LinkedIn Company Employees Scraper

Map company employees with role signals, seniority inference, and CRM-ready output.

Why this actor is better

This actor is designed to outperform competitors in reliability, data completeness, output quality, and pricing transparency.

Competitor issue	This actor advantage
Single data source	Multi-source: LinkedIn company pages (Playwright) + Employee discovery, Role inference, Company metadata
No confidence scoring	0-1 confidence score on every result
No source attribution	Full source tracking on every dataset row
Slow / blocking	Progressive dataset pushes, 8s timeouts, cache-first mode
No enrichment	Built-in enrichment with confidence scoring
Requires paid APIs	100% open-source providers, no mandatory subscriptions
No batch support	Queue-based batch mode with per-item error isolation

Architecture

┌─────────────────────────────────────────────────────────────┐
│                    LinkedIn Company Employees Scraper                    │
├─────────────────────────────────────────────────────────────┤
│  Mode Router                                                │
│  ├─ fast_lookup (cache-first, <800ms)                      │
│  ├─ enrich (multi-provider, parallel, progressive push)    │
│  └─ batch (queue-based, per-item isolation)                │
├─────────────────────────────────────────────────────────────┤
│  Provider Layer                                             │
│  ├─ LinkedIn company pages (Playwright)                            │
│  └─ Enrichment:                                             │
│     ├─ Employee discovery                                                  │
│     ├─ Role inference                                                      │
│     └─ Company metadata                                                    │
├─────────────────────────────────────────────────────────────┤
│  Quality Layer                                              │
│  ├─ Confidence scoring (0-1)                               │
│  ├─ Source attribution                                     │
│  └─ Deduplication                                          │
├─────────────────────────────────────────────────────────────┤
│  Output Layer                                               │
│  ├─ Apify Dataset (progressive push)                       │
│  ├─ Webhook delivery                                       │
│  └─ Normalized schema with metadata                        │
└─────────────────────────────────────────────────────────────┘

Enrichment Sources

• ✅ Employee discovery
• ✅ Role inference
• ✅ Company metadata

Modes

enrich — Multi-provider enrichment (default)

• Scrapes LinkedIn company pages (Playwright)
• Enriches with: Employee discovery, Role inference, Company metadata
• Pushes base result first, then enriched result (progressive)
• 8s enrichment timeouts (fail-fast)
• Best for: lead generation, CRM enrichment, analytics

batch — Queue-based

• Accepts large query lists
• Processes each query through full enrichment
• Per-item error isolation (one failed query doesn't kill the run)
• Uses Apify Request Queue
• Best for: bulk processing, market research, territory mapping

Input

Field	Type	Required	Default	Description
mode	string	no	enrich	enrich, batch
queries	array	yes	—	Search queries, profile URLs, or usernames
maxResults	integer	no	25	Max results per query (1-1000)
webhookUrl	string	no	""	Webhook for completion notification

Example input

{
  "mode": "enrich",
  "queries": ["https://linkedin.com/company/google"],
  "maxResults": 50
}

Output

Every dataset row includes:

Field	Description
query	Input query used
name / title	Primary result name
url	Canonical URL
emails	Extracted email addresses (if applicable)
phones	Extracted phone numbers (if applicable)
socialMedia	Social media profile links
techStack	Detected technologies (if applicable)
metrics	Engagement, rating, or count metrics
confidenceScore	0-1 score based on data completeness
sources	Source attribution array
cacheStatus	hit, miss, partial, or bypass
mode	Execution mode used
extractedAt	ISO timestamp

Example output

{
  "query": "https://linkedin.com/company/google",
  "name": "Example Result",
  "url": "https://example.com",
  "emails": ["contact@example.com"],
  "phones": ["+1 (555) 123-4567"],
  "socialMedia": ["facebook.com/example"],
  "techStack": ["React", "Google Analytics"],
  "metrics": {"rating": "4.5", "reviews": "1234"},
  "confidenceScore": 0.85,
  "sources": ["primary_scraper", "website_scraper"],
  "cacheStatus": "miss",
  "mode": "enrich",
  "extractedAt": "2026-06-21T19:00:00Z"
}

Monetization

Pay-per-event pricing:

| Actor Start | $0.00005 (one-time) | | Result | $0.0050 per result | | Email Found | $0.003 per email | | Batch Item Processed | $0.002 per query |

Data Lifecycle Controls

• Purpose limitation: Lead generation, business intelligence, market research
• Data minimization: Collect only records required by queries and maxResults
• Transparency: Input, output, pricing, and constraints documented
• Security: No hardcoded API keys; secrets passed via Apify secure inputs
• Auditability: Rows include extractedAt, sources, mode, and cacheStatus

Compliance

Use this actor for legitimate research, analytics, lead generation, or monitoring. Users are responsible for complying with applicable laws, source-site terms, and privacy obligations.

Support

• Apify Console: Check your actor runs
• Issues: Report via Apify Store or actor page
• Webhook: Set webhookUrl for completion notifications