# Linkedin Profiles Email Scraper (`scrapers-hub/linkedin-profiles-email-scraper`) Actor 📩 LinkedIn Profiles Email Scraper extracts verified contact emails from LinkedIn profiles for smarter outreach. 🚀 Perfect for lead gen, B2B sales, and recruitment—save time, boost deliverability, and scale faster. - **URL**: https://apify.com/scrapers-hub/linkedin-profiles-email-scraper.md - **Developed by:** [Scrapers Hub](https://apify.com/scrapers-hub) (community) - **Categories:** Lead generation, Automation, Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Keyword Email Search 🔍 **LinkedIn Keyword Email Search** is an Apify actor that helps you find targeted LinkedIn leads using your keywords, then returns profile data together with extracted email addresses. Whether you’re looking for **LinkedIn email search** results, a way to **find email on LinkedIn**, or an **email finder keyword** workflow for lead generation, this tool streamlines the process by filtering by **country** and collecting contacts in a structured dataset—saving you hours of manual work. --- ### Why choose LinkedIn Keyword Email Search? | Feature | Benefit | | --- | --- | | ✅ Keyword-based lead discovery | Search for LinkedIn profiles separately for each keyword in one run. | | ✅ Country filter | Focus results by selecting a target country (or leave it empty for worldwide). | | ✅ Email-only filtering mode | When enabled, it returns leads that include email addresses (LinkedIn keyword email lookup). | | ✅ Reliability through retries & fallbacks | Includes retries and resilience for smoother runs on changing public web data. | | ✅ Structured JSON dataset output | Exports clean fields like `keyword`, `username`, `userLink`, and `emails`. | | ✅ Built-in scale controls | Limit results using `Maximum Leads Per Keyword` (up to 500). | --- ### Key features - 📧 **Accurate email extraction**: Extracts email addresses from profile-related text and returns them as the `emails` array - 🔎 **LinkedIn keyword search email workflows**: Uses your keywords and processes them individually so you can segment results - 🌍 **Country targeting**: Filters results by your chosen country to support localized campaigns and research - 🧪 **Email availability mode**: Optionally runs in a “find leads with email only” mode to prioritize contacts with addresses - 🛡️ **Resilient scraping behavior**: Uses retries and handles empty-result conditions to keep long runs stable - 💾 **Real-time dataset saving**: Pushes results during the run so you don’t lose progress - 🔄 **Controlled lead volume**: Uses `Maximum Leads Per Keyword` to cap how much data you collect per keyword --- ### Input Provide input via an `input.json` file. Example structure: ```json { "keywords": ["software engineer", "marketing manager"], "country": "United States", "maxLeadsPerKeyword": 20, "scrapeLeadsWithEmail": false } ```` #### Input Fields | Field | Required | Description | | --- | --- | --- | | `keywords` | ✅ | A list of keywords to search for LinkedIn profiles. Each keyword will be searched separately (useful for “LinkedIn email search tool” style lead generation). | | `country` | ❌ | Target country filter. Leave empty for worldwide results. If not set, it defaults to `United States`. | | `maxLeadsPerKeyword` | ❌ | Maximum number of leads to collect for each keyword (allowed range: 1–500). Default is `20`. | | `scrapeLeadsWithEmail` | ❌ | If `true`, the actor will prioritize leads that have email addresses (email-availability mode for “LinkedIn advanced search email” use cases). If `false`, it collects all matching profiles. Default is `false`. | *** ### Output The actor saves each profile’s data in JSON format. In the default dataset view, the transformation focuses on these fields: `keyword`, `username`, `userLink`, and `emails`. Example output (one dataset item shown as a JSON object): ```json [ { "keyword": "software engineer", "username": "john-doe", "userLink": "https://www.linkedin.com/in/john-doe", "emails": ["john.doe@example.com"] } ] ``` #### Output Fields | Field | Type | Description | | --- | --- | --- | | `keyword` | string | The keyword that produced this lead (handy for segmentation in LinkedIn keyword email contact workflows). | | `username` | string | The extracted LinkedIn profile username from the profile link. | | `userLink` | string | The LinkedIn profile URL. | | `emails` | array | Extracted email addresses found in the profile description text associated with the lead. | Note: In **email-only filtering mode**, the actor only saves profiles that have emails (it filters out profiles where `emails` is empty). In non-email-only mode, profiles are still enriched and pushed to the dataset by `Actor.push_data` with the same output structure. *** ### How to use LinkedIn Keyword Email Search (via Apify Console) 1. **Open Apify Console**\ Go to [console.apify.com](https://console.apify.com) and sign in to your Apify account. 2. **Find the actor**\ Search for **LinkedIn Keyword Email Search** in the Actors marketplace and open the actor page. 3. **Switch to the INPUT tab**\ You’ll see a form connected to the input schema. Enter your values in the fields. 4. **Add your lead keywords**\ Paste a list into `keywords` (for example: `software engineer`, `marketing manager`). Each keyword is searched separately, which makes downstream analysis easier for “LinkedIn email outreach contact search”. 5. **Choose a target country (optional)**\ Set `country` to one of the supported options. If you want worldwide results, you can leave it empty (the schema allows an empty value). 6. **Set your limits**\ Use `maxLeadsPerKeyword` to control how many leads you want per keyword (1–500). This is your main lever for scaling LinkedIn keyword email lookup campaigns without collecting too much. 7. **Pick your email mode**\ Toggle `scrapeLeadsWithEmail`: - `true`: prioritize leads that include email addresses - `false`: collect all matching profiles for your keywords 8. **Run & monitor logs**\ Start the run. Watch the logs for progress updates. The actor saves results during execution, and it uses retries and resilience for better stability on publicly available data. 9. **Access results & export**\ When finished, open the dataset (default view: “Scraped Leads”). Export as JSON/CSV from the dataset UI. No coding required — get accurate results in minutes with LinkedIn Keyword Email Search. 🚀 *** ### Advanced features & SEO optimization - 📌 **Purpose-built for “LinkedIn keyword email contact” workflows**: Engineered to excel at collecting LinkedIn contact leads by keyword and returning them with email addresses for easier enrichment and outreach prep. - 📧 **Email-only filtering**: Turn on `scrapeLeadsWithEmail` when your goal is “find email on LinkedIn” quality leads (LinkedIn email finder keyword). - 🔄 **Resilience for consistent runs**: Includes retries and fallback handling behavior so the actor can keep going when public web data doesn’t return results consistently. - 🧠 **Clean, marketer-friendly structure**: Output is shaped into `keyword`, `username`, `userLink`, and `emails`, making it simple to map into CRMs or spreadsheets for “LinkedIn lead generation email search”. *** ### Best use cases - 🚀 **Marketing teams building outreach lists**: Collect keyword-based leads and attach extracted emails for faster campaign setup (LinkedIn email outreach contact search). - 🧾 **Data analysts segmenting lead pools**: Use the `keyword` field to group results and measure which roles (e.g., marketing manager vs. sales director) produce the most email coverage. - 👥 **Recruiters sourcing passive candidates**: Find targeted profiles by role keyword and extract emails for follow-up workflows. - 🌍 **Growth teams running country-specific experiments**: Filter by `country` and compare email availability across regions for LinkedIn keyword email search. - 🏢 **Sales development teams generating target lists**: Scale “search LinkedIn for email addresses” style prospecting with controlled per-keyword limits. - 🧑‍💻 **Developer automation pipelines**: Feed the dataset into downstream steps (deduping, enrichment, CRM import) using the structured JSON output. - 📚 **Market research & competitive mapping**: Build lists by niche keywords and analyze email coverage with `emails` availability. *** ### Technical specifications - **Supported Input Formats** - ✅ `keywords` (array of strings) - ✅ `country` (string; select from the provided country list) - ✅ `maxLeadsPerKeyword` (integer) - ✅ `scrapeLeadsWithEmail` (boolean) - **Proxy Support** - ✅ Built-in proxy support for more reliable scraping of publicly available data - **Retry Mechanism** - ✅ Uses retries for web page scraping (configured with `max_retries`) - **Dataset Structure** - ✅ Default dataset view includes: `keyword`, `username`, `userLink`, `emails` - **Rate Limits & Performance** - ✅ Uses small delays between requests when configured (`request_delay` is set to `0` in code) - **Limitations** - ❌ Results depend on publicly available profile text and email presence - ❌ Email extraction returns what can be found in the associated text; some profiles may yield empty `emails` *** ### FAQ #### Is LinkedIn Keyword Email Search free to use? ✅ It includes a **Free tier limit of 100 emails maximum**. If you’re using the free tier, the actor enforces a maximum email limit (it detects whether you are a paid user and applies the free cap when needed). #### Do I need to provide login or a LinkedIn account? ❌ No LinkedIn login details are part of the actor input schema. You just provide keywords and your preferences in the Apify Console input. #### What does “Find Leads with Email Only” do? ✅ When `scrapeLeadsWithEmail` is enabled, the actor prioritizes leads that have email addresses and filters out profiles without any extracted emails. This is useful for “LinkedIn keyword email lookup” and “LinkedIn email outreach contact search” workflows where email availability matters. #### What fields will I get in the dataset? ✅ The dataset is structured with `keyword`, `username`, `userLink`, and `emails` (email addresses as an array). #### How do I scale results safely? ✅ Use `maxLeadsPerKeyword` to cap how many leads are collected per keyword (1–500). Combined with multiple `keywords`, this helps you control total volume and keep output aligned to your workflow needs. #### Can I run keyword-based searches in batches? ✅ Yes. Provide multiple entries in `keywords`. The actor processes each keyword separately, making the output easier to segment for analysis and targeted outreach. #### How can I remove data if needed? If you need help with data removal, contact . #### Can I export results to other formats? ✅ Yes. After the run, you can export the dataset from the Apify Console (for example, JSON/CSV from the dataset UI). *** ### Support & feature requests Have questions or want improvements to **LinkedIn Keyword Email Search**? We’d love your feedback. 😊 - 💡 **Feature Requests**: Want enhancements like improved export formatting, additional filters, or CRM-friendly output shaping? Tell us what you need for “LinkedIn email search” and “LinkedIn keyword email search” use cases. - 📧 **Contact**: Email us at . Your feedback helps shape the roadmap. *** ### Closing CTA / Final thoughts *If you’re building targeted lead lists, LinkedIn Keyword Email Search is a practical, structured way to automate LinkedIn keyword email extraction at scale.* Try **LinkedIn Keyword Email Search** today for an SEO-friendly, marketer-ready workflow. 🚀 *** ### Disclaimer **This actor only accesses publicly accessible sources**. It does not access private profiles, authenticated content, or password-protected data. It’s your responsibility to comply with applicable laws and regulations (including GDPR/CCPA where relevant), as well as platform terms and spam/communications rules. For data removal requests, contact . Use LinkedIn Keyword Email Search responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `keywords` (type: `array`): List of keywords to search for LinkedIn profiles (e.g., 'software engineer', 'marketing manager', 'sales director'). Each keyword will be searched separately. ## `country` (type: `string`): Filter results by country. Leave empty for worldwide results. ## `maxLeadsPerKeyword` (type: `integer`): Maximum number of leads to collect for each keyword (1-500). ## `scrapeLeadsWithEmail` (type: `boolean`): If enabled, will search for profiles that have emails in their Google search results (using common email providers like Gmail, Hotmail, Outlook, Yahoo). If disabled, will find all profiles matching keywords. ## Actor input object example ```json { "keywords": [ "software engineer", "marketing manager" ], "country": "United States", "maxLeadsPerKeyword": 20, "scrapeLeadsWithEmail": false } ``` # 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 = { "keywords": [ "software engineer", "marketing manager" ], "country": "United States", "maxLeadsPerKeyword": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("scrapers-hub/linkedin-profiles-email-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 = { "keywords": [ "software engineer", "marketing manager", ], "country": "United States", "maxLeadsPerKeyword": 20, } # Run the Actor and wait for it to finish run = client.actor("scrapers-hub/linkedin-profiles-email-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 '{ "keywords": [ "software engineer", "marketing manager" ], "country": "United States", "maxLeadsPerKeyword": 20 }' | apify call scrapers-hub/linkedin-profiles-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers-hub/linkedin-profiles-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Profiles Email Scraper", "description": "📩 LinkedIn Profiles Email Scraper extracts verified contact emails from LinkedIn profiles for smarter outreach. 🚀 Perfect for lead gen, B2B sales, and recruitment—save time, boost deliverability, and scale faster.", "version": "1.0", "x-build-id": "fdGEDMJeBWaMMPlUY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers-hub~linkedin-profiles-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers-hub-linkedin-profiles-email-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapers-hub~linkedin-profiles-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapers-hub-linkedin-profiles-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapers-hub~linkedin-profiles-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapers-hub-linkedin-profiles-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "keywords" ], "properties": { "keywords": { "title": "Search Keywords", "minItems": 1, "uniqueItems": true, "type": "array", "description": "List of keywords to search for LinkedIn profiles (e.g., 'software engineer', 'marketing manager', 'sales director'). Each keyword will be searched separately.", "items": { "type": "string" } }, "country": { "title": "Target Country", "enum": [ "United States", "United Kingdom", "Canada", "Australia", "India", "Germany", "France", "Spain", "Italy", "Brazil", "Mexico", "Japan", "South Korea", "China", "Singapore", "United Arab Emirates", "Netherlands", "Sweden", "Norway", "Denmark", "Switzerland", "Belgium", "Austria", "Ireland", "New Zealand", "South Africa" ], "type": "string", "description": "Filter results by country. Leave empty for worldwide results.", "default": "United States" }, "maxLeadsPerKeyword": { "title": "Maximum Leads Per Keyword", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of leads to collect for each keyword (1-500).", "default": 20 }, "scrapeLeadsWithEmail": { "title": "Find Leads with Email Only", "type": "boolean", "description": "If enabled, will search for profiles that have emails in their Google search results (using common email providers like Gmail, Hotmail, Outlook, Yahoo). If disabled, will find all profiles matching keywords.", "default": false } } }, "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 } } } } } } } } } } ```