LinkedIn Company Insights Extractor (Sizing + Lead Score)

🧠 What does the LinkedIn Company Insights Extractor do?

The LinkedIn Company Insights Extractor is a specialized data extraction tool that collects public information from LinkedIn company pages and enriches it with computed sizing, completeness, and lead-priority signals — returned as structured JSON (or CSV) for CRM enrichment, lead gen, competitive intelligence, and programmatic SEO. It works with slug-based URLs (e.g., /company/microsoft/).

✨ What's New

This build adds concrete, data-backed enhancements on top of the core scraping engine, plus a schema that's intentionally distinct from earlier LinkedIn company scrapers:

1. Sizing intelligence (employeeRangeMin/employeeRangeMax, companyAgeYears, websiteDomain) — the free-text size label (e.g. "10,001+ employees") is parsed into a structured numeric range, foundedYear is turned into a computed company age, and companyWebsite is reduced to its bare registrable domain — all handy for filtering, segmentation, and CRM/domain matching without re-parsing text downstream. Implemented in src/parsers.py (parse_employee_range, compute_company_age_years, extract_website_domain).
2. Data-completeness score (dataCompletenessPercent) — the percentage of key profile fields (name, description, industry, size, founded year, HQ, org type, website, tagline) that were actually populated for a given page, so low-signal rows can be filtered or flagged instead of silently mixed in with complete ones. Implemented in src/parsers.py (compute_data_completeness).
3. Lead-priority score (leadPriorityScore) — a single 0-100 number blending employee count, company age, data completeness, and web presence, so sales/BD can rank and triage scraped companies instead of eyeballing raw fields. Implemented in src/parsers.py (compute_lead_priority_score).
4. Selective section scraping — three new input toggles (includeEmployeeSamples, includeRecentPosts, includeRelatedCompanies) let you skip sections you don't need, cutting parse time and payload size on large batches. Configurable performance knobs (parallelWorkers, requestTimeoutSeconds, retryLimit) are now exposed directly in the input schema instead of being fixed internals.
5. Per-run summary — a compact SUMMARY object (companies requested/processed, success rate, average data completeness, run duration) is written to the Key-Value Store alongside the full OUTPUT array, separate from the per-company dataset rows, for a quick health check on large batches.

📦 What LinkedIn Company Page data can I extract?

Availability depends on public visibility and page completeness.

🧩 Data Group	✅ Fields Extractable (examples)
Company Basics	companyName, companyDescription, tagline, industryCategory, organizationType, foundedYear, companyAgeYears
Brand & Media	logoUrl, companyWebsite, websiteDomain
Size & Reach	reportedEmployeeCount, companySizeLabel, employeeRangeMin, employeeRangeMax
Location	hqLocation → cityName, stateRegion, countryCode; headquartersLabel
Specialties	specialtyTags[] keywords for SEO and targeting
People (Preview)	employeeSamples[] (limited public sample): fullName, jobTitle, profileUrl, photoUrl
Updates / Posts	recentPosts[]: postText, publishedAt, postUrl
Network Data	relatedCompanies[]
Computed Signals	dataCompletenessPercent, leadPriorityScore, scrapedAtIso

🔧 Key Features

• Clean JSON Output: Normalized, distinctly-named fields ready for Salesforce/HubSpot, data warehouses, or Google Sheets.
• Sizing Intelligence: Structured employee ranges, company age, and website domain computed for you.
• Lead-Priority Scoring: A 0-100 blended score for fast triage of large batches.
• Selective Scraping: Toggle employee samples, posts, and related companies on/off to control cost and speed.
• Scalable Batching: Process hundreds to thousands of company URLs via a Request Queue with configurable parallel workers.
• Rate Awareness: Configurable timeout/retry limits, proxy support with automatic Residential fallback on blocks.
• Error Handling: Clear logs, per-row errorMessage, and a run-level SUMMARY in the Key-Value Store.

🏁 How to use the LinkedIn Company Insights Extractor

1. Log in to Apify – Create a free account or sign in to your existing one.
2. Select the Actor – Search for "LinkedIn Company Insights Extractor" in the Apify Store.
3. Enter Input Data – Paste one or multiple LinkedIn company page URLs into the companyUrls field.
4. Choose Options – Toggle includeEmployeeSamples, includeRecentPosts, includeRelatedCompanies, and set parallelWorkers / requestTimeoutSeconds / retryLimit to match your run. Optionally configure proxyConfig.
5. Run the Actor – Hit Start, and the scraper will automatically fetch the company details.
6. Download Results – Export your results in JSON, CSV, Excel, or XML format—ready for use in CRMs, analytics, or SEO workflows. Check the Key-Value Store for the OUTPUT array and the SUMMARY run report.

🎯 Use Cases (Real-World Wins)

• Sales & SDR 💼: Use leadPriorityScore and sizing fields to rank accounts before outreach.
• Recruiting 🧑‍💻: Validate headcounts, locations, and recent posts to tailor pitches.
• Competitive Intel 🕵️: Track taglines, repositioning, and related companies.
• Content & SEO 🧠: Build programmatic pages using industries, locations, and specialties.
• Partnerships & BD 🤝: Confirm company type, founded year, HQ, and company age for due diligence.
• Market Research 📊: Aggregate dataCompletenessPercent and sizing fields across categories and regions.
• Ops & RevOps ⚙️: Keep CRM records consistent with clean, distinctly-named JSON mappings.

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🏆 Why choose us?

• Compliance-first defaults: Public mode only; configurable throttling to reduce impact.
• Enriched, analytics-ready JSON: Computed sizing, completeness, and lead-priority fields on top of clean structured data.
• Cost control: Selective section scraping keeps large batches fast and cheap.
• Scale without chaos: From 1 → 100k URLs via queues, configurable parallel workers, and retries.
• Transparent telemetry: Per-row errorMessage plus a run-level SUMMARY report.

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📈 How many results can you scrape?

• Company profiles: Scales to thousands per run with proper throttling.
• Employees (public preview): Typically 3–4 public profiles visible without login (varies by page); skip with includeEmployeeSamples: false.
• Posts/Updates: Sample surfaced in the page's structured data; skip with includeRecentPosts: false.
• Related Companies: Returned when visible and public; skip with includeRelatedCompanies: false.

⚖️ Is it legal to scrape LinkedIn?

• Short answer: It depends on your jurisdiction, purpose, data type, access method, and LinkedIn's Terms of Service.
• Best Practices ✅
• Collect publicly available data only; do not defeat access controls.
• Respect ToS, robots, rate limits, and privacy laws (e.g., GDPR/CCPA).
• Provide opt-out/data deletion paths where applicable.
• Use data for legitimate, ethical purposes (analytics, research, enrichment).

🛡️ This guide is not legal advice. Consult counsel for use-case specific guidance.

🧪 Input

{
    "companyUrls": [
        "https://www.linkedin.com/company/netflix/"
    ],
    "includeEmployeeSamples": true,
    "includeRecentPosts": true,
    "includeRelatedCompanies": true,
    "parallelWorkers": 3,
    "requestTimeoutSeconds": 30,
    "retryLimit": 3
}

📤 Output Format

[
  {
    "requestedUrl": "https://www.linkedin.com/company/netflix/",
    "scrapeSuccess": true,
    "companyName": "Netflix",
    "companyDescription": "Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages.",
    "hqLocation": {
      "cityName": "Los Gatos",
      "stateRegion": "CA",
      "countryCode": "US"
    },
    "reportedEmployeeCount": 17554,
    "companyWebsite": "https://jobs.netflix.com?utm_campaign=LIHomePage&utm_source=linkedin",
    "websiteDomain": "jobs.netflix.com",
    "logoUrl": "https://media.licdn.com/dms/image/v2/D4E0BAQGMva5_E8pUjw/company-logo_200_200/company-logo_200_200/0/1736276678240/netflix_logo?e=2147483647&v=beta&t=-84GbYZIgL-lNtKMkXAk-OE1L6VJVMfBSLJRG8FLkVY",
    "tagline": "Play, pause, and resume watching anytime and anywhere. ",
    "industryCategory": "Entertainment Providers",
    "companySizeLabel": "10,001+ employees",
    "employeeRangeMin": 10001,
    "employeeRangeMax": null,
    "foundedYear": 1997,
    "companyAgeYears": 29,
    "headquartersLabel": "Los Gatos, CA",
    "organizationType": "Public Company",
    "specialtyTags": [
      "Revolutionizing the way people watch TV shows and movies!"
    ],
    "relatedCompanies": [
      {
        "profileUrl": "https://se.linkedin.com/company/spotify?trk=similar-pages",
        "companyName": "Spotify"
      },
      {
        "profileUrl": "https://www.linkedin.com/company/google?trk=similar-pages",
        "companyName": "Google"
      }
    ],
    "employeeSamples": [
      {
        "profileUrl": "https://www.linkedin.com/in/aaronhipple?trk=org-employees",
        "fullName": "Aaron Hipple",
        "jobTitle": "Audio Software Engineer",
        "photoUrl": "https://media.licdn.com/dms/image/v2/C4E03AQH_rhYlmsE33Q/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1516155809223?e=2147483647&v=beta&t=AOI83o_TV-HDY0dY3mTP9cgUFihsic0NL5HdYEE3VOw"
      }
    ],
    "recentPosts": [
      {
        "postUrl": "https://www.linkedin.com/posts/netflix_venicefilmfestival-dreamteam-activity-7376631561569484801-JgLk",
        "publishedAt": "2025-09-24T15:00:15.442Z",
        "postText": "At the Venice Film Festival 2025, we proudly showcased 4 World Premieres..."
      }
    ],
    "dataCompletenessPercent": 100.0,
    "leadPriorityScore": 94.5,
    "scrapedAtIso": "2026-08-17T12:00:00Z",
    "errorMessage": ""
  }
]

Note: employeeRangeMax is null for open-ended size labels like "10,001+ employees". leadPriorityScore blends reportedEmployeeCount (capped contribution), companyAgeYears, dataCompletenessPercent, and website presence into a single 0-100 ranking number — it is a heuristic for triage, not a certified valuation.

💬 FAQ

1) Is there a free version?

➡️ Many tools offer free tiers or trial credits with limits on URLs. Always review terms and data usage policies.

2) How is leadPriorityScore calculated?

➡️ min(employeeCount / 250, 40) + min(companyAgeYears * 0.5, 20) + dataCompletenessPercent * 0.3 + (10 if website present), capped at 100. It's a relative ranking heuristic, not a guarantee of lead quality.

3) Can I skip employees, posts, or related companies to save time?

➡️ Yes — set includeEmployeeSamples, includeRecentPosts, or includeRelatedCompanies to false in the input.

4) Does this support Sales Navigator or Recruiter?

➡️ Use extreme caution. Accessing Sales Navigator or Recruiter data may raise legal/ToS risks. Prefer public data and consult legal counsel.

5) Can I download results as CSV?

➡️ Yes. Most scrapers provide CSV and JSON export options directly from the Apify dataset.

6) Where do I find the run summary?

➡️ In the Key-Value Store under the SUMMARY key, alongside the full results array under OUTPUT.

🔗 What are other LinkedIn scraping tools?

LinkedIn Ads Scraper	LinkedIn Search Jobs Scraper
LinkedIn Company Employees Scraper	LinkedIn Post Scraper
LinkedIn Company About Scraper	LinkedIn Profile Scraper [Cheapest + Fastest]