# Booking Com Email Scraper Fast Advanced And Cheapest (`solid-scraper/booking-com-email-scraper-fast-advanced-and-cheapest`) Actor 📧 Grab verified Booking.com emails fast with this Advanced, cheapest email scraper. Target by keyword & location to build cleaner lead lists for agencies, sales teams & marketers. ⚡ Secure, efficient, and easy to use. - **URL**: https://apify.com/solid-scraper/booking-com-email-scraper-fast-advanced-and-cheapest.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Lead generation, Travel, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 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 ### Booking.Com Email Scraper - Fast, Advanced and Cheapest 🔍 **Booking.Com Email Scraper - Fast, Advanced and Cheapest** extracts email addresses from Booking.com based on the keywords and email-domain filters you specify. Whether you're a marketer, sales lead, recruiter, or researcher, this actor helps you solve the “how do I quickly find relevant contacts?” problem by turning public web data into a usable email list—so you can save hours of manual outreach prep and scale lead generation. --- ### Why choose Booking.Com Email Scraper - Fast, Advanced and Cheapest? | Feature | Benefit | | --- | --- | | ✅ **Keyword and email-domain targeting** | Finds emails that match your chosen keywords and allowed domains | | ✅ **Location filtering (optional)** | Narrows results when you want contacts tied to a specific location | | ✅ **Max email limit control** | Keeps runs predictable by stopping once your `maxEmails` limit is reached | | ✅ **Resume support with saved progress** | Continues from the last keyword/domain combination if a run is interrupted | | ✅ **Proxy resilience & fallbacks** | Improves reliability when scraping encounters blocks or empty results | | ✅ **Structured dataset output** | Saves results with consistent fields like `keyword`, `title`, `url`, and `email` | --- ### Key features - 🔎 **Accurate email extraction:** Extracts email addresses from publicly available sources and pushes each found lead into the dataset - 🎛️ **Flexible targeting inputs:** Supports `keywords`, optional `location`, and `customDomains` (like `@gmail.com`, `@yahoo.com`) to improve relevance for your booking.com email scraper email extractor workflow - ⏳ **Configurable volume with `maxEmails`:** Stops when the requested number of unique emails is reached (helps control scraping time/cost) - 🛡️ **Built-in reliability improvements:** Includes handling for empty results and blocked pages, with resilience for real-world variability - 🔄 **Progress saving & resuming:** Remembers which keyword/domain you were processing and what emails were already found - 📊 **Clear lead records:** Stores `keyword`, `title`, `description`, `url`, and `email` so you can quickly review quality and deduplicate downstream - 💾 **Incremental dataset writes:** Pushes results as they’re found, reducing the risk of losing progress during longer runs --- ### Input Provide input via an `input.json` file. Example structure: ```json { "keywords": ["manager", "founder"], "location": "Barcelona", "customDomains": ["@gmail.com", "@yahoo.com"], "maxEmails": 20 } ```` #### Input Fields | Field | Required | Description | | --- | --- | --- | | `keywords` | ✅ Yes | A list of keywords (or queries) used to find relevant Booking.com listings to extract emails from. | | `location` | ❌ No | Location text used to filter results. Leave empty to search without a location filter. | | `customDomains` | ❌ No | Email domain whitelist for extracted addresses (for example `@gmail.com`, `@yahoo.com`). | | `maxEmails` | ❌ No | Maximum number of **unique** emails to collect. The scraper stops once the limit is reached. Higher values can take longer and still don’t guarantee the exact count. | *** ### Output The actor saves each extracted lead into a dataset as JSON records. Example pushed record: ```json { "network": "Booking.com.com", "keyword": "manager", "title": "No title", "description": "No data", "url": "No URL", "email": "example@gmail.com" } ``` #### Output Fields | Field | Type | Description | | --- | --- | --- | | `network` | string | The network label used for output records (`Booking.com.com`). | | `keyword` | string | The keyword used for this extraction run. | | `title` | string | Title text captured from the source result. | | `description` | string | Description text (or extracted text) associated with the result where the email was found. | | `url` | string | The URL captured from the result. | | `email` | string | The extracted email address. | The dataset view is titled **Scraped Leads** and includes columns for `keyword`, `title`, `description`, `url`, and `email`. *** ### How to use Booking.Com Email Scraper - Fast, Advanced and Cheapest (via Apify Console) 1. **Open Apify Console**\ Log in at [console.apify.com](https://console.apify.com) and go to the **Actors** section. 2. **Find the actor**\ Search for **Booking.Com Email Scraper - Fast, Advanced and Cheapest** and open the actor page. 3. **Go to the INPUT section**\ Use the built-in form (or upload your `input.json`) to provide your extraction settings. 4. **Set your targeting**\ Enter `keywords` (required). Optionally add `location` and choose `customDomains` to improve result quality—useful for a booking.com email scraper email extractor style workflow. 5. **Choose your limit**\ Set `maxEmails` to control how many unique emails you want per run (the scraper stops once the limit is reached). 6. **Start the run**\ Click **Run**. Watch the logs for progress updates and any notes about results being limited. The actor saves progress and can resume later using its stored cursor and seen emails. 7. **Review results in OUTPUT**\ Open the **Scraped Leads** dataset to inspect the table (including `keyword`, `title`, `description`, `url`, `email`) and export to the formats you need (JSON/CSV from the dataset UI). 8. **Refine and rerun if needed**\ If you get fewer results than expected, try wider keywords, add more domains to `customDomains`, or adjust the `location` filter. No coding required—get actionable booking.com email scraping software results in minutes. *** ### Advanced features & SEO optimization - 🔁 **Resume-ready runs:** If your run is interrupted, it continues from the last processed keyword/domain while keeping `seen_emails` to avoid duplicates. - 🎯 **Engineered-for-purpose targeting:** Built around your keywords and email-domain filters, making it a strong fit for booking.com lead generation email scraper use cases. - 📊 **Early stopping for cost control:** The `maxEmails` limit helps you balance depth vs runtime—especially when using a fast email scraper for booking.com workflow. - 💡 **Result quality tuning:** If results are limited, broaden keywords, include similar terms, or add more domains to capture more relevant contact emails. *** ### Best use cases - 📈 **B2B lead generation:** Build a contact email list for outreach tied to specific Booking.com listing roles like manager or founder. - 🗂️ **Market research:** Compare contact availability across locations and keyword themes to understand how businesses present contact channels. - ✉️ **Cold email campaigns:** Use extracted booking email scraping tool outputs to populate outreach sequences and CRM lists. - 🧪 **Data enrichment projects:** Combine extracted emails with other lead metadata you already have, then deduplicate by email. - 🧑‍💼 **Sales ops & SDR workflows:** Generate quick prospect sets for a booking.com email collector tool process. - 🔎 **Research pipelines:** Feed extracted `keyword` + `url` + `email` records into analysis or compliance workflows for verification steps. *** ### Technical specifications - **Supported Input Formats** - ✅ `keywords`: array of strings (required) - ✅ `location`: string (optional) - ✅ `customDomains`: array of strings like `@gmail.com` / `@yahoo.com` (optional) - ✅ `maxEmails`: integer between 1 and 10000 (optional) - **Proxy Support** - ✅ Built-in proxy support to improve scraping reliability - **Retry Mechanism** - ✅ Includes resilience logic for empty results and blocked pages - **Dataset Structure** - ✅ Each extracted lead record is pushed with: `network`, `keyword`, `title`, `description`, `url`, `email` - **Rate Limits & Performance** - ✅ Runtime depends on search coverage and your chosen limits; larger runs and higher `maxEmails` can take longer - **Limitations** - ❌ If the public sources contain few matching contacts, the actor may return fewer than `maxEmails` - ❌ Free users are subject to a **100 emails maximum** limit applied by the actor (unless the environment indicates a paid user) *** ### FAQ #### How many emails can I collect with Booking.Com Email Scraper - Fast, Advanced and Cheapest? You can set `maxEmails` to control the maximum number of unique emails collected. The actor stops once the limit is reached, and larger values may take longer while still not guaranteeing you’ll reach the exact count. #### Do I need to provide keywords? Yes. The `keywords` field is required. It’s the main driver for finding relevant Booking.com contacts whose emails can be extracted. #### Can I filter results by location? Yes. Use the optional `location` field to narrow extraction to a specific place. Leave it empty to search without a location filter. #### How do custom email domains work? Use `customDomains` to whitelist which email address domains you want included (for example `@gmail.com`, `@yahoo.com`). This helps you focus the output and is commonly used in advanced booking.com email scraper workflows. #### What does the actor save in the dataset? Each record pushed to the dataset includes `network`, `keyword`, `title`, `description`, `url`, and `email`, which makes it easy to review and export your booking.com email list generator results. #### Is there a limit for free users? Yes. When running as a free user, the actor applies a maximum of **100 emails**. The actor checks the runtime environment to decide whether to enforce this limit. #### Does it resume if my run stops? Yes. The actor saves progress (including a cursor and `seen_emails`) and resumes from where it left off, helping you complete longer runs reliably. #### Can I use this with other tools or export later? Yes. After the run, you can export the dataset from the Apify dataset UI (for example to JSON/CSV workflows) and integrate the fields into your own pipelines. *** ### Support & feature requests If you’re using Booking.Com Email Scraper - Fast, Advanced and Cheapest and want improvements, we’d love your feedback 😊 💡 **Feature Requests:** Want enhancements like additional export formats, smarter filtering options, or CRM-friendly output? Share what would make your booking.com email scraper email extractor workflow faster. 📧 **Contact:** For help or suggestions, email . Your feedback helps shape the roadmap for future versions of this booking.com email scraping software. *** ### *Booking.Com Email Scraper - Fast, Advanced and Cheapest* — Final thoughts *Booking.Com Email Scraper - Fast, Advanced and Cheapest is built to be the most comprehensive, SEO-optimized booking.com email scraper option for teams that need results quickly.*\ If you’re ready to generate leads at scale, this actor is a great starting point. *** ### Disclaimer **This tool accesses publicly accessible sources only.** It does not access private profiles, authenticated data, or password-protected content. You are responsible for complying with applicable laws and regulations (including GDPR and CCPA where relevant), spam rules, and the involved platforms’ Terms of Service. For data removal requests, contact . Use Booking.Com Email Scraper - Fast, Advanced and Cheapest responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `keywords` (type: `array`): A list of keywords or queries to search for. ## `location` (type: `string`): Location to filter search results. ## `customDomains` (type: `array`): List of custom email domains ## `maxEmails` (type: `integer`): Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time. ## Actor input object example ```json { "keywords": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "maxEmails": 20 } ``` # 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": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/booking-com-email-scraper-fast-advanced-and-cheapest").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": [ "manager", "founder", ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com", ], } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/booking-com-email-scraper-fast-advanced-and-cheapest").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": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }' | apify call solid-scraper/booking-com-email-scraper-fast-advanced-and-cheapest --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/booking-com-email-scraper-fast-advanced-and-cheapest", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Booking Com Email Scraper Fast Advanced And Cheapest", "description": "📧 Grab verified Booking.com emails fast with this Advanced, cheapest email scraper. Target by keyword & location to build cleaner lead lists for agencies, sales teams & marketers. ⚡ Secure, efficient, and easy to use.", "version": "1.0", "x-build-id": "DGkeWwP9bHVGqLk3M" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~booking-com-email-scraper-fast-advanced-and-cheapest/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-booking-com-email-scraper-fast-advanced-and-cheapest", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~booking-com-email-scraper-fast-advanced-and-cheapest/runs": { "post": { "operationId": "runs-sync-solid-scraper-booking-com-email-scraper-fast-advanced-and-cheapest", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~booking-com-email-scraper-fast-advanced-and-cheapest/run-sync": { "post": { "operationId": "run-sync-solid-scraper-booking-com-email-scraper-fast-advanced-and-cheapest", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 or Queries", "type": "array", "description": "A list of keywords or queries to search for.", "default": [ "manager", "founder" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "customDomains": { "title": "Enter Custom Email Domains (e.g. @gmail.com, @yahoo.com)", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com", "@yahoo.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "Enter Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.", "default": 20 } } }, "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 } } } } } } } } } } ```