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In this video, we walk through one of the most effective prospecting workflows in Airschool: scraping the likers and commenters of a LinkedIn post, qualifying them automatically with AI, and enriching only those who match your Ideal Customer Profile.

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Why scrape LinkedIn posts?

LinkedIn is one of the largest professional databases available. When someone likes or comments on a post, whether from a competitor, a client, or an industry thought leader, they are signaling interest in a specific topic. This engagement data can be turned into a targeted list of high-quality prospects, without wasting credits on unqualified contacts.

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Extract likers and/or commenters

Start by copying the URL of the LinkedIn post you want to scrape. Then, on the Airschool platform, open the Extract LinkedIn post likers and commenters module and:
  • Give your search a name
  • Paste the LinkedIn post URL
  • Select what you want to extract: likers, commenters, or both
Once launched, Airschool builds a table containing key information for each profile, including:
  • First Name
  • Last Name
  • Job title
  • Company Name
  • Company Location
  • LinkedIn URLs
  • Reaction Type
  • People Profile: a rich summary pulled directly from LinkedIn, including headline, bio, all professional experiences, etc.
This People Profile field is especially important as it is the data that will be used in the next step to qualify each contact with AI.

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Qualify your ICP with AI

Once the table is ready, use the AI enrichment feature to automatically score each profile against your ICP criteria. To do this:
  1. Click Use AI and select the rows to process
  2. Choose your language model (e.g. GPT-5 Mini for speed and cost efficiency)
  3. Write your qualification prompt or import a saved template
In this example, the prompt evaluates whether the person matches Airschool’s ICP based on their LinkedIn profile data.
Important: make sure the People Profile field is correctly set as the input before running the workflow.
The AI returns a simple Yes / No ICP Fit score for each contact.

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Filter & enrich

Once the AI has processed all rows:
  1. Filter the table by ICP Fit = Yes
  2. Enrich only the qualified profiles with emails and phone numbers
This approach ensures you only spend credits on contacts that are genuinely relevant, maximizing both data quality and cost efficiency.

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Export the final prospect list

Finally, the qualified and enriched list can be exported directly to your tools:
  • CRM systems
  • Cold email platforms
  • Webhooks for automation
  • CSV download