LinkedIn Company Scraper: Size, Industry, Website, and Followers Without Login

LinkedIn company pages expose a consistent set of firmographic data without requiring login. Our LinkedIn Company Scraper loads each company page through a residential proxy, extracts the publicly visible fields, and returns structured JSON.

What you get per company

• name: company name
• tagline: company tagline
• industry: industry label (e.g. “Software Development”)
• company_size: employee count range (e.g. “1,001-5,000 employees”)
• headquarters: HQ city and country
• founded: founding year
• website: company website URL
• followers: LinkedIn follower count
• about: about/description text
• specialties: array of specialty strings
• company_url: canonical LinkedIn company URL
• scraped_at: ISO timestamp

Python example

import requests, time

run = requests.post(
    "https://api.apify.com/v2/acts/themineworks~linkedin-company-details/runs",
    headers={"Authorization": f"Bearer {APIFY_TOKEN}"},
    json={
        "companyUrls": [
            "https://www.linkedin.com/company/stripe",
            "https://www.linkedin.com/company/notion",
            "https://www.linkedin.com/company/figma"
        ]
    }
)

run_id = run.json()["data"]["id"]

while True:
    r = requests.get(
        f"https://api.apify.com/v2/actor-runs/{run_id}",
        headers={"Authorization": f"Bearer {APIFY_TOKEN}"}
    ).json()
    if r["data"]["status"] in ("SUCCEEDED", "FAILED"):
        break
    time.sleep(5)

companies = requests.get(
    f"https://api.apify.com/v2/actor-runs/{run_id}/dataset/items",
    headers={"Authorization": f"Bearer {APIFY_TOKEN}"}
).json()

for c in companies:
    print(c["name"], c["company_size"], c["industry"])
    print(f"  {c['headquarters']} | Founded {c['founded']}")
    print(f"  {c['website']}")

Enrich a lead list

import pandas as pd

df = pd.read_csv("accounts.csv")  # must have a 'linkedin_url' column

urls = df["linkedin_url"].dropna().tolist()

run = requests.post(
    "https://api.apify.com/v2/acts/themineworks~linkedin-company-details/runs",
    headers={"Authorization": f"Bearer {APIFY_TOKEN}"},
    json={"companyUrls": urls}
)
# ... poll and fetch as above, then merge on linkedin_url

ICP filtering example

icp_companies = [
    c for c in companies
    if "Software" in c.get("industry", "")
    and c.get("company_size", "").startswith(("201", "501", "1,001"))
    and c.get("headquarters", "").endswith("United States")
]

print(f"{len(icp_companies)} companies match ICP")

Use cases

Account-based marketing. Enrich a list of target accounts with firmographic data before building audiences or personalizing outreach.

Market research. Map industry composition, company size distribution, and geographic concentration across a defined sector.

Lead scoring. Add employee count and founding year to your scoring model to weight accounts by fit.

Sales territory planning. Filter a database of prospects by HQ location, size, and industry to carve territories or define segments.

Pricing

$0.004 per company. Private or inaccessible company pages are not charged.

Available on Apify.