Workflow overview
Why this workflow matters
Helpful for business development and pipeline building.
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 The workflow starts when triggered manually or from another workflow/form. It maps input fields for Airtop profile and post URL. Airtop opens a browser session and loads the LinkedIn post. An AI agent is instructed to extract engagement data via prompt-based analysis. 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.
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