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SKILL FILE

Scrape LinkedIn Profiles with AI

Extract profile data, job titles, companies, and connections from LinkedIn using Apify scrapers and Claude Code.

1B+ professionals on LinkedIn
500 profiles enriched per run
$1.50 per 1,000 profiles scraped
Download Skill File ↓

How scraped LinkedIn data flows across your company

One scrape generates intelligence for every department — automatically

Scrape LinkedIn Profiles Professional data at scale
1 Define Target Criteria
2 Apify Scraper Runs
3 Profiles Enriched
4 CRM Updated
Sales
  • Build prospect lists by title/company
  • ICP matching and lead scoring
  • Personalized connection request drafts
  • Territory and account mapping
Marketing
  • Audience research by role/industry
  • Persona building from real data
  • Content targeting by seniority
  • Thought leader identification
Growth
  • Market mapping by geography
  • Hiring signal detection
  • Competitive headcount tracking
  • TAM estimation by segment
CRM
  • Contact enrichment with work history
  • Company intel stored
  • LinkedIn URLs linked to records
  • Duplicate detection and merge
Prospect Spreadsheet
Outreach Sequences
Persona Document
ICP Report
Events Tracked
Contacts created with LinkedIn source
LinkedIn URLs linked to CRM records
Company data enriched
ICP scores assigned
Replaces LinkedIn Sales Navigator
$99/mo $5/mo
$1,128/yr saved
Scrape LinkedIn Profiles Professional data at scale
1
Define Target Criteria Job titles, companies, industries, locations, or profile URLs
2
Apify Scraper Runs LinkedIn profile extractor pulls full professional data — $1.50/1K
3
Profiles Enriched Matched against ICP, scored, company data cross-referenced
4
CRM Updated Qualified leads loaded with ICP scores and LinkedIn URLs
Sales
  • Build prospect lists by title/company
  • ICP matching and lead scoring
  • Personalized connection request drafts
  • Territory and account mapping
Marketing
  • Audience research by role/industry
  • Persona building from real data
  • Content targeting by seniority
  • Thought leader identification
Growth
  • Market mapping by geography
  • Hiring signal detection
  • Competitive headcount tracking
  • TAM estimation by segment
CRM
  • Contact enrichment with work history
  • Company intel stored
  • LinkedIn URLs linked to records
  • Duplicate detection and merge
Content Outputs
Prospect Spreadsheet from sales
ICP Report from growth
Persona Document from marketing
Outreach Sequences from sales
Everything Tracked
Contacts created with LinkedIn source
LinkedIn URLs linked to CRM records
Company data enriched
ICP scores assigned
Replaces LinkedIn Sales Navigator
$99/mo $5/mo
$1,128/yr saved

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SoloStack + Claude Code

$5/mo
  • Pay-per-use, no subscription
  • Your data in your repo
  • Zero vendor lock-in
  • Unlimited exports
Save $768/year

What this skill file teaches Claude

Drop one markdown file into your repo. Claude Code learns how to run this entire workflow.

1

Full Profile Extraction

Pull name, headline, current company, location, about section, and profile photo URL from any public LinkedIn profile.

2

Work Experience History

Extract complete employment history — company names, job titles, date ranges, and role descriptions for career pattern analysis.

3

Education & Certifications

Capture university names, degrees, fields of study, graduation years, and professional certifications.

4

Skills & Endorsements

Pull listed skills with endorsement counts to understand expertise areas and identify technical decision-makers.

5

Connection Count & Activity

See connection volume (500+ indicator), recent post activity, and engagement levels to gauge influence and responsiveness.

6

Bulk URL Processing

Feed in hundreds of LinkedIn profile URLs from Sales Navigator searches, event attendee lists, or company pages and scrape them all in one run.

Apify Actor: anchor/linkedin-people-profiles-scraper · ~$1.50 per 1,000 profiles

Build it with plain English

Tell Claude Code what to do. It handles the rest.

claude — solostack/
you: |
Scraping VP Marketing profiles at Series B SaaS in SF...

✓ 143 profiles found and extracted
✓ 143/143 have current company data
✓ 128 have 500+ connections
✓ Average tenure in current role: 2.3 years
✓ Top previous companies: Google (12), Meta (8), Salesforce (7)

Data saved to vp-marketing-sf-saas.json
Next: Score against ICP and draft personalized connection requests?
you: |
Processing 200 LinkedIn profile URLs...

✓ 194/200 profiles successfully scraped (6 private/deleted)
✓ 194 full work histories extracted
✓ 187 education records captured
✓ Average experience: 12.4 years
✓ Most common skills: SaaS (89), B2B Marketing (76), Growth (71)

Exported to linkedin-profiles-enriched.csv
Next: Match against CRM contacts to find existing relationships?
you: |
Scraping fintech CTOs in London (500+ connections)...

✓ 87 matching profiles extracted
✓ 87 current company names captured
✓ 72 have engineering backgrounds
✓ 45 previously founded a company
✓ Top universities: Imperial (14), UCL (11), Cambridge (9)

Data saved to fintech-ctos-london.json
Next: Enrich with company funding data and draft outreach?

What you can build with this

B2B lead generation

Build targeted prospect lists by job title, company, and industry. Extract contact context for personalized outreach that references their background and experience.

Recruiting & talent sourcing

Scrape candidate profiles matching your hiring criteria. Analyze work history patterns, skills overlap, and education to shortlist the best fits before reaching out.

Competitive intelligence

Track competitor hiring patterns by scraping their employees' profiles. Identify new teams being built, leadership changes, and strategic shifts before they're announced.

Investor & partner research

Build dossiers on potential investors, advisors, or partners. Understand their portfolio, background, and connections to craft warm introductions.

Things to know

!

LinkedIn aggressively rate-limits automated access. Use reasonable batch sizes (200-500 profiles per run) and space runs at least 30 minutes apart to avoid account restrictions.

!

Profiles set to private or with restricted visibility will return limited data. Expect 3-5% of URLs to return incomplete results.

!

Never use scraped LinkedIn data for unsolicited bulk email — this violates CAN-SPAM and GDPR. Use it for personalized, one-to-one outreach only.

Get the full skill file

Everything above is 80% of the skill file. Download the complete version with full implementation details, agent prompts, and ready-to-run scripts.

Common questions

The Apify actor handles authentication and session management. You don't need to provide your own LinkedIn credentials. The actor uses its own infrastructure to access public profile data, keeping your personal account safe from rate limiting or restrictions.
LinkedIn has anti-scraping measures, but Apify's actors are designed to mimic human browsing patterns and rotate sessions. The key is moderation — scraping 500 profiles per day is fine; scraping 50,000 in an hour will trigger blocks. Our pipeline enforces sensible rate limits by default.
The data is as accurate as what's on the person's LinkedIn profile. Job titles, companies, and dates come directly from the profile. The main limitation is that some people don't keep their profiles updated — roughly 15-20% of profiles have outdated current positions.
Yes, though that uses a different Apify actor. Company page scraping extracts employee count, industry, headquarters, description, and specialties. You can combine company scraping with profile scraping to build complete org charts.
Scraping publicly available professional data for legitimate business purposes (B2B sales outreach) generally falls under 'legitimate interest' in GDPR. However, you must provide an opt-out mechanism, honor data deletion requests, and never scrape or store sensitive personal data. Consult legal counsel for your specific use case.

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