LinkedIn Engager Analytics

Pull every liker and commenter on a LinkedIn post and bucket them by ICP fit. Outputs a roster + action list you can feed into your DM or outreach queue.

Needs a read credential: APIFY_TOKEN, or the Apify MCP connector (the only option on claude.ai). With neither, falls back to user-paste of the engager list.

When to use

• After publishing a post: "Who actually engaged? Are they ICP?"
• Before a campaign: "Pull the last 5 viral posts in my niche, group their commenters by company size"
• Reviewing competitor engagement: which prospects show up across multiple authors

Input

• One or more LinkedIn post URLs
• Optional: ICP definition (target titles, company size, industry)
• Optional: max engagers per post (default 100)

Output

Output format (engager roster, tier breakdown, action lists): see references/output-spec.md. Headline: a table of engagers labelled by ICP tier and a per-tier action list.

Steps

1. Fetch engagers. Call lib.ApifyClient.fetch_post_engagers(post_url=<url>, max_items=100). Returns a list of dicts with type ("commenters" | "likers"), name, subtitle (job title + company), url_profile, content (comment text if commenter), datetime. Cost is roughly $0.005 per engager-record. The underlying actor answers for one audience per run, so max_items is the total across both and is split evenly; pass types=("likers",) when only one side matters, or add "reshares" to include people who reposted.