieving email addresses.
➡️Markdown to HTML Conversion: For formatting content into presentable documents.

Benefits of the System

✅Efficiency: Automates a time-intensive process, significantly reducing manual effort.
Personalization: Creates tailored outreach messages for better response rates.
Scalability: Can handle large datasets and adapt to various job titles, locations, and industries.

Example Outputs

Spreadsheet Columns:

❇️Company Name
❇️Job Title
❇️Company Linkedin
❇️Company Description
❇️Job Description
❇️Apify Datased ID
❇️Decision Maker Name
❇️Domain
❇️Decision Maker’s Email Address
❇️Personalized First Line

If you want to learn more about this automation, click the link below and book a FREE call with me.

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