LinkedIn Post Reactions Scraper

Identify who's engaging with specific LinkedIn posts and comments. Extract reaction data with profile information including name, role, company, and contact details. Get a table of engaged users with their professional background; and filter through the table and generate additional columns with AI.

Skills

Get Post Reactions

Extract reactions from LinkedIn posts or comments to identify engaged audiences. Filter by reaction type (like, praise, empathy, appreciation, interest, entertainment) and choose between basic profile data or full professional background including experience, education, and skills.

Get reactions from a post about AI product development to identify engaged professionals interested in this space.

Extract reactions from competitor product announcements to find potential customers showing interest.

Identify who reacted to posts about startup fundraising to discover active investors and founders.

Get reactions from B2B SaaS posts to build a list of engaged prospects for outreach.

Find professionals who reacted to software engineering content to identify potential candidates.

View Table

View specific rows and columns from any table, ask questions about it, and analyse it with AI. If the agent performs searches, explain which rows are good and bad to improve the search.

Which job titles are most represented in these reactions?

What companies do these engaged users work for?

What types of reactions are most common?

Which profiles have the most connections?

What industries are represented in this data?

Filter Table

Filter any table with traditional filtering (i.e. patterns like names, URLs, etc). Explain what table you want to filter, and what rows you want to keep or remove.

Keep only senior-level professionals (VP, Director, C-level).

Remove students and keep only working professionals.

Keep only those with 500+ connections.

Keep only those who reacted with 'INTEREST' or 'APPRECIATION'.

Remove profiles without a profile picture.

Filter Table with AI

Filter any table with AI filtering (i.e. reasoning, semantic understanding, etc). Explain what table you want to filter, and what rows you want to keep or remove.

Keep only those who appear to be decision-makers at B2B SaaS companies based on their role and company.

Keep only those currently working in AI, ML, or data science roles based on their position and experience.

Keep only those who might be potential angel investors or VCs based on their background and current role.

Keep only those working at high-growth startups, exclude enterprise and consulting.

Keep only senior engineers or technical leads at tech companies, exclude non-technical roles.

Generate Table

Generate a new table from any table with AI. Explain what table you want to generate from, what columns you want to keep, and what new columns you want to generate.

Assess ICP fit based on their role, company, and experience, then generate a personalized outreach angle.

Identify their likely pain points based on their position, and create a value proposition for our product.

Extract key career transitions and achievements, then generate an investor pitch angle if they're a potential investor.

Summarize their expertise area based on experience and skills, and create a recruitment pitch for open roles.

Identify shared interests or connections based on their background, and generate a warm introduction message.