# Booking Com Email Scraper (`solid-scraper/booking-com-email-scraper`) Actor 📧 Extract verified email leads from Booking.com with a smart scraper—find targeted contacts by keyword, location & category. Perfect for outreach, sales teams & agencies seeking fresh B2B leads fast. 🚀 - **URL**: https://apify.com/solid-scraper/booking-com-email-scraper.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 🔍 **Booking.com Email Scraper** automates the process of scraping email addresses from Booking.com profiles using your chosen keywords and email-domain filters. If you need a **Booking.com email scraper tool** for lead generation, this actor helps you extract relevant contacts at scale—so you don’t waste hours on manual outreach research. Whether you’re looking for a **Booking.com email finder**, planning **Booking.com scrape emails**, or building a **booking.com email list builder**, you’ll find it useful for collecting business-facing emails from publicly available profile bios and content related to your keywords. Whether you’re a marketer, data analyst, or researcher, this tool enables faster data collection and saving you hours of manual work. --- ### Why choose Booking.com Email Scraper? | Feature | Benefit | |---|---| | ✅ **Keyword-based email discovery** | Finds emails from Booking.com bios and posts related to your keywords, helping you focus on what matters | | ✅ **Custom email-domain targeting** | Use custom domains (like `@gmail.com`) to narrow results to the contact types you want | | ✅ **Reliability-focused scraping engines** | Choose between **Cost Effective (New)** and **Legacy** engines depending on your speed vs. reliability needs | | ✅ **Resilience with retries and fallbacks** | Includes retries and fallback logic to improve results when pages return few or no results | | ✅ **Structured JSON output per match** | Each discovered email is pushed as a structured dataset row for easy export and analysis | | ✅ **Scale controls to manage runtime** | Use `maxEmails` to stop once you’ve collected enough leads—helping control scraping time and costs | --- ### Key features - 🔑 **Accurate email extraction from profile text**: Extracts email addresses from Booking.com profile bios using your configured keyword and domain filters - 🧰 **Flexible input targeting**: Combine `keywords` with an optional `location` filter to help narrow the relevant Booking.com profiles you’re scanning - 🎯 **Custom email-domain filtering**: Limits extracted results to your selected `customDomains` (for example `@gmail.com`) to improve lead relevance - 🛡️ **Engine choice for better outcomes**: Switch between **Cost Effective (New)** and **Legacy** engines via the `engine` input - 🔄 **Retry and fallback logic for low-result scenarios**: Designed to keep going when pages return no results or fail, improving overall yield - 💾 **Real-time dataset saving**: Pushes each found email record immediately so you don’t lose progress during long runs - 🧠 **De-duplication to avoid repeated emails**: Tracks `seen_emails` so the actor doesn’t push the same email multiple times - 📊 **Pagination with stop conditions**: Stops when it reaches `maxEmails` or when it determines there are no more useful pages to extract --- ### Input Provide input via an `input.json` file. Example structure: ```json { "keywords": ["hotel", "property"], "location": "Berlin", "platform": "Booking.com", "customDomains": ["@gmail.com", "@outlook.com"], "maxEmails": 50, "engine": "legacy", "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Key | Required | Description | |---|---:|---| | `keywords` | ✅ | A list of keywords to search for. The scraper uses these keywords to find Booking.com profile bios and posts that are related to what you’re targeting. | | `location` | ❌ | Location to filter search results. Leave it empty (`""`) to avoid location filtering. | | `platform` | ❌ | Select platform. The only supported value is `Booking.com`. | | `customDomains` | ❌ | List of custom email domains to target (for example `@gmail.com`). The scraper filters extracted emails so you only collect emails that match these domains. | | `maxEmails` | ❌ | Maximum number of emails to collect. The scraper stops once this limit is reached (note: higher limits may increase runtime and still don’t guarantee you’ll reach the exact number). | | `engine` | ❌ | Choose scraping engine. `cost-effective` (Cost Effective (New)) is designed for faster, cheaper scraping, while `legacy` (Legacy) is designed to be more reliable but slower and more expensive. | | `proxyConfiguration` | ❌ | Configure proxies for this Actor (your proxy settings). This affects how the actor makes network requests during the run. | *** ### Output The actor saves each discovered email record in JSON format (as dataset rows). Sample output row: ```json { "network": "Booking.com.com", "keyword": "hotel", "title": "No title", "description": "No data", "url": "No URL", "email": "example@gmail.com", "proxyGroups": ["GOOGLE_SERP"] } ``` #### Output Fields | Field | Type | Description | |---|---|---| | `network` | string | Source network label for the record (`"Booking.com.com"`). | | `keyword` | string | The keyword currently being used for discovery. | | `title` | string | Title text associated with the extracted item (may be `"No title"` if missing). | | `description` | string | Description/bio text from which the email was extracted (may be `"No data"` if missing). | | `url` | string | The URL associated with the extracted item (may be `"No URL"` if missing). | | `email` | string | The extracted email address that matched your domain filters. | | `proxyGroups` | array | The proxy group(s) associated with the run (logged as `user_proxy_group` in the actor code). | If your run finds no new emails before the stopping conditions are met, you simply won’t see additional rows in the dataset. *** ### How to use Booking.com Email Scraper (via Apify Console) 1. **Open Apify Console** 🌐\ Log in at https://console.apify.com and go to the **Actors** tab. 2. **Find the actor**\ Search for **Booking.com Email Scraper** in the marketplace and open the actor page. 3. **Go to the INPUT section** ✍️\ Paste your `input.json` using the built-in form or upload/input text—this actor expects the fields described in the **Input** section above. 4. **Set your targeting controls** 🎯\ Start with `keywords` (required). Optionally add `location` to filter results. Add `customDomains` to collect only the email domains you care about. 5. **Choose your engine** ⚙️\ Use `engine` to select **Cost Effective (New)** (`cost-effective`) or **Legacy** (`legacy`) depending on whether you prefer faster cost-effective scraping or the more reliable (but slower) approach. 6. **Configure proxies if needed** 🛡️\ If you want to control routing, adjust `proxyConfiguration`. For large runs, proxy support can help keep results stable. 7. **Run the actor** ▶️\ Click **Run**. During execution, you’ll see logs about progress and when the actor stops due to the `maxEmails` limit or low-result conditions. 8. **Open results & export** 📦\ After the run, open the **OUTPUT** tab, view the dataset, and export as **JSON** or **CSV** (via the Apify dataset tools). No coding required—get accurate results in minutes. *** ### Advanced features & SEO optimization - 🚦 **Engine tuning for Booking.com email harvesting software**: The `engine` input lets you choose **Cost Effective (New)** (`cost-effective`) or **Legacy** (`legacy`) to fit your workload, aligning with **Booking.com scrape emails** and **booking.com email list builder** use cases - 🔎 **Keyword + domain precision**: Designed to excel at **booking.com contact email scraper** workflows by combining `keywords` with `customDomains` - 📌 **Progress persistence for long runs**: Saves progress continuously using a key-value store, helping long jobs resume reliably - 📝 **Structured output for downstream enrichment**: Every discovered email is pushed with `network`, `keyword`, `title`, `description`, `url`, `email`, and `proxyGroups`, making it straightforward to feed into CRMs or analysis pipelines - 🕒 **Operational guidance for large searches**: Large searches or high email limits may take longer; you can increase the timeout in Run Options (default noted as 3600 s / 1 hr) for bigger jobs *** ### Best use cases - 📈 **B2B lead generation for property-related outreach**: Build a targeted **booking.com email finder** list by extracting emails that match your keyword strategy and chosen domains - 🧪 **Market research by niche and location**: Use `keywords` and `location` to compare contact patterns across regions while generating a consistent email dataset - 🎯 **Email list building with domain filtering**: Create cleaner outreach lists using `customDomains` so you only keep emails from the domains you prefer - 🗂️ **Data analysis and enrichment pipelines**: Feed structured dataset rows into spreadsheets, databases, or analyst workflows to analyze how contact info varies by keyword - 🧑‍💻 **Automation for CRM imports**: Use the JSON records to automate **Booking.com lead generation email scraper** exports into marketing systems - 🏢 **Business contact discovery**: Support **booking.com business contact email scraper** efforts by extracting business-facing emails found in profile bios and related content *** ### Technical specifications - **Supported Input Formats** - ✅ `keywords` (array of strings) - ✅ Optional `location` (string) - ✅ Optional `platform` (select; `Booking.com`) - ✅ Optional `customDomains` (array of strings, e.g. `@gmail.com`) - ✅ Optional `maxEmails` (integer, min `1`, max `10000`, default `20`) - ✅ Optional `engine` (`cost-effective` or `legacy`, default `legacy`) - ✅ Optional `proxyConfiguration` (object) - **Proxy Support** - ✅ Yes—supports configuring proxies via `proxyConfiguration`, and you can choose an engine that changes how the actor behaves during scraping - **Retry Mechanism** - ✅ Yes—includes retries and logic to handle low-result scenarios and failures for better resilience - **Dataset Structure** - ✅ Each discovered email is pushed as a dataset row with: - `network`, `keyword`, `title`, `description`, `url`, `email`, `proxyGroups` - **Rate Limits & Performance** - ✅ Performance depends on search size and email limits; large searches and high limits may take longer - ✅ You can increase the timeout in Run Options for larger jobs (default mentioned in the actor input description: 3600 s / 1 hr) - **Limitations** - ❌ The scraper cannot guarantee it will reach `maxEmails`; setting higher limits increases potential runtime without guaranteeing results - ❌ Results may be low if the chosen `keywords`, `customDomains`, or target scope are too narrow—broadening keywords and domains may help *** ### FAQ #### Do I need to provide all input fields? No. `keywords` is the only required input field. Everything else (`location`, `platform`, `customDomains`, `maxEmails`, `engine`, and `proxyConfiguration`) is optional and helps you refine targeting and runtime. #### What does the Booking.com Email Scraper extract? ✅ It extracts email addresses that match your configured `customDomains` from text content on Booking.com profiles and related bios/posts that are connected to your `keywords`. #### Can I limit how many emails the actor collects? ✅ Yes. Use `maxEmails` to set a maximum number of emails to collect. The actor stops once it reaches that limit, though reaching the exact number is not guaranteed. #### What are `customDomains` used for? `customDomains` are email-domain filters. For example, if you include `@gmail.com`, the actor will only keep extracted emails whose domain matches your list—helpful when you’re building a cleaner **booking.com contact information** workflow. #### Which engine should I choose? Use `engine` to switch between `cost-effective` (Cost Effective (New)) and `legacy` (Legacy). If you want faster, cheaper scraping, try `cost-effective`. If you prioritize reliability, choose `legacy`. #### How do I get the results? After the run completes, open the **OUTPUT** tab in Apify Console and download/export the dataset. The actor pushes each found email row immediately in JSON-friendly structure for easy analysis and CRM import. #### Is there a way to retry or continue long runs? The actor saves progress while it runs, which helps for long jobs. If results are low, the input guidance recommends re-running with broader keywords and more related terms or more domains. #### Where can I request a feature or custom solution? For custom solutions or feature requests, contact . *** ### Support & feature requests Want to improve your **Booking.com Email Scraper** workflow? We’re happy to hear what you’re trying to achieve. - 💡 **Feature Requests**: Examples include better export formats (e.g., CSV improvements), additional filtering options, or CRM-ready output structures for **booking.com email list builder** use cases. - 📧 **Contact**: Reach out at . Your feedback helps shape future updates to Booking.com email harvesting software. *** ### Disclaimer **This tool only accesses publicly accessible sources** and extracts information that is available on Booking.com profiles/bios and related publicly visible content. It does not access private profiles, authenticated data, or password-protected pages. It’s your responsibility to comply with applicable laws (including GDPR/CCPA where relevant), platform terms of service, and spam/email regulations. For data removal requests, contact . Please use this actor responsibly, ethically, and for legitimate purposes only. *Get the most comprehensive, SEO-optimized Booking.com Email Scraper results—built for scale.* # 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 ## `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. ## `engine` (type: `string`): Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `proxyConfiguration` (type: `object`): Configure proxies for this Actor. ## Actor input object example ```json { "keywords": [ "hotel" ], "location": "", "platform": "Booking.com", "customDomains": [ "@gmail.com" ], "maxEmails": 20, "engine": "legacy" } ``` # 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": [ "hotel" ], "location": "", "customDomains": [ "@gmail.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/booking-com-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": ["hotel"], "location": "", "customDomains": ["@gmail.com"], } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/booking-com-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": [ "hotel" ], "location": "", "customDomains": [ "@gmail.com" ] }' | apify call solid-scraper/booking-com-email-scraper --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", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Booking Com Email Scraper", "description": "📧 Extract verified email leads from Booking.com with a smart scraper—find targeted contacts by keyword, location & category. Perfect for outreach, sales teams & agencies seeking fresh B2B leads fast. 🚀", "version": "0.0", "x-build-id": "E51kl14xB9tut0Pkp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~booking-com-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-booking-com-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~booking-com-email-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-booking-com-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~booking-com-email-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-booking-com-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "hotel" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "platform": { "title": "Platform", "enum": [ "Booking.com" ], "type": "string", "description": "Select platform.", "default": "Booking.com" }, "customDomains": { "title": "Custom Email Domains", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "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 }, "engine": { "title": "Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "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 } } } } } } } } } } ```