LinkedIn Hiring Intent Monitor

Track company-level hiring intent signals for outbound, lead scoring, and recruitment intelligence workflows.

This Actor is designed for teams searching for:

• LinkedIn hiring intent monitor
• hiring signal tracker for B2B lead generation
• company hiring trend detection
• sales intelligence from hiring activity

What this MVP does

• Validates input for company URLs and/or search keywords.
• Generates deterministic hiring-intent records in mvp mode.
• Supports a live connector mode built with Crawlee RequestQueue + CheerioCrawler.
• Applies LinkedIn-specific selector parsing first, then falls back to generic text heuristics.
• Produces normalized company-level trend output for downstream integrations.

Best use cases

• Prioritize outbound account lists with hiring momentum signals.
• Enrich CRM records with hiring trend data.
• Build alerts for expansion-likelihood changes by company.
• Feed BI dashboards with normalized hiring-intent records.

Input (MVP)

• companyUrls - direct company URLs
• searchKeywords - keyword seeds
• locationKeywords - optional location filters
• maxCompanies - output cap
• maxJobsPerCompany - per-company role cap
• includeJobEnrichment - optional enriched fields
• executionMode - mvp or live
• requestDelayMs - delay between live requests
• maxRequestRetries - retry count for live fetches
• requestTimeoutMs - request timeout for live fetches
• maxConcurrency - parallel live requests
• proxyConfiguration - optional Apify proxy settings

Output (MVP)

• companySlug, companyUrl, openRoleCount, hiringSpikeScore
• roleDistribution, locationDistribution
• signals (growth/risk/opportunity)
• extractionMeta (live mode parser diagnostics)
• source, relatedToolsUrl (Discover Web Tools funnel links)

Important note

mvp mode runs as mvp-skeleton-no-live-scrape and does not fetch live pages.

live mode runs as live-connector-heuristic and fetches provided companyUrls to derive hiring signals from page text heuristics. This does not use authenticated LinkedIn scraping yet.

The actor focuses on company-level public-page signals and does not require LinkedIn login credentials.

Live run summary (OUTPUT_SUMMARY) also includes reliability metrics:

• processedUrls, failedUrls, blockedCount
• parseCoverageRate, selectorModeCount, fallbackModeCount, nonLinkedInCount

Source URL for Apify (monorepo)

Use this in Actor Source settings:

https://github.com/beydemirfurkan/discoverwebtools.com-apify-actor#main:actors/linkedin-hiring-intent-monitor

Local run

npm install
npm run start

Environment variables (for live mode)

export APIFY_TOKEN="your_apify_token"
export APIFY_PROXY_PASSWORD="your_apify_proxy_password"

Notes:

• Keep these values only in environment variables or secret stores.
• Do not commit real credentials into files.
• Local proxy usage may be limited by your Apify plan; Actor runtime on Apify platform is recommended for full proxy behavior.

Test commands

npm run test
npm run test:smoke
npm run test:live:local

MVP sample input

{
  "searchKeywords": ["ai hiring", "b2b data"],
  "locationKeywords": ["Istanbul", "Berlin"],
  "maxCompanies": 10,
  "maxJobsPerCompany": 40,
  "includeJobEnrichment": true
}

Live mode sample input

{
  "executionMode": "live",
  "companyUrls": [
    "https://www.linkedin.com/company/apify/"
  ],
  "locationKeywords": ["Berlin"],
  "maxCompanies": 1,
  "maxJobsPerCompany": 40,
  "requestDelayMs": 1200,
  "maxRequestRetries": 2,
  "requestTimeoutMs": 15000,
  "maxConcurrency": 3,
  "includeJobEnrichment": true
}

MVP sample output record

{
  "source": "https://discoverwebtools.com",
  "relatedToolsUrl": "https://discoverwebtools.com/tools?category=seo-tools",
  "sourceMode": "mvp-skeleton-no-live-scrape",
  "generatedAt": "2026-03-05T12:00:00.000Z",
  "companySlug": "seed-ai-hiring-istanbul",
  "companyUrl": null,
  "keywordSeed": "seed://ai hiring/Istanbul",
  "openRoleCount": 16,
  "hiringSpikeScore": 0.57,
  "roleDistribution": {
    "engineering": 5,
    "sales": 4,
    "marketing": 2,
    "operations": 3,
    "data": 2
  },
  "locationDistribution": {
    "primary": "Berlin",
    "remoteShare": 0.3
  },
  "signals": {
    "expansionLikelihood": "medium",
    "priorityForOutreach": "medium"
  },
  "enrichment": {
    "estimatedResponseRate": 0.12,
    "avgTimeToFillDays": 34
  }
}

Apify deploy checklist

1. Push changes to GitHub.
2. Set Actor Source URL to the monorepo path shown above.
3. Run a build.
4. Execute actor with sample input.
5. Validate dataset records and OUTPUT_SUMMARY.