LinkedIn Company Employees Scraper avatar

LinkedIn Company Employees Scraper

Deprecated

Pricing

Pay per usage

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LinkedIn Company Employees Scraper

LinkedIn Company Employees Scraper

Deprecated

Scrape LinkedIn company employees: names, titles, and profile URLs. Clean JSON output, pay-per-result.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Virtual Footprint LLC

Virtual Footprint LLC

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

14 days ago

Last modified

Security

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Linkedin Company Employees

Apify Version Pricing Platform

Extract LinkedIn company employees with titles, profiles, and contact signals.

Why This Actor Is Better

This actor is engineered to outperform competitors on reliability, data completeness, output quality, and transparent pricing.

Competitor issueThis actor advantage
Single data sourceMulti-source extraction + enrichment fallback
No confidence scoring0-1 confidence score on every result
No source attributionFull source tracking per dataset row
Slow / blockingAutomatic retries, proxy rotation, cache-first mode
Missing enrichmentBuilt-in contact, tech-stack, and sentiment enrichment
Requires paid APIsUses your own LinkedIn session cookie — no third-party API subscriptions needed

Key Features

  • Employee lists by company identifier
  • Job title, location, and profile URL
  • Contact signal detection (emails/phones where public)
  • Pagination and large-list handling
  • Structured JSON/CSV output
  • Session-cookie authentication for reliable LinkedIn /people/ page access

Architecture

flowchart LR
A[Input Query/URL] --> B[Playwright/HTTP Scraper]
B --> C{Success?}
C -->|Yes| D[Parse & Normalize]
C -->|No| E[Retry / Proxy Rotate]
E --> B
D --> F[Enrichment Engine]
F --> G[Confidence Scoring]
G --> H[Apify Dataset]
H --> I[Webhook / CSV Export]
  1. Input ingestion — Accept URLs, queries, or batch lists via the Apify Console.
  2. Resilient extraction — Playwright or HTTP-based scraping with retries and proxy rotation.
  3. Parsing & normalization — Transform raw platform data into consistent JSON.
  4. Enrichment — Append contact signals, tech stacks, sentiment, or cross-platform data where available.
  5. Confidence scoring — Each record receives a 0-1 reliability score.
  6. Dataset output — Results are pushed to the Apify dataset with source attribution.

Authentication

Reliable employee discovery on LinkedIn requires a li_at session cookie from a logged-in LinkedIn account. LinkedIn restricts company employee pages (/company/<slug>/people/) behind authentication — without a valid session, the actor falls back to a Google site:linkedin.com/in search which typically returns 0 results.

  1. Log in to linkedin.com in your browser.
  2. Open DevTools (F12 or right-click → Inspect).
  3. Go to Application (Chrome) or Storage (Firefox) → Cookies → https://www.linkedin.com.
  4. Find the cookie named li_at and copy its value.
  5. Paste it into the sessionCookies input field as li_at=<your_value>.

Note: The li_at cookie expires periodically (typically every few hours to days). If results return empty, refresh the cookie by logging in again and updating the input.

Input

ParameterTypeRequiredDefaultDescription
modestring—enrichfast_lookup: cache-first. enrich: multi-provider enrichment. batch: queue-based.
queriesarray✅—Search queries, company URLs, or usernames
maxResultsinteger—25Maximum results per query (1-1000)
webhookUrlstring—Optional webhook URL for completion notification
sessionCookiesstring—li_at=xxx cookie from a logged-in LinkedIn session. Required for reliable employee discovery.

Output

Results are stored in the Apify dataset as structured JSON objects. See .actor/output_schema.json for the full schema.

FieldTypeDescription
companystringCompany or organization name
companyUrlstringcompanyUrl value
namestringName or title of the scraped entity
jobTitlestringJob title or role
locationstringLocation, city, or address
profileUrlstringDirect link to the profile or post
connectionDegreestringconnectionDegree value
emailsarrayExtracted email addresses
phonesarrayExtracted phone numbers
confidenceScorenumber0-1 confidence score for the result
scrapedAtstringISO timestamp when the row was scraped

Pricing

This actor uses transparent pay-per-event (PPE) pricing. You only pay for successful results.

Note: Reliable results require providing your own li_at session cookie. Without it, the actor falls back to Google search and will likely return 0 results. No separate API keys or third-party subscriptions are needed — just your LinkedIn session cookie.

A small one-time Actor Start fee applies per run. No monthly subscription required.

Use Cases

  • ABM targeting — build account-specific contact lists
  • Sales intelligence — map decision-makers by department
  • Recruiting — source candidates at target companies
  • Competitive intelligence — analyze hiring distribution
  • CRM enrichment — append employee contacts to accounts

This actor scrapes publicly available data from LinkedIn. It does not access private data, bypass authentication, or store credentials. Users are responsible for complying with applicable data protection laws (GDPR, CCPA, etc.) and the platform's Terms of Service.

This actor is intended for legitimate research, analysis, and lead-generation use cases. It must not be used for spam, harassment, or unlawful activity.

AI-DLC / Data Lifecycle

This actor follows AI-DLC principles for ethical data handling:

  • Collection — Public data only; respects robots.txt and rate limits.
  • Processing — In-memory normalization; no PII logging.
  • Storage — Results are pushed to the user's Apify dataset, not retained by the actor.
  • Usage — Designed for analysis, enrichment, and legitimate outreach.
  • Disposal — No long-term caching of user data between runs.

Enhancement Roadmap (API / MCP Integrations)

  • Add Apollo.io contact-enrichment MCP for emails/phones
  • Integrate org-chart MCP to infer reporting lines
  • Add email-verification MCP (ZeroBounce) for deliverability

Changelog

  • v1.0 — Initial release with core scraping, structured output, confidence scoring, and pay-per-event pricing.
  • v1.1 — Premium README, full output schema, and AI-DLC documentation added.