# LinkedIn Lead Enricher — B2B Profile Scraper + Email Finder (`avinashchby/linkedin-lead-enricher`) Actor Scrape public LinkedIn profiles and company pages to extract B2B leads with job titles, company info, and email pattern guessing. Perfect for sales teams and recruiters. - **URL**: https://apify.com/avinashchby/linkedin-lead-enricher.md - **Developed by:** [Avinash](https://apify.com/avinashchby) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Lead Enricher — B2B Profile Scraper + Email Finder Scrape public LinkedIn profiles and company pages to extract structured B2B leads. This actor pulls job titles, company info, skills, location, and generates likely email patterns — perfect for sales teams, recruiters, and growth hackers. ### What It Does - Scrapes public LinkedIn profile pages using Playwright with anti-bot stealth. - Extracts name, headline, current job title, company, location, skills, and industry. - Visits the associated company page to extract the real company domain. - Guesses common email patterns (e.g. `first.last@domain.com`) when enabled. - Computes a **Lead Score (0-100)** based on data completeness. - Pushes every enriched lead to the Apify dataset and emits a `linkedin-lead-enriched` event. ### Input | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `profileUrls` | `stringList` | ✅ | — | LinkedIn profile URLs to scrape | | `maxResults` | `integer` | — | `10` | Max profiles to scrape (max 500) | | `includeEmailGuess` | `boolean` | — | `true` | Guess email patterns from name + domain | | `outputFormat` | `string` | — | `json` | Output format: `json`, `csv`, `hubspot`, `apollo`, `salesforce` | #### Example Input ```json { "profileUrls": ["https://www.linkedin.com/in/williamhgates/"], "maxResults": 10, "includeEmailGuess": true, "outputFormat": "json" } ```` ### Output Each item in the dataset is a structured lead record: ```json { "fullName": "Bill Gates", "headline": "Co-chair, Bill & Melinda Gates Foundation", "currentTitle": "Co-chair", "companyName": "Bill & Melinda Gates Foundation", "companyDomain": "gatesfoundation.org", "location": "Seattle, WA", "connectionDegree": "3rd", "profileUrl": "https://www.linkedin.com/in/williamhgates/", "emails": ["bill.gates@gatesfoundation.org", "billgates@gatesfoundation.org", "bgates@gatesfoundation.org"], "phones": [], "skills": ["Philanthropy", "Global Health", "Education"], "industry": "Philanthropic Fundraising Services", "leadScore": 100, "scrapedAt": "2026-05-17T12:30:00.000Z" } ``` #### Output Fields | Field | Description | |-------|-------------| | `fullName` | Person's full name | | `headline` | LinkedIn headline / tagline | | `currentTitle` | Most recent job title | | `companyName` | Current employer | | `companyDomain` | Company website domain | | `location` | Geographic location | | `connectionDegree` | LinkedIn connection degree (1st, 2nd, 3rd) | | `profileUrl` | Source profile URL | | `emails` | Guessed email patterns (if enabled) | | `phones` | Extracted phone numbers (if any) | | `skills` | List of skills from profile | | `industry` | Industry sector | | `leadScore` | Enrichment score (0-100) | | `scrapedAt` | ISO timestamp | ### Lead Score Formula The lead score rewards data completeness: | Criteria | Points | |----------|--------| | Has current title + company | 30 | | Has company domain | 20 | | Has location | 10 | | Has skills | 10 | | Has industry | 10 | | Email guessed | 20 | | **Maximum** | **100** | ### Limits & Warnings - This actor only scrapes **public** LinkedIn profile pages. Private or restricted profiles will return partial or empty data. - LinkedIn actively blocks scrapers. The actor uses stealth args and delays, but there is no guarantee of 100% reliability. - Respect LinkedIn's [Terms of Service](https://www.linkedin.com/legal/user-agreement) and applicable data privacy laws (GDPR, CCPA). - Email patterns are **guesses only** — they are not verified. Use a verification service before outreach. ### Pricing Compute units depend on the number of profiles scraped and the number of company pages visited. Typical usage is ~0.02 compute units per profile. ### Support For issues, feature requests, or custom integrations, reach out via the Apify platform or open an issue in the actor's repository. # Actor input Schema ## `profileUrls` (type: `array`): List of public LinkedIn profile URLs to scrape. ## `maxResults` (type: `integer`): Maximum number of profiles to scrape. ## `includeEmailGuess` (type: `boolean`): Generate likely email addresses from name + company domain. ## `outputFormat` (type: `string`): Format for the enriched lead output. ## `proxyConfiguration` (type: `object`): Select a proxy to avoid blocking. Apify Proxy is recommended. ## Actor input object example ```json { "profileUrls": [ "https://www.linkedin.com/in/williamhgates/" ], "maxResults": 10, "includeEmailGuess": true, "outputFormat": "json", "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): All extracted leads. # 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/" ] }; // Run the Actor and wait for it to finish const run = await client.actor("avinashchby/linkedin-lead-enricher").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/"] } # Run the Actor and wait for it to finish run = client.actor("avinashchby/linkedin-lead-enricher").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/" ] }' | apify call avinashchby/linkedin-lead-enricher --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=avinashchby/linkedin-lead-enricher", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Lead Enricher — B2B Profile Scraper + Email Finder", "description": "Scrape public LinkedIn profiles and company pages to extract B2B leads with job titles, company info, and email pattern guessing. Perfect for sales teams and recruiters.", "version": "1.0", "x-build-id": "ydqQrYWrrnK6Ng3ph" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/avinashchby~linkedin-lead-enricher/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-avinashchby-linkedin-lead-enricher", "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/avinashchby~linkedin-lead-enricher/runs": { "post": { "operationId": "runs-sync-avinashchby-linkedin-lead-enricher", "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/avinashchby~linkedin-lead-enricher/run-sync": { "post": { "operationId": "run-sync-avinashchby-linkedin-lead-enricher", "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": [ "profileUrls" ], "properties": { "profileUrls": { "title": "LinkedIn Profile URLs", "type": "array", "description": "List of public LinkedIn profile URLs to scrape.", "items": { "type": "string" } }, "maxResults": { "title": "Max Results", "maximum": 500, "type": "integer", "description": "Maximum number of profiles to scrape.", "default": 10 }, "includeEmailGuess": { "title": "Guess Email Patterns", "type": "boolean", "description": "Generate likely email addresses from name + company domain.", "default": true }, "outputFormat": { "title": "Output Format", "enum": [ "json", "csv", "hubspot", "apollo", "salesforce" ], "type": "string", "description": "Format for the enriched lead output.", "default": "json" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Select a proxy to avoid blocking. Apify Proxy is recommended.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```