LinkedIn Post Engagement Data Extractor

Use Case

This automation is designed to extract key engagement metrics and audience data from a LinkedIn post. It's useful for analyzing the impact of content and identifying engaged users for lead generation, marketing, or research purposes.

What It Does

Given a LinkedIn post URL and an Airtop profile, this automation extracts:

• Total number of reactions
• Total number of comments
• Total number of reposts
• A list of users who reacted or commented, including:
  • Their full name
  • Their job title
  • A link to their LinkedIn profile

Input Parameters

| Name | Description | Required | |------------------|------------------------------------------------------------|----------| | airtop_profile | The name of an Airtop Profile that's logged into LinkedIn | Yes | | linkedin_post_url| The full URL of the LinkedIn post you want to analyze | Yes |

How It Works

1. The workflow starts when triggered manually or from another workflow/form.
2. It maps input fields for Airtop profile and post URL.
3. Airtop opens a browser session and loads the LinkedIn post.
4. An AI agent is instructed to extract engagement data via prompt-based analysis.
5. The response is parsed and output in a structured format.

Output Format

The output will be a structured JSON object with the following fields:

{
  "interactors": [
    {
      "name": "Jane Doe",
      "job_title": "Marketing Director at ExampleCorp",
      "profile_url": "https://linkedin.com/in/janedoe"
    }
    // ... more interactors
  ],
  "reactions_count": 153,
  "comments_count": 21,
  "reposts_count": 8
}

Read more about how to [extract Linkedin post comments and reactions](https://www.airtop.ai/automations/linkedin-post-engagement-data-extractor-n8n).