LinkedIn Company Employees

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 issue	This actor advantage
Single data source	Multi-source extraction + enrichment fallback
No confidence scoring	0-1 confidence score on every result
No source attribution	Full source tracking per dataset row
Slow / blocking	Automatic retries, proxy rotation, cache-first mode
Missing enrichment	Built-in contact, tech-stack, and sentiment enrichment
Requires paid APIs	No external API keys required for core extraction

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

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.

Input

Parameter	Type	Required	Default	Description
mode	string	—	enrich	fast_lookup: cache-first. enrich: multi-provider enrichme...
queries	array	✅	...	Search queries, profile URLs, or usernames
maxResults	integer	—	25	Maximum results per query (1-1000)
webhookUrl	string	—		Optional webhook URL for completion notification

Output

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

Field	Type	Description
company	string	Company or organization name
companyUrl	string	companyUrl value
name	string	Name or title of the scraped entity
jobTitle	string	Job title or role
location	string	Location, city, or address
profileUrl	string	Direct link to the profile or post
connectionDegree	string	connectionDegree value
emails	array	Extracted email addresses
phones	array	Extracted phone numbers
confidenceScore	number	0-1 confidence score for the result
scrapedAt	string	ISO timestamp when the row was scraped

Pricing

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

Plan	Price per 1K results	Savings
Leading competitors	~$6.75/1K	—
This actor	$5.00/1K	26% cheaper

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

Legal & Compliance

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.