# LinkedIn Decision Makers Scraper - CEOs, Founders & Executives (`apt_marble/linkedin-decision-makers-scraper-ceos-founders-executives`) Actor Find CEOs, founders, CTOs, recruiters, and other decision makers from public LinkedIn profiles using — no LinkedIn login or cookies required 🚀 - **URL**: https://apify.com/apt\_marble/linkedin-decision-makers-scraper-ceos-founders-executives.md - **Developed by:** [Hamza](https://apify.com/apt_marble) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 5 total users, 3 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $2.50 / 1,000 results 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 Decision Makers Scraper **Find CEOs, founders, CTOs, recruiters, and other LinkedIn decision makers by job title, industry, and location — no cookies or LinkedIn login required.** Paste a few job titles, optionally narrow by industry and country, and walk away with a clean spreadsheet of names, current roles, companies, locations, and LinkedIn profile URLs — ready for your CRM, sequencer, or applicant-tracking system. No browser extensions. No LinkedIn account. No Sales Navigator seat. Just a single Apify actor that runs in the cloud and returns publicly visible profile data. --- ### What it does This actor turns LinkedIn into a B2B prospecting source. Specify the decision-maker titles you want (CEO, Founder, CTO, VP Sales, Marketing Director, Recruiter, …), optionally add industry tags (`SaaS`, `Fintech`, `Healthcare`) and locations (`United States`, `Berlin`), and it returns a clean dataset of matching profiles. It is positioned as an **affordable LinkedIn Sales Navigator alternative** for outbound sales, recruiting, and competitive-intelligence work. --- ### What you get back Each row in the dataset is one decision maker: ```json { "fullName": "John Smith", "firstName": "John", "lastName": "Smith", "headline": "CEO at AI Growth Labs", "currentRole": "CEO", "company": "AI Growth Labs", "location": "New York, United States", "linkedinUrl": "https://www.linkedin.com/in/johnsmith", "profileImage": null, "snippet": "CEO at AI Growth Labs helping SaaS companies...", "jobTitleMatched": "CEO", "industryKeyword": "SaaS", "locationKeyword": "United States", "timestamp": "2026-05-21T12:00:00Z" } ```` The full field list: | Field | What it is | |---|---| | `fullName` | The decision maker's full name | | `firstName` / `lastName` | Best-effort split for mail-merge | | `headline` | LinkedIn headline | | `currentRole` | Detected role (CEO, Founder, CTO, …) | | `company` | Detected company name | | `location` | City / region / country | | `linkedinUrl` | Canonical `https://www.linkedin.com/in/` URL | | `snippet` | Raw profile snippet text | | `jobTitleMatched` | The decision-maker title bucket this profile matched | | `industryKeyword` | Industry filter used (if any) | | `locationKeyword` | Location filter used (if any) | | `timestamp` | ISO 8601 scrape time | Export to CSV, JSON, Excel, or pipe directly into Zapier, Make, Clay, Apollo, or any HTTP webhook. *** ### Inputs | Field | Type | What it does | |---|---|---| | **Decision Maker Titles** | `array` | Titles to hunt for (`CEO`, `Founder`, `CTO`, `VP Sales`, …). Defaults to `CEO, Founder, CTO`. | | **Industry / Company Keywords** | `array` | Industry tags (`SaaS`, `Fintech`) or company names (`Stripe`, `OpenAI`). Optional. | | **Locations** | `array` | Country / region / city filters (`United States`, `Berlin`). Optional. | | **Maximum Profiles** | `integer` | Stop after collecting N unique profiles. Default `100`. | | **Search Language** | `string` | Language hint. Default `en`. | | **Deduplicate Results** | `boolean` | Drop duplicate LinkedIn URLs across the run. Default `true`. | The actor automatically expands every combination of (industries × locations) using the supplied title bucket. So 3 industries × 2 locations = 6 internal searches, all deduplicated into one clean dataset. *** ### Example use cases **Outbound B2B sales** — Pull a list of 200 SaaS founders in the United States in under a minute, then push them into Apollo or Clay for email enrichment. **Recruiting & sourcing** — Build a roster of every recruiter in healthcare across Germany and France. Pair `linkedinUrl` with a profile-scraper actor to enrich work history. **SaaS founders prospecting investors** — Search `Partner`, `Principal`, `Managing Director` across venture-capital firms for warm-intro targets. **HR agencies** — Find HR managers and CHROs by industry vertical, then run scheduled scrapes monthly to track leadership churn at target accounts. **Competitive intel for RevOps** — Map the head of growth, head of marketing, and CTO at every direct competitor in one run. **Outreach agencies** — Generate fresh decision-maker lists per client per industry, no Sales Navigator seat per agent. *** ### Tips that save you time and money - **Preview with a low cap.** Set `Maximum Profiles` to 25 for your first run to verify the queries return the kind of profiles you expect. - **Be specific with industries.** `"SaaS"` returns very different people than `"B2B SaaS"` or `"vertical SaaS"`. Use quoted phrases to keep the matching tight. - **Locations are loose by design.** Treat them as a phrase that appears anywhere on the profile, so you'll get some noise. For a clean per-country list, run separate location queries and filter the output. - **Mix in company names.** Adding `"Stripe"` as a keyword finds people working at Stripe or who mention Stripe in their headline — useful for ABM list-building. - **Deduplication is on by default.** Leave it on unless you specifically want to see overlap across keywords. *** ### Pricing — pay only for what you extract | Apify Plan | Start Fee | Per Profile | | ------------- | --------- | ----------- | | Free / Bronze | $0.0025 | $0.0025 | | Silver | $0.0025 | ~$0.0022 | | Gold | $0.0025 | ~$0.0020 | | Platinum | $0.0025 | ~$0.0018 | | Diamond | $0.0025 | ~$0.0015 | #### Real-World Cost Examples 💰 - 25 profiles for a quick test run: about **$0.06** - 250 SaaS founders in the US & Canada: about **$0.63** - 2,000 decision makers across multiple industries: about **$5.00** Affordable lead generation at scale without expensive LinkedIn tools 🚀 *** ### Frequently asked **Do I need a LinkedIn account or Sales Navigator?** No. The actor never logs into LinkedIn, never asks for cookies, and never touches your account. It returns publicly visible profile data only. **Will this get me LinkedIn-banned?** No. The actor never authenticates against LinkedIn — there's no account activity for LinkedIn to flag. **How accurate is the role/company parsing?** Very good for headlines in the standard `" at "` format, which is how most LinkedIn profiles are written. Multilingual headlines (`"CEO chez …"`, `"PDG bei …"`) are also detected. Obscure formats may leave the role/company fields null — the raw `headline` and `snippet` are always preserved so you can post-process. **Will I get duplicates if I run it twice?** Within a single run, no — dedup is on by default. Across runs, yes — track previously seen `linkedinUrl` values in your own pipeline. **Can I schedule this?** Yes. Apify Schedules let you run it weekly to track new decision makers entering an industry or location. Combine with a webhook to push new rows into Google Sheets, Notion, HubSpot, or Salesforce. **The actor returned 0 results — what's wrong?** Check in this order: (1) Are your industry/location keywords reasonable English phrases that would appear on a public profile? (2) Try removing the `Locations` filter to see if the issue is over-narrowing. (3) Broaden your title list — add synonyms like `Co-Founder` next to `Founder`. *** ### A note on responsible use This actor extracts data that is already publicly visible on LinkedIn. It does not bypass authentication, log into accounts, scrape private profiles, or pull anything beyond what any anonymous visitor could see. The legal foundation for scraping public profile data was reinforced in **hiQ Labs v. LinkedIn** (9th Circuit, 2022). That said: **scraped data is still personal data**. Don't use it for spam, harassment, or anything that violates GDPR, CCPA, or similar laws in your jurisdiction. Treat the people in your dataset the way you'd want to be treated in someone else's CRM. *** ### Drop it into your workflow - **Apify Schedules** → run weekly to catch newly visible decision makers in your target industries - **Zapier / Make** → push new rows into HubSpot, Salesforce, Notion, or Google Sheets - **Apify Webhook** → POST results to your server for custom enrichment - **Pair with a LinkedIn Profile Scraper** → use `linkedinUrl` to enrich each lead with full work history - **Pair with an email-finder** → push `firstName + lastName + company` into Clay, Apollo, or Hunter to resolve emails Run it once with a small `maxResults` to see what you get. The first 25 profiles are usually cheap enough to taste-test before committing. # Actor input Schema ## `jobTitles` (type: `array`): Job titles to hunt for. Common picks: CEO, Founder, Co-Founder, CTO, CMO, COO, VP Sales, Marketing Director, HR Manager, Recruiter, Head of Growth. Add as many as you want. ## `searchKeywords` (type: `array`): Industry tags (`SaaS`, `AI`, `Fintech`, `Healthcare`, `Cybersecurity`, `Shopify`, `E-commerce`) or specific company names (`Stripe`, `OpenAI`, `HubSpot`). Leave empty to skip industry filtering. ## `locations` (type: `array`): Country, region, or city filters. Examples: `United States`, `Canada`, `Germany`, `Dubai`, `Paris`. Leave empty to search worldwide. ## `maxResults` (type: `integer`): Stop after collecting this many unique decision-maker profiles. ## `language` (type: `string`): Language hint for the search (`en`, `fr`, `de`, `es`, `pt`, etc.). ## `deduplicateResults` (type: `boolean`): Drop duplicate profiles based on the canonical LinkedIn URL. ## Actor input object example ```json { "jobTitles": [ "CEO", "Founder", "CTO" ], "searchKeywords": [ "SaaS" ], "locations": [ "United States" ], "maxResults": 100, "language": "en", "deduplicateResults": true } ``` # 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 = { "jobTitles": [ "CEO", "Founder", "CTO" ], "searchKeywords": [ "SaaS" ], "locations": [ "United States" ] }; // Run the Actor and wait for it to finish const run = await client.actor("apt_marble/linkedin-decision-makers-scraper-ceos-founders-executives").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 = { "jobTitles": [ "CEO", "Founder", "CTO", ], "searchKeywords": ["SaaS"], "locations": ["United States"], } # Run the Actor and wait for it to finish run = client.actor("apt_marble/linkedin-decision-makers-scraper-ceos-founders-executives").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 '{ "jobTitles": [ "CEO", "Founder", "CTO" ], "searchKeywords": [ "SaaS" ], "locations": [ "United States" ] }' | apify call apt_marble/linkedin-decision-makers-scraper-ceos-founders-executives --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apt_marble/linkedin-decision-makers-scraper-ceos-founders-executives", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Decision Makers Scraper - CEOs, Founders & Executives", "description": "Find CEOs, founders, CTOs, recruiters, and other decision makers from public LinkedIn profiles using — no LinkedIn login or cookies required 🚀", "version": "0.0", "x-build-id": "99deDRlP7OlyhhTE9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apt_marble~linkedin-decision-makers-scraper-ceos-founders-executives/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apt_marble-linkedin-decision-makers-scraper-ceos-founders-executives", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/apt_marble~linkedin-decision-makers-scraper-ceos-founders-executives/runs": { "post": { "operationId": "runs-sync-apt_marble-linkedin-decision-makers-scraper-ceos-founders-executives", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/apt_marble~linkedin-decision-makers-scraper-ceos-founders-executives/run-sync": { "post": { "operationId": "run-sync-apt_marble-linkedin-decision-makers-scraper-ceos-founders-executives", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "jobTitles" ], "properties": { "jobTitles": { "title": "🎯 Decision Maker Titles", "type": "array", "description": "Job titles to hunt for. Common picks: CEO, Founder, Co-Founder, CTO, CMO, COO, VP Sales, Marketing Director, HR Manager, Recruiter, Head of Growth. Add as many as you want.", "default": [ "CEO", "Founder", "CTO" ], "items": { "type": "string" } }, "searchKeywords": { "title": "Industry / Company Keywords", "type": "array", "description": "Industry tags (`SaaS`, `AI`, `Fintech`, `Healthcare`, `Cybersecurity`, `Shopify`, `E-commerce`) or specific company names (`Stripe`, `OpenAI`, `HubSpot`). Leave empty to skip industry filtering.", "default": [], "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "Country, region, or city filters. Examples: `United States`, `Canada`, `Germany`, `Dubai`, `Paris`. Leave empty to search worldwide.", "default": [], "items": { "type": "string" } }, "maxResults": { "title": "Maximum Profiles", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Stop after collecting this many unique decision-maker profiles.", "default": 100 }, "language": { "title": "Search Language", "type": "string", "description": "Language hint for the search (`en`, `fr`, `de`, `es`, `pt`, etc.).", "default": "en" }, "deduplicateResults": { "title": "Deduplicate Results", "type": "boolean", "description": "Drop duplicate profiles based on the canonical LinkedIn URL.", "default": true } } }, "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 } } } } } } } } } } ```