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Extract public LinkedIn company profiles at scale — name, about, industry, size, HQ, specialties, followers, funding, and logos from a company slug, URL, or URN. No cookie required. $1.20 per 1,000 companies.
Extract public LinkedIn company profiles at scale — name, about, industry, size, HQ, specialties, followers, funding, and logos from a company slug, URL, or URN. No cookie required. $1.20 per 1,000 companies.
Fast company enrichment for outbound sales and market maps — consistent JSON rows without maintaining your own parsers.
On Scrapy.io, LinkedIn Company Details Scraper (No Cookie) by Data Doping is built for scraping linkedin data workflows — run from the Store, schedule recurring jobs, or POST to datadoping.p.scrapy.io from your stack.
/company/ URLs in companiesLinkedIn is the system of record for B2B identity — profiles, company updates, and post feeds that power ABM and competitive intelligence. A scraping linkedin data pipeline on Scrapy.io converts public URLs into structured JSON without maintaining cookie-based browser farms.
LinkedIn Company Business Data Scraper is built for API-first batch jobs with caps you control. Schedule runs, call datadoping.p.scrapy.io, or chain Data Doping LinkedIn tools on the same Scrapy.io billing account.
This scraping linkedin data on Scrapy.io exports structured fields including:
For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.
Teams discover LinkedIn Company Business Data Scraper while researching scraping linkedin data and related terms such as data scraper linkedin, scraping linkedin, scrape linkedin, linkedin scraping. This listing is structured to answer common questions — including — with concrete Input and Output examples you can run on Scrapy.io without maintaining your own scraper infrastructure.
If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.
Use this checklist before your first production run of LinkedIn Company Business Data Scraper:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetdatadoping.p.scrapy.io/linkedin-company-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for LinkedIn Company Business Data Scraper so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Provide LinkedIn company slugs, numeric URNs, or full linkedin.com/company/... URLs in companies.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"companies": [
"google"
]
}| Field | Type | Required | Description |
|---|---|---|---|
companies | string[] | Yes | List of LinkedIn company identifiers, URNs, or company URLs to scrape. Enter one identifier/URL per line. URLs will be automatically converted to identifiers. Also accepted: company (Single company alias); or input (Single company alias). |
Results appear in the Scrapy.io run Output tab. Companies and Errors tables in the run output.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
{
"name": "Example Co",
"tagline": "Building the future",
"industry": "Software Development",
"company_size": "201-500 employees",
"headquarters": "San Francisco, CA",
"followers": 125000,
"company_url": "https://www.linkedin.com/company/example-co/"
}Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.
enrich account lists with firmographics
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
build competitor landscapes by vertical
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
track funding signals on target companies
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
hydrate account objects from LinkedIn URLs
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
~1 company per second with automatic backoff and per-row errors — built for API batches, not browser tabs. Prefer Data Doping when company cards must refresh on a schedule.
LinkedIn Company Business Data Scraper is rarely the only step in a data workflow. Teams typically:
See Related Data Doping tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.
Most production deployments follow the same shape:
postUrl, placeId, videoId, reviewId, …) plus scrape date where history mattersLinkedIn Company Business Data Scraper separates successful rows from per-input errors, so staging logic can WHERE type != 'error' (or the equivalent filter for your tool) without failing the whole batch. Join across Data Doping tools on those stable keys to build multi-step datasets without re-scraping upstream steps.
Maintaining Facebook, LinkedIn, Instagram, or X extractors in-house means handling rate limits, HTML or API changes, proxy rotation, and observability — work that rarely differentiates your product. LinkedIn Company Business Data Scraper on Scrapy.io outsources that operational burden: you supply inputs, Scrapy.io runs the job, and you pay per successful row.
Data Doping listings add API-first, warehouse-ready documentation (clear caps, field lists, and pipeline patterns) so data teams can onboard without reading executor source code. When requirements change, update the input JSON or schedule — not your scraper fleet.
LinkedIn Company Business Data Scraper runs on Scrapy.io support multiple ways to get data out:
For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.
Run LinkedIn Company Business Data Scraper once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:
datadoping.p.scrapy.io on a queueData Doping tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, max_posts, max_comments, or equivalent limits in the input form.
curl -X POST "https://datadoping.p.scrapy.io/linkedin-company-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"companies": ["google", "https://linkedin.com/company/example-company"]
}'Bulk runs via the scraper endpoint:
curl -X POST "https://datadoping.p.scrapy.io/linkedin-company-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"companies": ["google", "https://linkedin.com/company/example-company"]
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
LinkedIn Company Business Data Scraper is available through the Scrapy.io MCP server — configure your API key in Cursor, Claude Desktop, or another MCP client, then invoke the tool from agent workflows. This is useful for ad-hoc research ("scrape these ten URLs and summarize the Output") without writing boilerplate HTTP code.
For production, prefer the publisher API or scheduled runs; use MCP for exploratory analysis and internal tooling where a human or agent supplies inputs interactively. See the API tab on LinkedIn Company Business Data Scraper for MCP connection snippets.
| Tool | Best for |
|---|---|
| LinkedIn Profile Lead Scraper | Data Doping companion tool — overview |
| Instagram Profile Bulk Extractor | Data Doping companion tool — overview |
| X Profile Insights Extractor | Data Doping companion tool — overview |
Batch company identifiers in API jobs — ~1 company per second typical throughput
Per-row errors isolate bad slugs without failing the batch
Store company_url as the stable warehouse key
Inspect per-row errors in the Errors output view instead of failing an entire batch
Facebook-heavy runs failing in a pattern? Use Issues on this Data Doping listing and attach your run ID plus one post, page, or search query
LinkedIn Company Business Data Scraper collects publicly available data only. You are responsible for complying with platform terms, applicable laws, and data-protection regulations (including GDPR when personal data is involved). Consult your legal team for your specific use case.
$3.00 per 1,000 companies — billed per successful row on Scrapy.io. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.
Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.
Yes. POST to https://datadoping.p.scrapy.io/linkedin-company-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.
Yes. Configure the Scrapy.io MCP endpoint with your API key to query LinkedIn Company Business Data Scraper from AI assistants and agent workflows.
Data Doping focuses on Meta and social discovery workflows — leave a Reviews note if this actor saved you from browser scraping and which Facebook surface you use daily.
Fast company enrichment for outbound sales and market maps — consistent JSON rows without maintaining your own parsers.
On Scrapy.io, LinkedIn Company Details Scraper (No Cookie) by Data Doping is built for scraping linkedin data workflows — run from the Store, schedule recurring jobs, or POST to datadoping.p.scrapy.io from your stack.
/company/ URLs in companiesLinkedIn is the system of record for B2B identity — profiles, company updates, and post feeds that power ABM and competitive intelligence. A scraping linkedin data pipeline on Scrapy.io converts public URLs into structured JSON without maintaining cookie-based browser farms.
LinkedIn Company Business Data Scraper is built for API-first batch jobs with caps you control. Schedule runs, call datadoping.p.scrapy.io, or chain Data Doping LinkedIn tools on the same Scrapy.io billing account.
This scraping linkedin data on Scrapy.io exports structured fields including:
For your first run, keep caps low (maxResults, maxReviews, etc.) until you validate row shape in the Output preview.
Teams discover LinkedIn Company Business Data Scraper while researching scraping linkedin data and related terms such as data scraper linkedin, scraping linkedin, scrape linkedin, linkedin scraping. This listing is structured to answer common questions — including — with concrete Input and Output examples you can run on Scrapy.io without maintaining your own scraper infrastructure.
If you arrived from SEO or paid search, start with the Input JSON example below, run once on the free tier, then scale with schedules or the publisher API once row shape and cost look right.
Use this checklist before your first production run of LinkedIn Company Business Data Scraper:
maxResults, maxReviews, or equivalent limits so a full batch stays within budgetdatadoping.p.scrapy.io/linkedin-company-scraper/v1/api or create a scheduled jobMost teams keep a "golden" input file in git for LinkedIn Company Business Data Scraper so staging and production use identical payloads. Update that file when you add keywords, targets, or communities — not the orchestration code around it.
Provide LinkedIn company slugs, numeric URNs, or full linkedin.com/company/... URLs in companies.
Configure the run in the Scrapy.io input form or pass JSON to the publisher API.
{
"companies": [
"google"
]
}| Field | Type | Required | Description |
|---|---|---|---|
companies | string[] | Yes | List of LinkedIn company identifiers, URNs, or company URLs to scrape. Enter one identifier/URL per line. URLs will be automatically converted to identifiers. Also accepted: company (Single company alias); or input (Single company alias). |
Results appear in the Scrapy.io run Output tab. Companies and Errors tables in the run output.
Each successful row is designed for warehouse loads: stable column names, explicit error rows, and caps you control in the input form.
{
"name": "Example Co",
"tagline": "Building the future",
"industry": "Software Development",
"company_size": "201-500 employees",
"headquarters": "San Francisco, CA",
"followers": 125000,
"company_url": "https://www.linkedin.com/company/example-co/"
}Download the full dataset as JSON, CSV, or Excel from the Output tab, or fetch results programmatically via the publisher API after the run completes.
enrich account lists with firmographics
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
build competitor landscapes by vertical
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
track funding signals on target companies
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
hydrate account objects from LinkedIn URLs
Teams usually snapshot these rows on a schedule, store a scrapedAt timestamp in their warehouse, and diff week-over-week to spot new entries or metric changes. For first-time setup, run Data Doping with conservative caps, validate the Output preview against your schema, then promote the same JSON to a cron or API job. Document which Output view (Posts, Comments, Reviews, etc.) your downstream models consume so new teammates can reproduce the pipeline without tribal knowledge.
~1 company per second with automatic backoff and per-row errors — built for API batches, not browser tabs. Prefer Data Doping when company cards must refresh on a schedule.
LinkedIn Company Business Data Scraper is rarely the only step in a data workflow. Teams typically:
See Related Data Doping tools below for same-publisher companions you can chain without leaving the Scrapy.io billing account.
Most production deployments follow the same shape:
postUrl, placeId, videoId, reviewId, …) plus scrape date where history mattersLinkedIn Company Business Data Scraper separates successful rows from per-input errors, so staging logic can WHERE type != 'error' (or the equivalent filter for your tool) without failing the whole batch. Join across Data Doping tools on those stable keys to build multi-step datasets without re-scraping upstream steps.
Maintaining Facebook, LinkedIn, Instagram, or X extractors in-house means handling rate limits, HTML or API changes, proxy rotation, and observability — work that rarely differentiates your product. LinkedIn Company Business Data Scraper on Scrapy.io outsources that operational burden: you supply inputs, Scrapy.io runs the job, and you pay per successful row.
Data Doping listings add API-first, warehouse-ready documentation (clear caps, field lists, and pipeline patterns) so data teams can onboard without reading executor source code. When requirements change, update the input JSON or schedule — not your scraper fleet.
LinkedIn Company Business Data Scraper runs on Scrapy.io support multiple ways to get data out:
For production pipelines, most teams land JSON in object storage, normalize in dbt or Spark, and schedule recurring runs so the Store listing becomes just another data source — not a manual step.
Run LinkedIn Company Business Data Scraper once from the Store to validate inputs, then promote the same JSON payload to a scheduled job on Scrapy.io. Common patterns:
datadoping.p.scrapy.io on a queueData Doping tools use pay-per-result billing, so scheduled jobs stay predictable when you cap maxResults, max_posts, max_comments, or equivalent limits in the input form.
curl -X POST "https://datadoping.p.scrapy.io/linkedin-company-scraper/v1/api" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"companies": ["google", "https://linkedin.com/company/example-company"]
}'Bulk runs via the scraper endpoint:
curl -X POST "https://datadoping.p.scrapy.io/linkedin-company-scraper/v1/scraper" \
-H "Content-Type: application/json" \
-H "X-API-Key: YOUR_API_KEY" \
-d '{
"companies": ["google", "https://linkedin.com/company/example-company"]
}'Open the API tab on the Store listing for Python, JavaScript, cURL, OpenAPI, and MCP snippets.
LinkedIn Company Business Data Scraper is available through the Scrapy.io MCP server — configure your API key in Cursor, Claude Desktop, or another MCP client, then invoke the tool from agent workflows. This is useful for ad-hoc research ("scrape these ten URLs and summarize the Output") without writing boilerplate HTTP code.
For production, prefer the publisher API or scheduled runs; use MCP for exploratory analysis and internal tooling where a human or agent supplies inputs interactively. See the API tab on LinkedIn Company Business Data Scraper for MCP connection snippets.
| Tool | Best for |
|---|---|
| LinkedIn Profile Lead Scraper | Data Doping companion tool — overview |
| Instagram Profile Bulk Extractor | Data Doping companion tool — overview |
| X Profile Insights Extractor | Data Doping companion tool — overview |
Batch company identifiers in API jobs — ~1 company per second typical throughput
Per-row errors isolate bad slugs without failing the batch
Store company_url as the stable warehouse key
Inspect per-row errors in the Errors output view instead of failing an entire batch
Facebook-heavy runs failing in a pattern? Use Issues on this Data Doping listing and attach your run ID plus one post, page, or search query
LinkedIn Company Business Data Scraper collects publicly available data only. You are responsible for complying with platform terms, applicable laws, and data-protection regulations (including GDPR when personal data is involved). Consult your legal team for your specific use case.
$3.00 per 1,000 companies — billed per successful row on Scrapy.io. You are charged only for successfully scraped rows. See Scrapy.io pricing for plan details.
Yes. Use webhooks, scheduled runs, or the publisher API to push data into your warehouse, CRM, or automation stack.
Yes. POST to https://datadoping.p.scrapy.io/linkedin-company-scraper/v1/api with your API key. See the API tab on the Store listing for ready-made snippets.
Yes. Configure the Scrapy.io MCP endpoint with your API key to query LinkedIn Company Business Data Scraper from AI assistants and agent workflows.
Data Doping focuses on Meta and social discovery workflows — leave a Reviews note if this actor saved you from browser scraping and which Facebook surface you use daily.