🔗 LinkedIn Company URL Finder Scraper

🚀 Export the LinkedIn company page of any domain in seconds. Paste company websites, get one row per company with the LinkedIn company URL, a 0 to 100 confidence score, the evidence behind it and the company's other social links. 20 fields per row, and the Actor never opens LinkedIn.

LinkedIn Company URL Finder turns a list of company domains (or names) into their LinkedIn company page URLs without touching LinkedIn. It reads the company's own website first, because a company's footer or structured data is the most reliable place to find its LinkedIn link. When the site does not publish one, it checks Wikidata and public search results, and it scores every match so you can see how sure it is.

Each row carries 20 fields. In our accuracy test on 55 real domains (49 companies of every size from 12 countries plus 6 sites with no company page), with the default settings (company site, Wikidata and Bing) the Actor returned the right LinkedIn page for 36 of the 49 companies (74%) at 97% precision. With Google switched on it found 42 of 49 (86%) at 98% precision. It returned nothing for all 6 non-company sites. Everything below is measured, including where it fails.

🎯 Target Audience	💡 Primary Use Cases
Sales and RevOps teams, lead-gen agencies, recruiters, growth marketers, data and CRM teams	Filling the LinkedIn URL column of a CRM or Clay table, account enrichment, ABM lists, recruiting research, competitor tracking

📋 What the LinkedIn Company URL Finder Scraper does

• 🌐 Domain in, LinkedIn URL out. Accepts stripe.com, https://www.notion.so/product or an email address like ana@acme.com.
• 🏢 Company names too. A line without a dot is treated as a name and searched. Name-only matches cannot be checked against a website, so their confidence never goes above medium.
• 🧾 Reads the company site first. Structured data (sameAs), footer and header links, and links hidden in page scripts. Links from sites that redirect (notion.so to notion.com) are followed safely.
• 📚 Wikidata as a second source. Many well-known companies have their LinkedIn ID stored against their official website.
• 🔎 Search as a fallback. Bing by default. Google through the Apify Google SERP pool is optional (Use Google as the last resort): it finds more companies but is slower. All search can be switched off.
• 🎯 Every match is scored. A 0 to 100 score, a high / medium / low label, the method, and a list of reasons in plain words.
• ↔️ Alternatives. Up to 4 other candidate pages with their scores, so a doubtful row is easy to review.
• 🔗 Social links as a bonus. Facebook, Instagram, X and YouTube links found on the same website, at no extra cost.
• 🛑 Never opens LinkedIn. No login, no cookies, no LinkedIn requests at all, so LinkedIn's blocks cannot break it.
• 🚦 Honest about misses. A company with no page found is reported as not_found and is not charged.

💡 Why it matters: the LinkedIn URL is the key that unlocks company data, people search and outreach. A wrong URL is worse than a missing one, so every row says how it was found and how sure the Actor is.

🎬 Full Demo (🚧 Coming soon)

📊 Output

One row per input. Values the source withholds read Not Disclosed, fields that do not apply read N/A, and empty lists are [].

Field	Description
🖼 imageUrl	Company logo or social image read from the website, N/A when the site could not be read
📥 input	The domain or name exactly as you supplied it
🌐 domain	Normalized company domain (N/A for name-only lookups)
🔗 linkedinUrl	Canonical URL, https://www.linkedin.com/company/<slug>, N/A when not found
🔤 linkedinSlug	The company identifier at the end of the URL
🏢 companyName	Name from the LinkedIn search result title when seen, otherwise from the website
🚦 status	found, not_found or error
🎯 confidence	high (80+), medium (55 to 79), low (30 to 54) or none
💯 confidenceScore	0 to 100
🧭 method	Where the match came from, joined with +: site-structured-data, site-link, site-source, wikidata, search-bing, search-duckduckgo, search-google
✅ verifiedBySite	Yes when the company website itself links to this page
🧾 matchReasons	The evidence behind the score, one short sentence each
↔️ alternatives	Other candidates with linkedinUrl, linkedinSlug, companyName, score, source
🏠 website	The page that was read on the company website
📘 facebookUrl	Facebook page linked from the website
📸 instagramUrl	Instagram profile linked from the website
🐦 twitterUrl	X (Twitter) profile linked from the website
▶️ youtubeUrl	YouTube channel linked from the website
🕒 scrapedAt	Collection time (ISO 8601)
❌ error	null unless the company could not be checked

Three real rows from a cloud run (the third one needed Google, which is optional):

[
  {
    "imageUrl": "https://dam-cdn.atl.orangelogic.com/AssetLink/5140xb7orvf7timubceisv3470t0305a.webp",
    "input": "atlassian.com",
    "domain": "atlassian.com",
    "linkedinUrl": "https://www.linkedin.com/company/atlassian",
    "linkedinSlug": "atlassian",
    "companyName": "Atlassian",
    "status": "found",
    "confidence": "high",
    "confidenceScore": 100,
    "method": "site-source+wikidata",
    "verifiedBySite": "Yes",
    "matchReasons": [
      "LinkedIn URL found in the company website source",
      "only LinkedIn company link on the site",
      "Wikidata lists this LinkedIn ID for the company website",
      "LinkedIn slug matches the company name"
    ],
    "alternatives": [],
    "website": "https://www.atlassian.com/",
    "facebookUrl": "N/A",
    "instagramUrl": "N/A",
    "twitterUrl": "N/A",
    "youtubeUrl": "N/A",
    "scrapedAt": "2026-09-29T04:35:04.125Z",
    "error": null
  },
  {
    "imageUrl": "https://images.ctfassets.net/ct4bxoykjwgb/62APtIxMy9L1S8YnUi00Lm/2f6e3f8ccbe2d3cbb1b633895176968a/salesforce-logo.jpg",
    "input": "salesforce.com",
    "domain": "salesforce.com",
    "linkedinUrl": "https://www.linkedin.com/company/salesforce",
    "linkedinSlug": "salesforce",
    "companyName": "Salesforce",
    "status": "found",
    "confidence": "high",
    "confidenceScore": 88,
    "method": "wikidata",
    "verifiedBySite": "No",
    "matchReasons": [
      "Wikidata lists this LinkedIn ID for the company website",
      "LinkedIn slug matches the company name"
    ],
    "alternatives": [],
    "website": "https://www.salesforce.com/",
    "facebookUrl": "N/A",
    "instagramUrl": "N/A",
    "twitterUrl": "N/A",
    "youtubeUrl": "N/A",
    "scrapedAt": "2026-09-29T04:35:03.902Z",
    "error": null
  },
  {
    "imageUrl": "https://s.pinimg.com/images/facebook_share_image.png",
    "input": "pinterest.com",
    "domain": "pinterest.com",
    "linkedinUrl": "https://www.linkedin.com/company/pinterest",
    "linkedinSlug": "pinterest",
    "companyName": "Pinterest",
    "status": "found",
    "confidence": "medium",
    "confidenceScore": 57,
    "method": "search-google",
    "verifiedBySite": "No",
    "matchReasons": [
      "LinkedIn slug matches the company name",
      "search result title matches the company name",
      "first search result"
    ],
    "alternatives": [],
    "website": "https://www.pinterest.com/",
    "facebookUrl": "N/A",
    "instagramUrl": "N/A",
    "twitterUrl": "N/A",
    "youtubeUrl": "N/A",
    "scrapedAt": "2026-09-29T04:38:44.649Z",
    "error": null
  }
]

✨ Why choose this Actor

• 🛡 It never touches LinkedIn. Finders that check every candidate on LinkedIn itself inherit LinkedIn's blocks and captchas. This one only reads the company's website, Wikidata and search results.
• 📈 A score you can act on. In our test, high-confidence rows were right 36 times out of 37, and medium-confidence rows 6 out of 6 (a small sample). The default keeps medium and above, because the low band (30 to 54) was right only about one time in five.
• 🔍 The evidence is in the row. method, verifiedBySite, matchReasons and alternatives show why a URL was chosen, so reviewing is fast.
• 🧠 Careful about look-alikes. Names that merely contain your brand (a haberdashery called "Nellie Notions" for Notion) are scored down, and two near-equal candidates lower each other's score.
• 🔗 Chains with other Actors. linkedinUrl goes into LinkedIn Company Profiles Scraper (input Company URLs) or LinkedIn Posts Scraper (input startUrls, which accepts company pages), and website goes into Contact Info Scraper (input startUrls).
• 🛑 Fails loudly. A run where nothing could be checked ends as FAILED with the reason, never as a green run with an empty table.
• ⚡ Light and fast. Plain HTTP, no browser: a domain whose site answers takes 1 to 4 seconds. With Google switched on, the 55-domain test took about 6 minutes on 512 MB, because about a third of the domains ended up needing a search engine and some Google requests must be retried.

📈 How it compares to alternatives

	This Actor	Typical LinkedIn URL finders
Opens LinkedIn to validate	❌ Never	Some do, and break when LinkedIn blocks them
Reads the company website	✅ Structured data, footer, page source	Varies
Confidence score and evidence per row	✅ 0 to 100, reasons, alternatives	Varies
Alternatives for doubtful rows	✅ Up to 4	Varies
Company names as input	✅ Capped at medium confidence	Varies
Other social links from the same site	✅	Varies
Unbilled misses	✅ not_found and error rows are free	Varies
Employee count, industry, headquarters	❌ Only LinkedIn itself has them	Some, by reading LinkedIn itself

Honest ceilings, all measured:

• Recall depends on the company site. 36 of 49 companies (74%) were resolved from the site and Wikidata alone. The other 13 needed a search engine, and Google (optional) resolved 6 more. Bing returned a usable LinkedIn page for only 1 of 19 requests, so treat it as a bonus.
• Google is not consistent, which is why it is off by default. Many Google requests return no usable page (cookie wall, script-only page or timeout): in one run 76 requests were sent and 45 were billed as search results. The Actor retries, but two runs of the same 55 domains each found 42 correct companies and differed on 3 (Spotify, Globant and Linear in one run; DoorDash, Pinterest and Jumia in the other). Run again to fill gaps.
• Parent and acquired brands. If a site links to its parent, that is what you get. hotjar.com links to Contentsquare, and typeform.com links to pages other than the one Google ranks first. The row says verifiedBySite: Yes, which means the site links to it, not that it is the brand's own page.
• Name collisions. A personal or small site whose name matches a company (stallman.org and a company called Stallman) can score low-band matches. The default minimum confidence hides them.
• Names without a website. Capped at medium because nothing can be checked against the company's site.
• No firmographics. Employee count, industry, headquarters and follower count exist only on LinkedIn, which this Actor never opens.

🚀 How to use

1. Create a free Apify account with $5 of credit: sign up here.
2. Open LinkedIn Company URL Finder and paste your domains (or company names) into Domains or company names, one per line.
3. Set Max Items, and choose the Minimum confidence you want to keep. Switch on Use Google as the last resort to find more companies at the cost of a slower run, or turn off search engines if you only want what the company sites publish.
4. Click Start and download the dataset as CSV, Excel, JSON or XML.

Example:

{ "companies": ["stripe.com", "https://www.notion.so", "ana@acme.com", "Acme Rockets"], "maxItems": 100, "minConfidence": "medium" }

💼 Business use cases

📇 CRM and Clay enrichment

Fill the LinkedIn URL column for thousands of accounts. Route high rows straight to enrichment and send medium and not_found rows to review.

🎯 Account-based marketing

Turn a list of target domains into LinkedIn company pages for ad audiences, outreach sequences and account research.

🧑‍💼 Recruiting and talent research

Find the company page of every employer on a target list, then feed the URLs to the LinkedIn Jobs, Posts or Company Profiles Actors.

🕵️ Competitor and market mapping

Map a market from a list of company websites and keep the alternatives column to spot subsidiaries and regional pages.

🔌 Automating LinkedIn Company URL Finder Scraper

• Make and Zapier: run it when a new company lands in your CRM and write the URL back.
• Slack: post rows that need review (medium, low) into a team channel.
• Airbyte: sync the dataset into BigQuery, Snowflake or Postgres.
• GitHub Actions: trigger runs from your data pipeline through the Apify API.
• Google Drive: save each run's CSV or Excel export to a shared folder.

🌟 Beyond business use cases

• 🎓 Research: link company registries or funding lists to their LinkedIn presence.
• 🙋 Personal: tidy the company links in a job-search spreadsheet.
• 🤝 Non-profit: find the LinkedIn pages of partner organizations and grantees.
• 🧪 Experimentation: build labelled domain-to-page datasets to test your own matching models.

🤖 Ask an AI assistant about this scraper

Paste this page into ChatGPT, Claude or Gemini and ask things like "How should I treat medium confidence rows?" or "Which fields tell me the company website itself confirmed the match?".

❓ Frequently Asked Questions

🔑 Do I need a LinkedIn account?

No. The Actor never opens LinkedIn. It reads the company's website and publicly available search results.

🧭 How does it find the page without LinkedIn?

In order: the company website (structured data, footer and header links, page source), Wikidata, Bing (DuckDuckGo if Bing is unreachable), and, only if you switch it on, Google through the Apify Google SERP pool. It stops as soon as the evidence is strong enough, so most rows never touch a search engine.

💯 What does the confidence score mean?

The score adds up evidence and is capped at 100.

• The company website. A LinkedIn link in the site's structured data (sameAs) is worth 70 points, a footer or header link 62, another link 58, and a link found only in the page source 48. It adds 8 more when it is the only LinkedIn company link on the site.
• Wikidata. Listing that page for the company's official website adds 68.
• The name. The slug matching the company name adds up to 20. A site link whose slug does not resemble the site name loses 15, because it may be a parent or a partner.
• Search results. A result found only through search starts at 14. The LinkedIn snippet listing the company website adds 35 (12 if the domain is only mentioned in passing), a title matching the name up to 15, first place 8, two engines 8, two queries 4.
• Doubt. Two near-equal candidates cost the leader 10. Name-only lookups are capped at 79.

High is 80 and above, medium 55 to 79, low 30 to 54, and anything under 30 is not reported as a match.

🏷 Why is my name-only lookup never high?

Without a website to check, a common name can belong to several companies. Name-only scores are capped at 79 so nothing unverified is labelled high.

⚠️ How accurate is it?

We tested 55 real domains on Apify: 49 companies (32 large, 10 mid-size, 7 small, from 12 countries: US, Sweden, Australia, UK, Germany, Spain, Argentina, Brazil, India, Singapore, the Netherlands, Nigeria) and 6 sites with no company page (personal sites and a reserved example domain). The expected LinkedIn slug for each company was written from memory before the runs, then checked. Each row below comes from a real cloud run with Google switched on. The first row is what the default settings give: it keeps only the rows of that run that did not need a search engine, which is a lower bound because Bing can add a few.

	Precision	Recall
Default settings (site, Wikidata, Bing), corrected labels	97.3% (36 of 37)	73.5% (36 of 49)
Google on, expected slugs exactly as first written	88.4% (38 of 43 returned)	77.6% (38 of 49)
Google on, after correcting 4 expected slugs with independent evidence	97.7% (42 of 43)	85.7% (42 of 49)

The 4 corrections: Twilio (twilio-inc-), Booking.com (booking.com) and Mixpanel (mixpanel-inc-) are the real slugs, confirmed by the top Google result and by the company site, and Jumia has two plausible pages (jumia and jumia-group), so either counts. The one wrong high-confidence answer is Typeform. The set was also used while building the Actor (Wikidata and the reserved-domain rule were added after seeing misses), so it is a development benchmark, not a blind test. The test set, the raw results and the scoring script are in the repository (tests/accuracy).

🙈 Why did a company come back as not found?

Its website hides the LinkedIn link (many sites build their footer with JavaScript), Wikidata does not know it, and Bing returned nothing usable. Switching on Use Google as the last resort and re-running the misses usually finds several of them. The alternatives column still lists weaker candidates, and lowering Minimum confidence keeps them as matches.

🔤 Why does a slug end with a hyphen or a number?

Because that is the real LinkedIn address. Twilio's page is twilio-inc- and Mixpanel's is mixpanel-inc-. The Actor reports exactly what the company links to.

🌍 Does it work outside the US?

Yes. The test set includes companies from 12 countries, and LinkedIn country subdomains (ie.linkedin.com) are normalized to the plain www.linkedin.com/company/<slug> form. Search requests use the English US results page, so very small local companies with no website link are the hardest case.

💸 Am I charged for rows that are not found?

No. Only rows with status found are charged. not_found and error rows are delivered free.

🔒 Is it safe to paste internal or private addresses?

The Actor only fetches public websites. Addresses that point to private networks, localhost or link-local ranges are refused, including after redirects.

⏱ How fast is it?

A domain whose company site answers takes 1 to 4 seconds. Domains that need Google take longer because some Google requests must be retried: the 55-domain accuracy test ran for about 6 minutes on 512 MB with 5 companies in flight.

🧾 Can I keep only strong matches?

Yes. Minimum confidence defaults to medium. Set it to high to keep only strongly verified matches. Weaker matches are reported as not found and still appear in alternatives.

🔌 Integrate with any app

Connect the dataset to Make, Zapier, n8n, Google Sheets, Airtable, HubSpot or your own code through the Apify API, webhooks and integrations.

🔗 Recommended Actors

• LinkedIn Company Profiles Scraper: paste the linkedinUrl column into Company URLs to read the company pages.
• LinkedIn Posts Scraper: the same URLs work as startUrls to collect a company's posts.
• Contact Info Scraper: the website column goes into startUrls to collect emails, phones and addresses.

💡 Pro Tip: browse the complete ParseForge collection for more B2B data Actors.

🆘 Need Help? Open our contact form and we will get back to you.

⚠️ Disclaimer: this is an independent tool, not affiliated with LinkedIn or any company it looks up. It reads only publicly available data: company websites, Wikidata and search-engine results.