# LinkedIn Company Lookup (`jobo.world/linkedin-company-lookup`) Actor Paste a list of LinkedIn companies — URLs or slugs — and get back structured JSON: followers, employees, headquarters, industries, recent posts, similar companies, and more. Batch-friendly, fault-tolerant, every field comes with a documented fill rate so you know exactly what to expect. - **URL**: https://apify.com/jobo.world/linkedin-company-lookup.md - **Developed by:** [Enrico](https://apify.com/jobo.world) (community) - **Categories:** Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 company scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## LinkedIn Company Lookup **Paste a list of LinkedIn companies. Get back structured JSON.** Followers, employee count, headquarters, industries, recent posts, similar companies, alumni insights — one record per company, ready to drop into a CRM, a dataset, or your own analysis. [![Run on Apify](https://img.shields.io/badge/Run%20on-Apify-blue)](https://apify.com/jobo.world/linkedin-company-lookup) --- ### ⚡ Why use this actor? - **Just paste — any format works.** Full URLs, bare slugs, locale subdomains (`uk.linkedin.com`), `/about` and `/jobs` paths — all normalized for you. Mix them freely in one run. - **Batch-friendly.** Up to 5 companies per run; lookups run in parallel. - **Failure-tolerant.** One bad URL doesn't kill the run. Failed rows include an `_error` object with a machine-readable `error_type` so you can retry surgically. - **Honest about coverage.** See the [Data coverage](#-data-coverage) section below — every field comes with a real fill-rate percentage so you know exactly what to expect before you spend a credit. - **Pay only for what works.** You're billed per successful company; invalid URLs cost a fraction of a successful lookup, and server / network errors are free. See [Pricing](#-pricing). --- ### 🚀 Quick start ```json { "slugs": ["openai", "anthropicresearch", "stripe"] } ```` That's it. You get one record per company in the dataset. *** ### 📋 Input parameters You must provide at least one of `urls` or `slugs`. They can be mixed. **Up to 5 identifiers per run** (combined across `urls` and `slugs`). | Parameter | Type | Description | | --------- | ----- | ----------------------------------------------------------------------------------------------------------------------------------------------- | | `urls` | Array | Full LinkedIn company URLs, e.g. `https://www.linkedin.com/company/ibm`. Locale subdomains and trailing paths (`/about`, `/jobs`) are stripped. | | `slugs` | Array | Just the slug, e.g. `ibm`, `microsoft`, `openai`. Pattern: `^[A-Za-z0-9._\-]+$`. | #### Mixed input example ```json { "urls": [ "https://www.linkedin.com/company/ibm", "https://uk.linkedin.com/company/microsoft/about/" ], "slugs": ["openai", "anthropicresearch"] } ``` The two URLs above both normalize to canonical form, and any duplicates are removed automatically. *** ### 📤 What you get back One record per input company in the actor's default dataset. Each record carries the full LinkedIn profile shape (see the **Dataset Schema** tab for every field) plus two helper fields: | Field | Description | | ------------- | ------------------------------------------------------------------------------------------------------ | | `_input_url` | The exact URL the actor sent for this row. Use it to correlate dataset rows back to your input list. | | `_error` | Present only when the lookup failed. Inspect `kind`, `status`, and `body` to retry. | #### Successful record (truncated) ```json { "_input_url": "https://www.linkedin.com/company/ibm", "id": "ibm", "company_id": "1009", "name": "IBM", "url": "https://www.linkedin.com/company/ibm", "website": "https://www.ibm.com", "website_simplified": "ibm.com", "logo": "https://media.licdn.com/dms/image/...", "country_code": "US", "country_codes_array": ["US"], "headquarters": "Armonk, New York", "company_size": "10,001+ employees", "employees_in_linkedin": 421337, "followers": 19248301, "industries": "IT Services and IT Consulting", "organization_type": "Public Company", "founded": "1911", "specialties": "Cloud, Mobile, Cognitive, Security, ...", "about": "At IBM, we do more than work. We create...", "employees": [ {"title": "Arvind Krishna", "subtitle": "Chairman and CEO at IBM", "link": "https://www.linkedin.com/in/...", "img": "..."} ], "similar": [ {"title": "Microsoft", "subtitle": "Software Development", "location": "Redmond, WA", "Links": "https://www.linkedin.com/company/microsoft"} ], "updates": [ {"title": "...", "text": "...", "post_url": "...", "likes_count": 1842, "comments_count": 73} ] } ``` #### Failed record ```json { "_input_url": "https://www.linkedin.com/company/this-doesnt-exist-12345", "_error": { "kind": "http", "status": 404, "body": { "title": "Not found", "status": 404, "detail": "No LinkedIn company found for the provided URL.", "error_type": "not_found" } } } ``` The `error_type` field is the canonical, machine-readable classifier: | `error_type` | HTTP | Meaning | Billed | | ---------------------- | :--: | ---------------------------------------------------------------- | :----: | | `not_found` | 404 | URL parsed correctly but the company doesn't exist. | ✓ | | `invalid_input` | 400 | URL malformed or wrong host. | — | | `upstream_unavailable` | 503 | Upstream provider unreachable / transient. Safe to retry. | — | | `internal_error` | 500 | Unexpected server error. | — | *** ### 📊 Data coverage How often is each field actually populated? These percentages are measured over **2,358 real LinkedIn company records**, covering a mix of public, private, large, and small companies. #### ✅ Always present (100% of records) `id` · `name` · `url` · `logo` · `image` · `description` · `company_id` · `company_size` · `employees_in_linkedin` · `followers` #### 🟢 Almost always (>90%) | Field | Filled | |---|---:| | `industries` | 99.96% | | `similar[]` (similar companies) | 99.62% | | `organization_type` | 98.94% | | `about` | 98.05% | | `unformatted_about` | 98.05% | | `website` / `website_simplified` | 97.79% | | `employees[]` (people preview) | 97.58% | | `get_directions_url[]` | 91.56% | | `country_code` / `country_codes_array` | 91.31% | | `formatted_locations` / `locations[]` | 91.31% | | `headquarters` | 91.26% | #### 🟡 Common (50–90%) | Field | Filled | |---|---:| | `updates[]` (recent posts) | 83.88% | | `slogan` | 72.82% | | `founded` | 64.93% | | `specialties` | 61.24% | | `additional_information` | 54.24% | #### 🟠 Sometimes (10–50%) | Field | Filled | |---|---:| | `affiliated[]` (related companies) | 23.71% | #### 🔴 Rare (<10%) — present mostly for venture-backed or public companies | Field | Filled | |---|---:| | `alumni` / `alumni_information[]` | 2.76% | | `crunchbase_url` (when LinkedIn cross-links) | 2.42% | | `funding` (LinkedIn-shipped funding summary) | ~2.4% | | `investors[]` | ~1.4% | | `stock_info` | private companies → null | > **What does this mean for you?** If your use case depends on `funding`, `investors`, or `alumni_information`, expect those fields on a small minority of companies — typically venture-backed startups and large enterprises. Identity, size, headquarters, posts, and similar-companies data are reliable across the board. *** ### 🚀 Usage examples #### Look up a single company ```json { "slugs": ["openai"] } ``` #### Look up several companies by slug ```json { "slugs": ["stripe", "plaid", "ramp", "brex", "mercury"] } ``` #### Mix full URLs and bare slugs in one run ```json { "urls": [ "https://www.linkedin.com/company/ibm", "https://fr.linkedin.com/company/airbus/about/" ], "slugs": ["microsoft", "openai"] } ``` *** ### ❓ FAQ #### How long does a run take? Each lookup typically completes in 30–60 s. A run of 5 companies in parallel lands in ~1 minute. #### Why are some fields `null`? LinkedIn data coverage varies per company. A small startup won't have `alumni_information` or `funding`. A privately-held firm won't have `stock_info`. See the [Data coverage](#-data-coverage) section for measured fill rates per field. **Null = "LinkedIn doesn't expose this for this company"** — not "the actor failed to map it." #### Can I look up a personal LinkedIn profile? No — this actor handles company pages only (`/company/`). Personal profiles (`/in/`) are not supported. #### Why are some fields like `Links` capitalized inside `similar[]`? That's how LinkedIn returns them. We preserve the upstream shape so existing parsers keep working. #### How do I retry just the failures? Filter the dataset for rows where `_error` is set, then feed the `_input_url` values back into a new run. #### What happens if I pass the same URL twice? Inputs are de-duplicated after canonicalization (`urls` and `slugs` both normalize to `https://www.linkedin.com/company/`), so you won't be charged twice for the same company in a single run. *** ### 💰 Pricing Pay-per-event — you're billed only for outcomes, not run-time: | Event | Charged when | Price | | ------------------ | -------------------------------------------------------------- | ----------- | | `successful-lookup`| Company successfully scraped and returned (HTTP 200). | $0.005 each | | `failed-lookup` | URL is structurally valid but the company doesn't exist (404). | $0.002 each | | Server / network errors (HTTP 5xx, timeouts) | — | not billed | Apify's standard `apify-actor-start` ($0.00005, ~one event per run at 128 MB) also applies. *** ### 🔗 Related actors | Actor | Best for | | ------------------------------------------------------------------------------------------- | --------------------------------------------------- | | **[Crunchbase Company Lookup](https://apify.com/jobo.world/crunchbase-company-lookup)** | Resolve Crunchbase URLs into structured JSON. | | **[Glassdoor Company Lookup](https://apify.com/jobo.world/glassdoor-company-lookup)** | Resolve Glassdoor URLs into ratings + interviews. | | **[ATS Jobs Search](https://apify.com/jobo.world/ats-jobs-search)** | Search jobs from 48 ATS platforms in one API call. | *** ### 🏢 About Jobo Jobo provides job & company data infrastructure for developers, recruiters, and AI agents. - **Website**: [jobo.world](https://jobo.world) - **Support**: enrico@jobo.world # Actor input Schema ## `urls` (type: `array`): Full LinkedIn company URLs, e.g. 'https://www.linkedin.com/company/ibm'. Locale subdomains and '/about', '/jobs', '/people' suffixes are stripped automatically. Up to 5 per run. ## `slugs` (type: `array`): Just the slug part of the company URL — e.g. 'ibm' for https://www.linkedin.com/company/ibm. Allowed characters: letters, digits, '-', '\_', '.'. Up to 5 per run (combined with urls). ## Actor input object example ```json { "urls": [ "https://www.linkedin.com/company/ibm", "https://www.linkedin.com/company/microsoft" ] } ``` # Actor output Schema ## `companies` (type: `string`): All resolved LinkedIn company records (including failures, identifiable by the presence of an `_error` field). ## `overview` (type: `string`): Compact tabular view: name, slug, country, employees, followers, industries, website. ## `csv_export` (type: `string`): Flattened CSV — useful for spreadsheets, CRM imports, and BI tools. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "urls": [ "https://www.linkedin.com/company/ibm", "https://www.linkedin.com/company/microsoft" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jobo.world/linkedin-company-lookup").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "urls": [ "https://www.linkedin.com/company/ibm", "https://www.linkedin.com/company/microsoft", ] } # Run the Actor and wait for it to finish run = client.actor("jobo.world/linkedin-company-lookup").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "urls": [ "https://www.linkedin.com/company/ibm", "https://www.linkedin.com/company/microsoft" ] }' | apify call jobo.world/linkedin-company-lookup --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jobo.world/linkedin-company-lookup", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Company Lookup", "description": "Paste a list of LinkedIn companies — URLs or slugs — and get back structured JSON: followers, employees, headquarters, industries, recent posts, similar companies, and more. Batch-friendly, fault-tolerant, every field comes with a documented fill rate so you know exactly what to expect.", "version": "1.0", "x-build-id": "6UwgagsD6yQbXkQDN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jobo.world~linkedin-company-lookup/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jobo.world-linkedin-company-lookup", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jobo.world~linkedin-company-lookup/runs": { "post": { "operationId": "runs-sync-jobo.world-linkedin-company-lookup", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jobo.world~linkedin-company-lookup/run-sync": { "post": { "operationId": "run-sync-jobo.world-linkedin-company-lookup", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "urls": { "title": "LinkedIn Company URLs", "maxItems": 5, "uniqueItems": true, "type": "array", "description": "Full LinkedIn company URLs, e.g. 'https://www.linkedin.com/company/ibm'. Locale subdomains and '/about', '/jobs', '/people' suffixes are stripped automatically. Up to 5 per run.", "items": { "type": "string" } }, "slugs": { "title": "LinkedIn Company Slugs", "maxItems": 5, "uniqueItems": true, "type": "array", "description": "Just the slug part of the company URL — e.g. 'ibm' for https://www.linkedin.com/company/ibm. Allowed characters: letters, digits, '-', '_', '.'. Up to 5 per run (combined with urls).", "items": { "type": "string", "pattern": "^[A-Za-z0-9._\\-]+$" } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```