n8n LinkedIn Lead Finder: GPT-5.6 + Bright Data + Slack

Turn an ICP into qualified LinkedIn company leads—automatically

This n8n LinkedIn Lead Finder workflow takes your ICP, searches LinkedIn company pages using Bright Data, enriches each company, then scores prospects with OpenAI (GPT-5.6). Qualified and rejected leads are saved to Google Sheets, and a ranked digest is posted to Slack for fast follow-up.

What this workflow does

• Collects inputs via an n8n form: ICP, target country, and desired company count.
• Generates 5 LinkedIn-focused search queries using OpenAI (GPT-5.6), tailored to your ICP.
• Searches with Bright Data SERP API for each query, extracts valid LinkedIn company URLs, deduplicates them by company slug, and caps results to your requested maximum.
• Enriches company profiles by calling Bright Data’s LinkedIn dataset scraper, pulling details like industry, size, headquarters, specialties, and about text.
• Scores each company 0–100 against the ICP using GPT-5.6, including evidence, missing criteria, and a likely objection.
• Logs outcomes to Google Sheets: qualified and rejected leads are appended to separate tabs based on your minimum score threshold.
• Posts a ranked digest to Slack containing your qualified leads for quick review.

Use cases

• For SaaS operators: generate outbound lead lists from an ICP without manual LinkedIn research.
• For automation engineers: build a repeatable pipeline that turns form inputs into enriched prospects, evidence, and scoring.
• For sales teams: receive a daily/weekly Slack digest of top-matching LinkedIn company leads with “why it fits” context.

Technical details

• OpenAI: GPT-5.6 used for query planning and company scoring.
• Bright Data: SERP API to find LinkedIn URLs + LinkedIn dataset scraper to enrich company details (HTTP Header Auth with Authorization: Bearer <API_KEY>).
• Google Sheets: separate tabs for qualified vs rejected companies.
• Slack: posts a ranked qualified-leads digest.
• n8n logic nodes: if, set, code, limit, slack, split out.