# LinkedIn Profile Scraper - People, Job Changes & B2B Leads (`scrapesage/linkedin-profile-scraper`) Actor Scrape public LinkedIn profiles into rich people records: name, headline, current company & title, location, full work experience, education, languages, follower & connection counts and a lead score. Feed profile URLs or search by keyword. Job-change monitor mode. No login, no cookies, no browser. - **URL**: https://apify.com/scrapesage/linkedin-profile-scraper.md - **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $4.00 / 1,000 profile 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 Profile Scraper — People, Job Changes & B2B Leads Turn any list of **public LinkedIn profiles** into rich, structured people records — **full name, headline, current company & title, location, complete work experience, education, languages, exact follower & connection counts, and a 0–100 lead score**. Feed profile URLs (or usernames) straight from your CRM or Sales Navigator export, and optionally **expand into related profiles** ("People also viewed") to snowball a small seed list into hundreds of similar prospects. Then switch on **monitor mode** to get **job-change alerts** — the single strongest B2B buying signal there is. No login, no cookies, no browser — fast, public-data extraction. ### Why this LinkedIn profile scraper? Most LinkedIn scrapers either need your account cookies (risky) or return a thin record with the headline and little else. This actor merges **two sources on every public profile** — the embedded JSON-LD and the rendered page — to ship the **richest dataset in the category**, and it never asks for your login. | Data | Typical scrapers | This actor | |---|---|---| | Full name, headline, location | ✅ | ✅ | | Current company, title & seniority | partial | ✅ | | **Complete work experience** (title, company, company URL, date range, duration) | ❌ | ✅ | | **Education** (school, school URL, degree, years) | ❌ | ✅ | | **Exact follower count** (not "12M") | ❌ | ✅ | | Connection count | partial | ✅ | | Languages, awards, external links | ❌ | ✅ | | **Lead score (0–100)** per profile | ❌ | ✅ | | **Job-change / title-change / headline-change detection** | ❌ | ✅ monitor mode | | **Related-profile discovery** ("People also viewed") | ❌ | ✅ snowball | | Needs your LinkedIn cookies? | often | **❌ never** | ### Use cases - **B2B lead generation & prospecting** — enrich a list of profile URLs into a complete sales record: name, title, company, seniority, location and lead score. Prioritize decision-makers (`seniorityLevel` = Owner/C-Level or VP/Director). - **Job-change alerts (buying signals)** — run in monitor mode on a schedule and get a record the moment a prospect changes jobs, gets promoted, or updates their headline. New-in-role buyers are the warmest leads in B2B. - **Recruiting & sourcing** — build candidate shortlists with full experience and education history; track when passive candidates become open to work. - **CRM enrichment** — keep contact records fresh with current title, company and location. - **Market & talent intelligence** — map who works where, seniority distribution, and follower influence across a company or industry. - **Influencer & creator research** — rank profiles by exact follower count and recent activity. ### How to use 1. [Sign up for Apify](https://console.apify.com/sign-up) — the free plan is enough to try this actor. 2. Open the **LinkedIn Profile Scraper**, paste **Profile URLs** (or usernames) — optionally turn on **Discover related profiles** — and click **Start**. 3. Watch results stream into the dataset table. 4. **Export** as JSON, CSV, Excel, XML, or RSS — or pull results programmatically via the [Apify API](https://docs.apify.com/api/v2). ### Input ```json { "profileUrls": [ "https://www.linkedin.com/in/williamhgates", "satyanadella" ], "discoverRelated": false, "maxRelatedPerProfile": 20, "maxProfiles": 100, "includeExperience": true, "includeEducation": true, "includeActivity": false, "monitorMode": false } ```` - **profileUrls** — LinkedIn profile URLs (`https://www.linkedin.com/in/`) or bare usernames. The primary, fastest, most reliable input. - **startUrls** — alternative request-list of profile URLs (handy when chaining from another actor). - **discoverRelated** *(default false)* — expand each seed profile into its **"People also viewed"** people (one level deep), bounded by **maxRelatedPerProfile** and **maxProfiles**. The reliable way to grow a seed list into similar prospects without supplying every URL. - **maxProfiles** *(default 100)* — cap the number of profiles; set `0` for no limit (explicit opt-in). - **includeExperience / includeEducation** *(default true)* — full experience & education lists (same page, no extra request). - **includeActivity** *(default false)* — recent public posts/activity when present. - **monitorMode** *(default false)* — emit a record only when a profile **changed** since the last run (new job / title / headline). See below. - **maxConcurrency** *(default 8)* — profiles fetched in parallel. - **proxyConfiguration** — keep the default (Apify **residential**, US); LinkedIn blocks datacenter IPs. ### Output One record per profile (`type: "profile"`): ```json { "type": "profile", "profileUrl": "https://www.linkedin.com/in/williamhgates", "publicId": "williamhgates", "fullName": "Bill Gates", "firstName": "Bill", "lastName": "Gates", "headline": "Chair, Gates Foundation and Founder, Breakthrough Energy", "currentTitle": "Co-chair", "currentCompany": "Gates Foundation", "currentCompanyUrl": "https://www.linkedin.com/company/gates-foundation", "seniorityLevel": "Owner/C-Level", "locationName": "Seattle, Washington, United States", "city": "Seattle", "country": "United States", "about": "Chair of the Gates Foundation. Founder of Breakthrough Energy. Co-founder of Microsoft…", "profilePhotoUrl": "https://media.licdn.com/dms/image/v2/…/profile-displayphoto.jpg", "followerCount": 40467271, "connectionCount": 500, "connectionCountText": "500+", "experience": [ { "title": "Co-chair", "company": "Gates Foundation", "companyUrl": "https://www.linkedin.com/company/gates-foundation", "dateRange": "2000 - Present", "durationText": "26 years", "startDate": 2000, "isCurrent": true }, { "title": "Co-founder", "company": "Microsoft", "dateRange": "1975 - Present", "startDate": 1975, "isCurrent": true } ], "experienceCount": 3, "education": [ { "school": "Harvard University", "schoolUrl": "https://www.linkedin.com/school/harvard-university", "dateRange": "1973 - 1975", "startYear": 1973, "endYear": 1975 } ], "educationCount": 2, "languages": ["English"], "jobTitles": ["Co-chair", "Founder", "Co-founder"], "isInfluencer": true, "leadScore": 92, "source": "url", "scrapedAt": "2026-06-26T12:00:00.000Z" } ``` ### Job-change monitoring (the killer feature) Turn on **monitorMode** and combine it with an Apify **Schedule** (e.g. weekly). On the first run every profile is emitted as `first_seen`. On later runs the actor compares each profile to its stored snapshot and emits a record **only when something changed**: ```json { "fullName": "Jane Doe", "changeType": "new_job", "currentTitle": "VP of Marketing", "currentCompany": "Acme Corp", "previousTitle": "Director of Marketing", "previousCompany": "Globex", "changedFields": ["company", "title"], "lastChangedAt": "2026-06-26T12:00:00.000Z", "profileUrl": "https://www.linkedin.com/in/janedoe" } ``` Monitor mode is **orthogonal to Apify Schedules** — the Schedule decides *when* the actor runs; monitor mode decides *what* it emits. Wire a [webhook](https://docs.apify.com/platform/integrations/webhooks) or [Zapier](https://docs.apify.com/platform/integrations/zapier) zap to push job-change alerts straight into your CRM or Slack. State is kept in a named key-value store (`monitorStoreName`). ### Automate & schedule Run this actor on autopilot and pull results into your own stack: - **[Apify API](https://docs.apify.com/api/v2)** — start runs, fetch datasets, and manage schedules over REST. - **[apify-client for JavaScript](https://docs.apify.com/api/client/js/)** and **[apify-client for Python](https://docs.apify.com/api/client/python/)** — official SDKs. - **[Schedules](https://docs.apify.com/platform/schedules)** — run hourly/daily/weekly to refresh records or watch a set of prospects for job changes. - **[Webhooks](https://docs.apify.com/platform/integrations/webhooks)** — trigger downstream actions (CRM import, Slack alert, email sequence) the moment a run finishes. ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' }); const run = await client.actor('scrapesage/linkedin-profile-scraper').call({ profileUrls: [ 'https://www.linkedin.com/in/williamhgates', 'satyanadella', ], maxProfiles: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(`Got ${items.length} LinkedIn profiles`); ``` ### Integrate with any app Connect the dataset to 5,000+ apps — no code required: - **[Make](https://docs.apify.com/platform/integrations/make)** — multi-step automation scenarios. - **[Zapier](https://docs.apify.com/platform/integrations/zapier)** — push new profiles or job-change alerts straight into your CRM. - **[Slack](https://docs.apify.com/platform/integrations/slack)** — get notified when a monitored prospect changes jobs. - **[Google Drive / Sheets](https://docs.apify.com/platform/integrations/drive)** — auto-export every run to a spreadsheet. - **[Airbyte](https://docs.apify.com/platform/integrations/airbyte)** — pipe results into your data warehouse. - **[GitHub](https://docs.apify.com/platform/integrations/github)** — trigger runs from commits or releases. ### Use with AI assistants (MCP) The output is clean, LLM-ready JSON. Call this actor from Claude, ChatGPT, or any agent framework through the **[Apify MCP server](https://docs.apify.com/platform/integrations/mcp)** — ask your assistant to "enrich these LinkedIn URLs into a lead list and flag anyone who changed jobs this month" and let it run this scraper for you. ### Agent-ready: autonomous payments (x402 & Skyfire) This actor is **agent-ready** — AI agents can discover it, run it, and **pay for it autonomously**, with no Apify account and no human in the loop. It uses [pay-per-event](https://docs.apify.com/platform/actors/publishing/monetize/pay-per-event) pricing and [limited permissions](https://docs.apify.com/platform/actors/development/permissions), so it qualifies for Apify's agentic-payment standards: - **[x402](https://docs.apify.com/platform/integrations/x402)** — an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) — no account, no API key. - **[Skyfire](https://docs.apify.com/platform/integrations/skyfire)** — agent-to-service payments for fully autonomous AI-agent workflows. Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes. ### More scrapers from scrapesage Build a complete **B2B lead-gen & sales-intelligence stack**: - **[LinkedIn Company Scraper](https://apify.com/scrapesage/linkedin-company-scraper)** — firmographics & company B2B leads (size, industry, HQ, website). - **[LinkedIn Jobs Scraper](https://apify.com/scrapesage/linkedin-jobs-scraper)** — job postings as hiring-intent signals. - **[LinkedIn Ad Library Scraper](https://apify.com/scrapesage/linkedin-ad-library-scraper)** — competitor B2B ads & creatives. - **[Website Contact Scraper](https://apify.com/scrapesage/website-contact-scraper)** — emails, phones & socials from any domain (enrich your profile leads with contact details). - **[Google Maps Scraper](https://apify.com/scrapesage/google-maps-scraper)** — local business leads, emails & contacts. - **[Salesforce AppExchange Scraper](https://apify.com/scrapesage/salesforce-appexchange-scraper)** — ISV vendor & publisher leads. - **[IndiaMART Scraper](https://apify.com/scrapesage/indiamart-scraper)** — B2B supplier & product leads. ### Tips - **Profile URLs are the most reliable input.** Turn on **Discover related profiles** to snowball from a handful of seeds into many similar prospects. - **Keep the residential proxy.** LinkedIn blocks datacenter IPs; the actor rotates a fresh residential IP per request and retries transient rate-limits automatically. - **For job-change monitoring**, reuse the same `monitorStoreName` across scheduled runs so snapshots persist. - **Cost control** — each profile is one request; lower `maxConcurrency` for steadier runs on very large lists. ### FAQ **Do I need my LinkedIn account or cookies?** No. This actor reads **public** profile pages only — no login, no cookies, no browser. **Which fields can it get?** Name, headline, current company/title, seniority, location, about, profile photo, exact follower count, connection count, full work experience (with company URLs and dates), education, languages, awards, external links, and recent activity (opt-in) — plus a lead score. **Why is a field sometimes empty?** Profiles are member-filled. Sections like About, Languages, Awards or external links are `null` only when the member didn't add them (or LinkedIn doesn't expose them to logged-out visitors), never because the scraper skipped them. Skills and certifications are not shown on logged-out public profiles. **Can I discover profiles without supplying every URL?** Yes — turn on `discoverRelated` and the actor expands each seed profile into the people LinkedIn lists under "People also viewed" (one level deep, bounded by your caps). Start with a few good seeds and let it snowball into similar prospects. **Can I export to Google Sheets, CSV, or Excel?** Yes — one click in the dataset view, or automatically on every run via the [Google Drive integration](https://docs.apify.com/platform/integrations/drive). **Is scraping LinkedIn legal?** This actor collects only publicly available data. You are responsible for using the data in compliance with applicable laws (GDPR/CCPA for personal data) and LinkedIn's terms. Scraping of public profile data has been upheld in the U.S. (hiQ v. LinkedIn), but rules vary by jurisdiction and use case — get advice for your situation. ### Need help? Open an issue on the actor's **Issues** tab, or visit the [Apify help center](https://help.apify.com/). Feature requests are welcome — this actor is actively maintained. # Actor input Schema ## `profileUrls` (type: `array`): LinkedIn profile URLs (https://www.linkedin.com/in/) or bare usernames. The primary, fastest, most reliable input — paste a list exported from your CRM, Sales Navigator, or a spreadsheet. ## `startUrls` (type: `array`): Alternative to Profile URLs — a standard Apify request list of LinkedIn profile URLs. Useful when chaining from another actor or integration. ## `discoverRelated` (type: `boolean`): Expand each seed profile into the people LinkedIn shows under "People also viewed" on that profile — a reliable way to snowball a small seed list into many similar prospects (same role, network or industry). Bounded to one level of expansion and the Max profiles cap. ## `maxRelatedPerProfile` (type: `integer`): When Discover related profiles is on, how many related people to harvest from each seed profile (before the overall Max profiles cap is applied). ## `maxProfiles` (type: `integer`): Maximum number of profile records to return. Keep modest for a fast run; set 0 for no limit (explicit opt-in). ## `includeExperience` (type: `boolean`): Extract the full work-experience list (title, company, company URL, date range, duration, location). Same page — no extra request. ## `includeEducation` (type: `boolean`): Extract the education list (school, school URL, degree, field, years). Same page — no extra request. ## `includeActivity` (type: `boolean`): Also extract the profile's recent public posts / activity (text + link) when present. Same page — no extra request. ## `monitorMode` (type: `boolean`): Re-scan the same profiles on a schedule and emit a record ONLY when something changed since the last run — a new job, a title change, a company change or a headline change. Perfect for sales/recruiting buying-signals. Works alongside Apify Schedules (the schedule controls WHEN it runs; monitor mode controls WHAT is emitted). State is stored in a named key-value store. ## `monitorStoreName` (type: `string`): Named key-value store that remembers each profile's last snapshot for monitor mode. Reuse the same name across scheduled runs. ## `maxConcurrency` (type: `integer`): How many profiles to fetch in parallel. Lower = gentler on rate limits and steadier; higher = faster. ## `proxyConfiguration` (type: `object`): LinkedIn requires residential proxies. Keep the default (Apify residential, US) for the most reliable results. ## Actor input object example ```json { "profileUrls": [ "https://www.linkedin.com/in/williamhgates" ], "discoverRelated": false, "maxRelatedPerProfile": 20, "maxProfiles": 100, "includeExperience": true, "includeEducation": true, "includeActivity": false, "monitorMode": false, "monitorStoreName": "linkedin-profile-monitor", "maxConcurrency": 8, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `results` (type: `string`): All scraped LinkedIn profile / people-lead records as JSON items in the default dataset. # 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 = { "profileUrls": [ "https://www.linkedin.com/in/williamhgates", "satyanadella" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("scrapesage/linkedin-profile-scraper").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 = { "profileUrls": [ "https://www.linkedin.com/in/williamhgates", "satyanadella", ], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("scrapesage/linkedin-profile-scraper").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 '{ "profileUrls": [ "https://www.linkedin.com/in/williamhgates", "satyanadella" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call scrapesage/linkedin-profile-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapesage/linkedin-profile-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Profile Scraper - People, Job Changes & B2B Leads", "description": "Scrape public LinkedIn profiles into rich people records: name, headline, current company & title, location, full work experience, education, languages, follower & connection counts and a lead score. Feed profile URLs or search by keyword. Job-change monitor mode. No login, no cookies, no browser.", "version": "0.1", "x-build-id": "IBpuHmoGAaHArUoWQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapesage~linkedin-profile-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapesage-linkedin-profile-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapesage~linkedin-profile-scraper/runs": { "post": { "operationId": "runs-sync-scrapesage-linkedin-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapesage~linkedin-profile-scraper/run-sync": { "post": { "operationId": "run-sync-scrapesage-linkedin-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "profileUrls": { "title": "Profile URLs or usernames", "type": "array", "description": "LinkedIn profile URLs (https://www.linkedin.com/in/) or bare usernames. The primary, fastest, most reliable input — paste a list exported from your CRM, Sales Navigator, or a spreadsheet.", "items": { "type": "string" } }, "startUrls": { "title": "Start URLs (request list)", "type": "array", "description": "Alternative to Profile URLs — a standard Apify request list of LinkedIn profile URLs. Useful when chaining from another actor or integration.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "discoverRelated": { "title": "Discover related profiles", "type": "boolean", "description": "Expand each seed profile into the people LinkedIn shows under \"People also viewed\" on that profile — a reliable way to snowball a small seed list into many similar prospects (same role, network or industry). Bounded to one level of expansion and the Max profiles cap.", "default": false }, "maxRelatedPerProfile": { "title": "Max related per profile", "minimum": 1, "maximum": 50, "type": "integer", "description": "When Discover related profiles is on, how many related people to harvest from each seed profile (before the overall Max profiles cap is applied).", "default": 20 }, "maxProfiles": { "title": "Max profiles", "minimum": 0, "maximum": 100000, "type": "integer", "description": "Maximum number of profile records to return. Keep modest for a fast run; set 0 for no limit (explicit opt-in).", "default": 100 }, "includeExperience": { "title": "Include work experience", "type": "boolean", "description": "Extract the full work-experience list (title, company, company URL, date range, duration, location). Same page — no extra request.", "default": true }, "includeEducation": { "title": "Include education", "type": "boolean", "description": "Extract the education list (school, school URL, degree, field, years). Same page — no extra request.", "default": true }, "includeActivity": { "title": "Include recent activity", "type": "boolean", "description": "Also extract the profile's recent public posts / activity (text + link) when present. Same page — no extra request.", "default": false }, "monitorMode": { "title": "Monitor mode (job-change detection)", "type": "boolean", "description": "Re-scan the same profiles on a schedule and emit a record ONLY when something changed since the last run — a new job, a title change, a company change or a headline change. Perfect for sales/recruiting buying-signals. Works alongside Apify Schedules (the schedule controls WHEN it runs; monitor mode controls WHAT is emitted). State is stored in a named key-value store.", "default": false }, "monitorStoreName": { "title": "Monitor store name", "type": "string", "description": "Named key-value store that remembers each profile's last snapshot for monitor mode. Reuse the same name across scheduled runs.", "default": "linkedin-profile-monitor" }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "How many profiles to fetch in parallel. Lower = gentler on rate limits and steadier; higher = faster.", "default": 8 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "LinkedIn requires residential proxies. Keep the default (Apify residential, US) for the most reliable results.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```