LinkedIn Company Scraper — No Login, No Cookies, Pay Per Result

Full LinkedIn company data — 41 firmographic fields per record plus optional posts, jobs, and employee demographics — in clean structured JSON. No LinkedIn login required. No cookies. No browser session. No account ban risk.

The richest LinkedIn company scraper on Apify Store. Built for B2B sales prospecting, CRM enrichment, account-based marketing (ABM), competitive intelligence, market research, and recruiting.

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How this compares to other LinkedIn company scrapers

We benchmarked the direct competitors on Apify Store. Here's the honest landscape:

	automation-lab/linkedin-company	scraperx/linkedin-company-about	bebity/linkedin-companies-profiles	This actor
Pricing model	$0.003-0.00345/co + $0.005 run fee	$19.99/month + usage	$29/month + usage	Pay-per-result, $0.005/record
Hidden subscription fee?	No, but per-run fee	✅ Yes ($240/yr)	✅ Yes ($348/yr)	❌ None
Fields per company	18	10	~10	41
Includes recent posts?	❌	❌	❌	✅ (toggleable, +23 fields per post)
Includes open jobs?	❌	❌	❌	✅ (toggleable, +13 fields per job)
Includes employee demographic breakdowns?	❌	❌	❌	✅ 7 groups: Location, School, Function, Skill, Service Category, Field of Study, Current Company
Similar/affiliated companies?	❌	❌	Partial	✅ Top 10 embedded in company record
No login / no cookies	✅	✅	❓	✅
Source code visibility	Public	Public	Public	Hidden (paid-tier protection)

Bottom line: The richest LinkedIn company scraper on Apify Store. 2-4× more data per record than competitors at a comparable per-record price — with no monthly subscription. You pay only for what you scrape.

What you get — 4 record types per company

For each input company, the actor returns:

1. company record (always — 41 fields)

• Core: id, name, universalName, linkedinUrl, description (full + preview), entityType (COMPANY / SCHOOL)
• Scale: staffCount, staffCountRange ("10,001+ employees"), followerCount
• Categorization: industriesV2[], industriesLegacy[], specialities[]
• Contact: website, callToActionUrl, callToActionType
• Founded: foundedYear, foundedMonth, foundedDay
• Location: hqCountry, hqCity, hqGeographicArea, hqLine1, hqPostalCode + full locations[] array (all worldwide offices) + locationsCount
• Brand: logoUrl (largest), coverImageUrl
• Verification: pageVerified, pageVerifiedAt, isClaimable
• Network: similarCompaniesCount + top 10 similarCompanies[] (id, name, industry, followerCount, url) + affiliatedByJobsCount + affiliatedByEmployeesCount + affiliatedByShowcasesCount
• Meta: availableTabs[], scrapedAt

2. companyPost records (optional, includePosts=true — 23 fields per post)

• Post: urn, url, header ("Microsoft reposted this"), text + textPreview, isReshare, edited
• Timestamps: postedAt (ISO), postedAtMs (Unix)
• Engagement: totalReactions, commentsCount, repostsCount, reactionBreakdown[] (per-type)
• Media: mediaContent[] (image/video URLs), mediaCount
• Author: name, url, type (COMPANY or PERSON for reshared posts)

3. companyJob records (optional, includeJobs=true — 13 fields per job)

• jobId, jobTitle, jobUrl
• jobLocation (e.g., "London, England, United Kingdom (Hybrid)")
• jobListedAt (ISO + Unix ms)
• jobVerified
• companyLogoUrl

4. companyEmployeeGroup records (optional, includeEmployees=true — 7 records per company)

Employee demographic breakdowns straight from LinkedIn's "People insights" page:

• Locations — top 15 cities/countries with employee counts
• Current company — affiliated entities
• School — top 15 universities employees attended
• Current Function — Engineering, Sales, Marketing, etc.
• Skill Explicit — top 15 skills mentioned
• Service categories — for service-based companies
• Field of Study — Computer Science, Business Admin, etc.

Each record includes totalEmployees (the company's total LinkedIn-discoverable employee count).

Top use cases

1. CRM enrichment

Drop a list of LinkedIn company URLs into your HubSpot, Salesforce, Attio, or Pipedrive workflow. Back-fill industry, headcount, HQ, founded year, specialities, website, follower count in one batch. Replaces $5,000/year Clearbit subscriptions for SMB-tier needs.

2. Account-based marketing (ABM) list building

Turn a static list of company URLs into a fully-resolved target-account universe with firmographic filters (size, industry, HQ region) ready to apply. Build ICP-filtered ABM lists in one run.

3. Competitor headcount tracking

Snapshot employee counts and follower growth at a regular cadence to chart your competitor's trajectory. Compare staff counts month-over-month — early warning for layoffs, hiring sprees, or product launches.

4. Competitor post engagement audit

Toggle includePosts=true. Pull every competitor's recent post with full engagement metrics. Compare reaction counts, comment volume, and post velocity across your competitive set.

5. Open-roles intelligence

Toggle includeJobs=true. See every open role at a target company with location, posted date, and job URL. Track hiring sprees as buying signals or sales triggers.

6. Employee demographic intelligence

Toggle includeEmployees=true. Get 7 distribution groups: where employees are located, what schools they attended, what functions they work in, what skills they list. Powerful for sales targeting, recruiting strategy, and competitor analysis.

7. Recruiting / talent market research

Combine includeEmployees=true with includeJobs=true. Map a target company's talent landscape end-to-end — current employee distribution + active openings. Build hiring competitor analyses in one run.

8. Investment due diligence

Pull firmographics + employee growth indicators + recent post momentum on potential acquisitions or investments. Public LinkedIn data fast-tracks the company-data part of your CIM build.

Quick start (3 steps)

Step 1 — Get the company URL

Open the LinkedIn company page and copy the URL — https://www.linkedin.com/company/<universal-name>/. You can also pass just the slug (e.g., microsoft) via the Company universal names field.

Step 2 — Choose your toggles

• Default: just company records (1 per input, $0.005 each)
• includePosts: true: adds N recent posts per company
• includeJobs: true: adds N open jobs per company
• includeEmployees: true: adds 7 demographic groups per company

Step 3 — Run + export

Results stream into the Dataset tab. Each record has a type field — filter to whichever subset you need. Export JSON, CSV, or Excel, or pipe to HubSpot/Salesforce/Airtable/Zapier/Make/n8n.

Input

Field	Type	Default	Description
companyUrls	array of strings	[]	LinkedIn company page URLs.
companyNames	array of strings	[]	Alternative: pass universal-name slugs directly (e.g., "microsoft").
includePosts	boolean	false	Adds recent posts as companyPost records.
maxPostsPerCompany	integer	10	Cap on posts (when enabled).
includeJobs	boolean	false	Adds open job listings as companyJob records.
maxJobsPerCompany	integer	50	Cap on jobs (when enabled).
includeEmployees	boolean	false	Adds 7 companyEmployeeGroup records per company.
proxyConfiguration	object	Apify residential	Defaults are correct.

At least one of companyUrls or companyNames is required.

Example input

{
  "companyUrls": [
    "https://www.linkedin.com/company/microsoft/",
    "https://www.linkedin.com/company/openai/"
  ],
  "includePosts": true,
  "maxPostsPerCompany": 5,
  "includeEmployees": true
}

This run returns: 2 company records + 10 companyPost records + 14 companyEmployeeGroup records = 26 records total = $0.13.

Pricing — pay only for results

$5.00 per 1,000 records. Pay-per-result.

• ✅ No subscription
• ✅ No monthly minimum
• ✅ No per-run start fee
• ✅ No charge for failed runs or unresolvable companies (clean diagnostic record)
• ✅ Apify's free tier ($5/month platform credit) covers ~1,000 records to start

No hidden costs vs competitors:

• $0.005/record flat — no per-run fee like automation-lab ($0.003-0.00345 + $0.005/run fee)
• No $20-30 monthly subscription (scraperx, bebity)
• Far more data per dollar — 41 fields vs competitors' 10-18 means 2-4× more data per $1 spent
• One transparent price for every record type (company, post, job, employee group)

Combine with other LinkedIn actors

Build a complete LinkedIn intelligence pipeline:

• Pipe similarCompanies[].url into another run to expand your target universe (network-walking)
• Pipe companyPost.postUrn into the LinkedIn Post Comments Scraper for full comment threads
• Pipe companyPost.postUrn into the LinkedIn Post Reactions Scraper for reactor lists
• Pipe jobUrl into LinkedIn jobs scrapers for full job descriptions

FAQ

Do I need a LinkedIn account?

No. This actor reads public company-page data without any LinkedIn login, cookie, or browser session.

Will my LinkedIn account get banned?

No — because we never use it. Cookie-based scrapers risk your account every run. This actor doesn't.

Why is this cheaper than other LinkedIn company scrapers?

Direct competitors charge $0.003+/company plus run fees (automation-lab), or $20-30/month subscriptions (scraperx, bebity). We negotiated a managed data partnership that gives us cookieless LinkedIn access at lower vendor cost and pass the savings through. Pure pay-per-result, no monthly fees.

Can I scrape multiple companies in one run?

Yes. Paste a list of URLs into Company URLs. The actor processes them sequentially with built-in deduplication by universal name slug.

Can I scrape personal profiles too?

No — this actor only accepts company pages (linkedin.com/company/<slug>/). For personal profile data, see the LinkedIn Profile Engagement Scraper or LinkedIn Profile Reactions Scraper from linkedintel.

What's in companyEmployeeGroup?

It's employee demographics, not a list of individual employees. Seven aggregated groups per company: Locations (where employees live), Schools (where they studied), Current Function (their job categories), Skills, Service Categories, Fields of Study, and Current Company affiliations. Each group lists top 15 items with employee counts.

What's the maximum employees / posts / jobs per company?

• Posts: up to 500 per company (controlled by maxPostsPerCompany)
• Jobs: up to 1,000 per company (controlled by maxJobsPerCompany)
• Employee groups: always 7 records per company (LinkedIn's fixed categorization)

How fast is it?

• Company only: 3-7 seconds per company
• With all toggles ON: 10-20 seconds per company (more API calls)

What if the company is private or doesn't exist?

The actor returns a clean diagnostic record and continues with the next company — never crashes mid-batch.

Can I integrate with Zapier / Make / n8n / HubSpot?

Yes — Apify integrates natively with all of them, plus Salesforce, Airtable, Google Sheets, and any webhook-compatible tool.

Can AI agents pay for and run this actor?

Yes — Agent Payments (x402 / USDC) are enabled.

Legal & compliance

• Extracts publicly available data only — no logins, no access-control bypass, no private content
• You are responsible for complying with LinkedIn's Terms of Service, GDPR (EU), CCPA (California), and other applicable laws
• Personal data returned (employee counts, names in similar-company lists) may require a lawful basis (legitimate interest, consent) before outbound use
• This actor is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation or Microsoft Corporation. "LinkedIn" is a registered trademark of LinkedIn Corporation

Changelog

v1.0.0 — 2026-05-17

• Initial release
• Cookieless architecture — zero account-ban risk
• 4 record types in one actor: company (41 fields), companyPost (23 fields), companyJob (13 fields), companyEmployeeGroup (9 fields)
• Up to 500 posts, 1,000 jobs, and 7 employee demographic groups per company
• Multi-company batch with dedup by universal name slug
• Native Apify integrations + Agent Payments (x402 / USDC)
• 13/13 tests passed across 3 tiers (correctness, toggle combinations, batch + dedup)

Support

Questions, feature requests, or bug reports? Open an issue on the actor's Issues tab. We respond within 24 hours.

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