# Target Email Scraper (`scraperoka/target-email-scraper`) Actor 📧 Target Email Scraper extracts verified email addresses from target pages with precision. 🚀 Perfect for B2B outreach, lead gen, and sales prospecting—save time, improve deliverability, and scale campaigns with confidence. - **URL**: https://apify.com/scraperoka/target-email-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, Automation, Developer tools - **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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ### Target Email Scraper 🎯 Manually hunting for lead emails across the web wastes hours you can’t get back. **Target Email Scraper** finds email addresses from publicly available sources using your keywords and email-domain filters, returning results you can export and use for outreach. Ideal for marketers, recruiters, and growth teams doing targeted email harvesting at scale—get thousands of leads-ready records in a single run. --- ### What You Get: Sample Output Here's a sample record from a single run: ```json [ { "keyword": "marketing", "title": "Example Contact Page", "description": "For business inquiries: sales-team@gmail.com. We respond within 24 hours.", "url": "https://target.com/example-contact", "email": "sales-team@gmail.com" }, { "keyword": "john", "title": "Team Directory", "description": "Reach out at john@companymail.com for partnerships and press.", "url": "https://target.com/team", "email": "john@companymail.com" } ] ```` **Output Fields** | Field | Type | What It Tells You | |---|---|---| | `keyword` | string | Which keyword you used to generate this lead email result | | `title` | string | The page/result title associated with the extracted email | | `description` | string | The extracted text snippet tied to the email (useful for context) | | `url` | string | The source link where the email was found | | `email` | string | The extracted email address (deduplicated across the run) | | `status` | not present in output | The actor logs errors, but the pushed dataset record contains `keyword`, `title`, `description`, `url`, and `email` (no explicit status field is written) | | `error_message` | not present in output | If a request fails, the run continues; individual records are only pushed when an email is detected | Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard. *** ### Why Target Email Scraper? There are a lot of ways to pull email data from the web — here’s what sets Target Email Scraper apart. #### Keyword-first targeting Target Email Scraper is driven by your `keywords` input, so results are tied directly to the intent you’re researching (e.g., outreach topics, roles, or brand-related terms). Pair that with your domain filters for more targeted email harvesting tools style results. #### Domain filtering for cleaner leads You control which email domains are considered through `customDomains`. That helps the targeted email scraper focus on the domains you care about (for example, limiting results to specific business email providers). #### Deduplicated emails in a single run The actor keeps a `seen_emails` set, so the same email won’t be emitted multiple times within a run. This means your bulk email scraper output is less noisy and easier to import into outreach workflows. #### Resilient scraping with fallback behavior If the initial attempt yields no emails for a query under the selected proxy approach, Target Email Scraper can switch to a fallback proxy configuration to try again. This is designed to keep your lead email scraper runs productive even when some requests underperform. *** ### Configuring Your Run Drop this into your `input.json` to get started: ```json { "keywords": ["john", "marketing"], "location": "United States", "platform": "Target", "customDomains": ["@gmail.com", "@company.com"], "proxyConfiguration": { "useApifyProxy": true } } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | A list of keywords the actor uses to drive targeted email scraping results | | `location` | ⬜ | Optional location text to help filter results when provided | | `platform` | ⬜ | Selects the platform type for this actor (the only available value is `Target`) | | `customDomains` | ⬜ | Filters emails to only the domains you list (for example `@gmail.com`) | | `proxyConfiguration` | ⬜ | Configure proxy usage for this Actor | | ↳ `proxy support` | ⬜ | When enabled, routing is performed via Apify Proxy for reliability | *** ### Core Capabilities #### Targeted keyword email harvesting Target Email Scraper uses your `keywords` array to guide what it looks for, aligning results with the topics you’re actively prospecting. It outputs each detected lead email record along with the associated `keyword` for traceability. #### Focused website email scraper output You get structured records containing `title`, `description`, `url`, and the final `email`. That combination makes it much easier to validate sources and build qualified lead email scraper lists without jumping around manually. #### Custom email-domain filtering With `customDomains`, you can restrict extracted emails to specific domains. This keeps your email address scraper results more relevant and reduces time spent cleaning up mismatched leads. #### Proxy support for reliable runs The actor supports `proxyConfiguration` so you can improve reliability for larger batches and repeated runs. It’s especially helpful when you need consistent data mining email scraper behavior across many keywords. #### Dataset-ready results for automation All collected results are pushed to the Apify dataset at the end of the run via `Actor.push_data(...)`. You can then export instantly or move the data into your CRM or outreach pipeline. *** ### Who Gets the Most Out of This Here's how different teams put Target Email Scraper to work: **Lead generation and growth teams** use it to build outreach lists tied to specific keywords, filtered to the email domains they trust. The output includes the source `url` and contextual `description`, so they can quickly vet and prioritize targets. **B2B marketers** use the email harvesting tool to expand prospecting lists while keeping results consistent with their messaging themes. By narrowing `customDomains`, they reduce irrelevant leads and speed up list-building. **Recruiters and HR teams** can use a target email scraper workflow to identify candidate outreach contacts based on keyword research. The `title` and `url` fields help support faster manual verification when needed. **Data analysts and researchers** use it to create structured datasets for downstream processing. Because each record includes the `keyword` used, it’s easier to analyze which keyword themes correlate with higher-quality email matches. **Automation specialists (technical users)** can run Target Email Scraper programmatically, then feed the dataset into pipelines for deduplication, enrichment, scoring, or CRM ingestion. The consistent record structure supports reliable automation. *** ### Step-by-Step: How to Use It No coding needed. Here's how to run Target Email Scraper from start to finish: 1. **Open the actor on Apify** — go to [console.apify.com](https://console.apify.com). 2. **Enter your inputs** — set `keywords`, optionally `location`, choose `platform` (Target), add `customDomains`, and configure `proxyConfiguration` if needed. 3. **Configure proxy settings** — select your preferred proxy configuration for this Actor to improve reliability. 4. **Hit Run and watch the live log** — monitor progress and check logs if requests fail. 5. **View results in the dataset tab** — the actor pushes collected records as a dataset after the run. 6. **Export as JSON, CSV, or Excel** — download directly from Apify or integrate with your workflow. The whole process takes under 5 minutes to set up. *** ### Integrations & Export Options Once your data is collected, Target Email Scraper plugs directly into your existing workflow. Export formats are available directly from the Apify dataset tab: JSON, CSV, or Excel. From there, you can import into spreadsheets, CRMs, or enrichment tools used in your email extraction software process. You can also use the Apify platform’s API access to pull results programmatically (see [apify.com/docs/api](https://apify.com/docs/api) for details), and connect the workflow to automation tools such as Zapier or Make for pushing new results to your downstream systems. *** ### Pricing & Free Trial Target Email Scraper runs on the Apify platform, which offers a **free tier** — no credit card required to get started. In practice, this typically means you can run several tests to validate your keywords and domain filters before scaling up. For ongoing usage, pricing is based on Apify platform compute units (CU) rather than a simple per-row fee. Start on Apify to confirm exact credits and compute usage for your workload, then scale when you’re ready. Start for free at [apify.com](https://apify.com) and scale when you're ready. *** ### Reliability & Performance | What We Handle | How | |---|---| | Proxy reliability | Built-in proxy support for more consistent scraping runs | | Empty-result scenarios | Fallback behavior can switch proxy configuration when no emails are found for a query | | Run continuity | If a request fails for one keyword/domain combo, the actor continues processing others | | Output usability | Results are structured into consistent JSON objects in the dataset | **Limitations:** The actor extracts emails only when they are present in publicly available sources tied to the run’s logic. If the target contact information is not available or doesn’t match your `customDomains` filters, you may get fewer (or zero) results. For cases requiring different strategies or expanded targeting logic, consider requesting a custom setup. For enterprise-scale runs, contact us to discuss custom configurations. *** ### Frequently Asked Questions #### Is there a free plan or trial? Yes. Target Email Scraper runs on the Apify platform, which offers a **free tier** to help you test your inputs before scaling. #### Do I need to log in to Target to use this? No. This actor scrapes emails from publicly available sources and is designed to work without requiring login credentials to the target platform. #### How accurate is the data? Accuracy depends on what is published publicly. The actor extracts email addresses that match your `customDomains` filters and returns them with the related `url` and contextual `description` so you can quickly validate. #### How many results can I get per run? The actor requests a batch size of `num=100` while processing each keyword and domain combination. Your final number of dataset records depends on how many matching emails are found across those combinations. #### How often is the data updated / how fresh is it? Data freshness depends on when sources are updated and when you run the actor. Each run collects results at runtime and pushes them to your dataset after completion. #### Is this legal? Does it comply with GDPR / CCPA? Target Email Scraper accesses **publicly available data** and does not require login-gated access. It’s still your responsibility to comply with GDPR, CCPA, and applicable platform Terms of Service when collecting, storing, and using email addresses. #### Can I export results to Google Sheets or Excel? Yes. You can export from the Apify dataset tab in standard formats like JSON, CSV, or Excel, which you can then import into Google Sheets or other tools. #### Can I run this on a schedule automatically? Yes. You can schedule actor runs using Apify platform capabilities, so the Target Email Scraper can refresh your email lists automatically on a recurring basis. #### Can I access this via API? Yes. You can access actor runs and results programmatically using the Apify API—see [apify.com/docs/api](https://apify.com/docs/api) for details. #### What happens if the actor hits an error? The actor logs request failures for specific keyword/domain combinations and continues processing other combinations. It still outputs whatever results were successfully collected into the dataset. *** ### Need Help or Have a Request? Got a question about Target Email Scraper or want a new feature added? Reach out at . We’re happy to help with setup ideas and can consider improvements like batch CSV upload support or a webhook on completion. Target Email Scraper is actively maintained based on user feedback. *** ### Disclaimer & Responsible Use *Target Email Scraper is the fastest, most reliable way to extract targeted lead emails from publicly available sources — start your free run today.* This actor collects **publicly available data** only. It does not access private accounts, login-gated content, or password-protected pages. You are responsible for complying with GDPR, CCPA, applicable privacy regulations, and the relevant platform Terms of Service. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): A list of keywords to search for. ## `location` (type: `string`): Location to filter search results. ## `platform` (type: `string`): Select platform. ## `customDomains` (type: `array`): List of custom email domains ## `proxyConfiguration` (type: `object`): Configure proxies for this Actor. ## Actor input object example ```json { "keywords": [ "john", "marketing" ], "location": "", "platform": "Target", "customDomains": [ "@gmail.com" ] } ``` # 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": [ "john", "marketing" ], "location": "", "customDomains": [ "@gmail.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/target-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": [ "john", "marketing", ], "location": "", "customDomains": ["@gmail.com"], } # Run the Actor and wait for it to finish run = client.actor("scraperoka/target-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": [ "john", "marketing" ], "location": "", "customDomains": [ "@gmail.com" ] }' | apify call scraperoka/target-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/target-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Target Email Scraper", "description": "📧 Target Email Scraper extracts verified email addresses from target pages with precision. 🚀 Perfect for B2B outreach, lead gen, and sales prospecting—save time, improve deliverability, and scale campaigns with confidence.", "version": "0.0", "x-build-id": "tI8Q8perZqLWHbh0t" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~target-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-target-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~target-email-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-target-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~target-email-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-target-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Keywords", "type": "array", "description": "A list of keywords to search for.", "default": [ "john", "marketing" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "platform": { "title": "Platform", "enum": [ "Target" ], "type": "string", "description": "Select platform.", "default": "Target" }, "customDomains": { "title": "Custom Email Domains", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com" ], "items": { "type": "string" } }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Configure proxies for this Actor." } } }, "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 } } } } } } } } } } ```