LinkedIn Employee Movement & Workforce Intelligence

Analyze current and previous public LinkedIn employee datasets to detect hires, departures, role changes and workforce expansion signals.

Why use this Actor

Competitive, recruiting and sales teams need repeatable evidence of workforce movement instead of repeatedly reviewing raw employee exports. This Actor is deliberately separated from source extraction. It accepts supplied public-data rows or an Apify Dataset and turns them into recurring decision intelligence. That architecture reduces dependence on source-site markup, login flows and proxy behavior while letting upstream collection tools change without rebuilding the intelligence layer.

Key features

• Detects hires and departures across reusable snapshots
• Detects title and location changes for retained employees
• Produces workforceMovementScore and expansion/contraction signals
• Works on supplied Apify datasets without bypassing LinkedIn authentication
• Reads inline rows or an Apify Dataset with read-only permissions.
• Compares an optional previous snapshot and emits deterministic agentAction output.
• Runs at 256 MB with no mandatory paid LLM or browser dependency.

Example

{
  "currentItems": [
    {
      "id": "e1",
      "name": "Ana Silva",
      "title": "AI Engineer",
      "company": "Acme",
      "location": "São Paulo",
      "url": "https://linkedin.example/e1"
    },
    {
      "id": "e2",
      "name": "Bruno Lima",
      "title": "Sales Director",
      "company": "Acme",
      "location": "Rio",
      "url": "https://linkedin.example/e2"
    },
    {
      "id": "e3",
      "name": "Carla Souza",
      "title": "Data Engineer",
      "company": "Acme",
      "location": "Remote",
      "url": "https://linkedin.example/e3"
    }
  ],
  "previousItems": [
    {
      "id": "e1",
      "name": "Ana Silva",
      "title": "ML Engineer",
      "company": "Acme",
      "location": "São Paulo",
      "url": "https://linkedin.example/e1"
    },
    {
      "id": "e4",
      "name": "Diego Costa",
      "title": "Analyst",
      "company": "Acme",
      "location": "São Paulo",
      "url": "https://linkedin.example/e4"
    }
  ]
}

The run writes one structured report to the default Dataset and stores the same object in INTELLIGENCE_REPORT. Downstream automations can route the report by agentAction, while the current source Dataset can be preserved as the baseline for the next scheduled run.

Use cases

• Competitive intelligence
• Recruiting intelligence
• Sales triggers
• Workforce planning
• Investment research
• AI agents

A common workflow is: collect authorized public data, store it in an Apify Dataset, run this Actor with current and previous Dataset IDs, route the resulting action to a workflow or agent, and preserve the current Dataset for the next comparison.

Pricing

The product uses one primary pay-per-event unit: One decision-ready intelligence report written to the default dataset. The configured price is $0.010 per report before any Marketplace tiering or future approved changes. There is no separate start-fee design in the QuanMatrix product model.

Limitations

• Analyzes supplied public-data datasets; it does not bypass authentication or private-data controls.

• Signals are deterministic heuristics based on observed snapshot fields.

• Input field aliases are normalized conservatively.

• The Actor does not bypass authentication, private-account controls, robots restrictions, or source-platform access rules.

• Decision scores are prioritization aids based on observed fields and snapshot differences, not guarantees about future outcomes.

Output and automation

Every result contains ok, mode and agentAction, plus source counts and product-specific score fields. The output schema exposes both the default Dataset and the stored intelligence report so the Actor can be used from Tasks, schedules, API calls, agents and other Apify workflows.

Gen2 decision intelligence

This Actor preserves its original analysis and adds a decision layer with baseline awareness, regression detection, confidence, GO/WARN/BLOCK executive output, and an optional economic-impact estimate. Economic estimates are produced only when the user supplies valuePerImpactUnitUsd; the result states the calculation basis instead of inventing monetary value.