# Airbnb Experiences Scraper · Host Email & Phone Finder (`corent1robert/airbnb-experiences-scraper`) Actor Search Airbnb Experiences by city — title, host, price, rating, duration, category, languages. Export-ready dataset for market research, competitive intel, and tour operator lead gen. - **URL**: https://apify.com/corent1robert/airbnb-experiences-scraper.md - **Developed by:** [Corentin Robert](https://apify.com/corent1robert) (community) - **Categories:** Lead generation, Travel, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.49 / 1,000 experiences This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Airbnb Experiences Scraper — Host Email & Phone Finder Extract Airbnb Experiences in any city and automatically find the host's **email address and phone number** via AI-powered Google search and website crawling. Get title, price, rating, meeting point, address, and contact info ready for outreach — no Airbnb login, no API key. --- ### Who is this for? | You are… | Typical goal | Suggested setup | |----------|-------------|-----------------| | **Tour operator / travel agency** | Benchmark competitors, spot pricing gaps | City search, all categories, `maxExperiences: 0` | | **Activity platform** (GetYourGuide, Viator) | Monitor competitor supply in key markets | Multiple cities, category filter, scheduled run | | **B2B supplier** (catering, transport, venues) | Find popular experience hosts for partnership outreach | City search + **Enrich details** + **Find host email** | | **Outbound / SDR team** | Build a cold outreach list of experience operators | City search + enrichment ON — export `host_email` + `host_name` | | **Market researcher** | Map experience supply, pricing, and categories by city | Multiple cities, no cap, export full dataset | | **Experience host / entrepreneur** | Validate a new concept against existing supply | City search + category filter, sort by `review_count` | **What you get by default:** title, host name, price per person (local currency), rating, review count, duration, category, cover photo, and a direct experience URL — for every experience visible on Airbnb's public search pages. **Enable enrichment** when you need the meeting point address, next available date, and optionally the host's external website and email for outreach. --- ### What it extracts #### Base fields (always collected) | Field | Description | |-------|-------------| | `experience_id` | Unique Airbnb experience ID | | `title` | Experience title | | `description_short` | First ~300 characters of the description | | `category` | Category (Cooking, Cultural tours, Landmarks, etc.) | | `price_per_person` | Price per person in local currency | | `currency` | Currency code — auto-detected from city country (EUR for France, GBP for UK…) | | `duration_hours` | Duration in decimal hours (1.5 = 1h 30min) | | `rating` | Average star rating | | `review_count` | Number of published reviews | | `host_name` | Host display name | | `badges` | Badges shown on the card (Popular, Original, etc.) | | `is_business_host` | True when the host operates as a business entity | | `is_online` | True for online/virtual experiences | | `cover_photo_url` | Main experience photo URL | | `url` | Direct link to experience page | | `city` | City searched | | `scraped_at` | ISO timestamp of extraction | #### With **Enrich details** ON | Field | Description | |-------|-------------| | `address_locality` | City from experience page (e.g. `Paris`) | | `address_region` | Region (e.g. `Île-de-France`) | | `address_country` | Country (e.g. `France`) | | `meeting_point` | Exact meeting location as communicated to guests (e.g. `2 Port de Suffren`) | | `next_available_date` | Next bookable date (`YYYY-MM-DD`) | | `description_full` | Full description text | #### With **Find host website & email** ON | Field | Description | |-------|-------------| | `host_website` | Host's external website, discovered via Google search and content verification | | `host_email` | Found email address, validated by AI | | `host_email_score` | AI confidence score (0–100) — emails below threshold are dropped | | `host_email_source` | How the email was found (`google-snippet`, `google-contact`, `crawl`) | | `host_phone` | Phone number extracted from the host's website or Google snippets | --- ### Typical fill rates Reference run: **50 Paris experiences**, May 2026, enrichment ON. | Field | Typical fill | Notes | |-------|-------------|-------| | `title`, `rating`, `review_count`, `price_per_person` | **100%** | From search cards | | `host_name` | **~95%** | A few anonymous listings | | `meeting_point` | **~80%** | Present when the host fills in their meeting point — missing on some online/virtual experiences | | `address_locality` / `address_region` | **~95%** | From JSON-LD on detail page | | `next_available_date` | **~90%** | Missing if fully booked or inactive | | `host_website` | **~25-35%** | Hosts with a detectable online footprint | | `host_email` (score >= 70) | **~15-25%** | Higher for business operators with a dedicated website | | `host_phone` | **~10-20%** | Phones published on the host website or visible in Google snippets | --- ### Quick start 1. Open the Actor in Apify Console and click **Try**. 2. Paste one or more cities (`Paris, France`) or Airbnb Experience URLs in the **Cities or Experience URLs** field. 3. Set **Max experiences per city** (`50` for a quick test, `0` for all). 4. Enable **Find host website & email** if you need contact info. 5. Click **Start** — results appear in the **Dataset** tab as they are collected. --- ### Input reference #### Console fields | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `targets` | string[] or URL[] | — | Cities (`Paris, France`) or Airbnb Experience URLs — one per line, auto-detected | | `maxExperiences` | integer | `0` | Max results per city. `0` = no cap | | `category` | string | all | Category filter | | `enrichContact` | boolean | `false` | Find host website, email, and phone | #### API-only keys (not shown in Console form) Pass these in JSON input when calling via API: | Key | Type | Default | Description | |-----|------|---------|-------------| | `currency` | string | auto | Currency override (e.g. `USD`). Default: auto-detected from city country | | `minRating` | number | — | Minimum star rating filter (e.g. `4.5`) | | `language` | string | — | Language filter (e.g. `English`, `French`) | | `minEmailScore` | integer | `70` | AI confidence threshold for email acceptance (0-100) | #### Input JSON example — city search ```json { "targets": ["Paris, France", "Barcelona, Spain"], "maxExperiences": 100, "category": "food_and_drink", "enrichContact": true } ```` #### Input JSON example — direct URLs ```json { "targets": [ "https://www.airbnb.com/experiences/12345", "https://www.airbnb.com/experiences/67890" ], "enrichContact": true } ``` *** ### Output sample ```json { "experience_id": "6785604", "url": "https://www.airbnb.com/experiences/6785604", "title": "Fast-Access Seine River Cruise from Eiffel Tower", "description_short": "Board an eco-friendly electric boat at the Eiffel Tower and uncover the history of Paris' iconic bridges and monuments with live guide narration.", "category": "Cultural tours", "price_per_person": 21, "currency": "EUR", "duration_hours": 1, "rating": 4.68, "review_count": 635, "host_name": "Vedettes De Paris", "badges": "Popular", "is_business_host": false, "is_online": false, "city": "Paris, France", "address_locality": "Paris", "address_region": "Île-de-France", "address_country": "France", "meeting_point": "2 Port de Suffren", "next_available_date": "2026-06-01", "host_website": "https://vedettesdeparis.fr", "host_email": "info@vedettesdeparis.com", "host_email_score": 91, "host_email_source": "crawl", "host_phone": "+33 (0)1 44 59 84 04", "cover_photo_url": "https://a0.muscache.com/im/pictures/Mt/MtTemplate-6785604/original/d19a8935-1762-403c-ad39-05b59bce45fc.jpeg", "scraped_at": "2026-06-01T08:30:00.000Z" } ``` *** ### How it works 1. **Build search URL** from the city input with local currency auto-detection. 2. **Fetch search page** via plain HTTP — no browser, no Airbnb login. 3. **Parse `niobeClientData`** from the page's embedded JSON (Airbnb's server-side data payload). 4. **Extract and normalize** each experience card into a flat row. 5. **Paginate** via cursor until all results are collected or the cap is reached. 6. *(With Enrich details ON)* Visit each experience page once — extract meeting point, address, next date, and full description from structured JSON-LD. 7. *(With Find host email ON)* For each unique host: Google via autom.dev to find their website and email, crawl the site, validate the email with GPT-4o mini, and extract any phone number from the page content. 8. **Export** rows to the Apify dataset progressively as each page is processed. All steps are **HTTP-only** — no browser, no Airbnb account required. *** ### Performance and cost Reference timings: Paris, May 2026, 1024 MB. | Scenario | Experiences | Wall time | Notes | |----------|-------------|-----------|-------| | City search only | 50 | ~5s | Search cards, no detail pages | | + Enrich details | 50 | ~35s | 1 detail page per experience | | + Find host email | 50 | ~3–5 min | 2–4 Google searches + optional crawl per host | **PPE pricing:** `enrichContact: true` bills at **$0.05 per host enrichment attempt**, regardless of whether an email is found. The base search + detail enrichment runs on standard Apify compute (typically < $0.01 for 50 results). | Run type | Approx. cost | |----------|-------------| | 50 experiences, search only | < $0.01 | | 50 experiences + details | < $0.02 | | 50 experiences + details + contact enrichment | ~$2.50 | *** ### Important notes - **Public data only** — reads the same pages visible to any browser without an account. - **Online experiences** are included and flagged with `is_online: true`. - **Meeting point** is as provided by the host — it may be a full street address, a landmark name, or a neighbourhood. - **Currency** is auto-detected from the search city (France → EUR, USA → USD, UK → GBP). Override with `currency` in API input. - **Email enrichment** uses external APIs (autom.dev for Google search, OpenAI for validation) — both are configured server-side; no API key required from you. *** ### Airbnb Actors suite (corent1robert) | Step | Actor | Best for | |------|-------|----------| | **Discover pro hosts** | [Airbnb Professional Host Scraper](https://apify.com/corent1robert/airbnb-professional-host-scraper) | City search, pro host contacts (email, phone, company, SIRET) | | **Map host portfolios** | [Airbnb Host Portfolio Scraper](https://apify.com/corent1robert/airbnb-host-portfolio-scraper) | Listing count, geo, review sample, optional business contact | | **Deep listing data** | [Airbnb Property Details Scraper](https://apify.com/corent1robert/airbnb-property-details-scraper) | Amenities, GPS, photos, pricing context, 30+ fields | | **Experiences** | **Airbnb Experiences Scraper** *(this Actor)* | Experiences by city — host name, price, meeting point, email | | **All reviews** | [Airbnb Reviews Scraper](https://apify.com/corent1robert/airbnb-reviews-scraper) | Every review on a listing — rating, comment, date, host reply | *** ### Support Questions or custom scraping needs? Contact # Actor input Schema ## `targets` (type: `array`): **City names** — format: `City, Country` (the country is required). Examples: • `Paris, France` • `New York, United States` • `Barcelona, Spain` **Experience URLs** — paste any Airbnb Experience URL: • `https://www.airbnb.com/experiences/12345` You can mix cities and URLs in the same list. ## `maxExperiences` (type: `integer`): Maximum number of experiences to collect per city. **0 or empty = no limit** — collects everything available (may take several minutes on large cities). ## `category` (type: `string`): Only collect experiences in this category. Leave empty for all categories. ## `enrichContact` (type: `boolean`): **Checked:** Search for the host's external website, email address, and phone number via Google + AI validation. Billed at **$0.05 per host** (Pay-Per-Event) — only when this option is enabled. ## Actor input object example ```json { "targets": [ "Paris, France" ], "maxExperiences": 0, "category": "", "enrichContact": false } ``` # Actor output Schema ## `dataset` (type: `string`): All scraped experiences with full field set ## `overview` (type: `string`): Title, category, price, rating, reviews, host, city ## `runLog` (type: `string`): Live progress log with phase stats # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "targets": [ "Paris, France" ] }; // Run the Actor and wait for it to finish const run = await client.actor("corent1robert/airbnb-experiences-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "targets": ["Paris, France"] } # Run the Actor and wait for it to finish run = client.actor("corent1robert/airbnb-experiences-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 '{ "targets": [ "Paris, France" ] }' | apify call corent1robert/airbnb-experiences-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=corent1robert/airbnb-experiences-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Airbnb Experiences Scraper · Host Email & Phone Finder", "description": "Search Airbnb Experiences by city — title, host, price, rating, duration, category, languages. Export-ready dataset for market research, competitive intel, and tour operator lead gen.", "version": "1.0", "x-build-id": "rUqNQIdgbu6UfWYV9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/corent1robert~airbnb-experiences-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-corent1robert-airbnb-experiences-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/corent1robert~airbnb-experiences-scraper/runs": { "post": { "operationId": "runs-sync-corent1robert-airbnb-experiences-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/corent1robert~airbnb-experiences-scraper/run-sync": { "post": { "operationId": "run-sync-corent1robert-airbnb-experiences-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "targets": { "title": "Cities or Experience URLs", "type": "array", "description": "**City names** — format: `City, Country` (the country is required).\n\nExamples:\n• `Paris, France`\n• `New York, United States`\n• `Barcelona, Spain`\n\n**Experience URLs** — paste any Airbnb Experience URL:\n\n• `https://www.airbnb.com/experiences/12345`\n\nYou can mix cities and URLs in the same list.", "items": { "type": "string" } }, "maxExperiences": { "title": "Max experiences per city (0 = no limit)", "minimum": 0, "type": "integer", "description": "Maximum number of experiences to collect per city. **0 or empty = no limit** — collects everything available (may take several minutes on large cities).", "default": 0 }, "category": { "title": "Category filter", "enum": [ "", "art_and_culture", "food_and_drink", "nature_and_outdoors", "sightseeing", "sports", "entertainment", "wellness" ], "type": "string", "description": "Only collect experiences in this category. Leave empty for all categories.", "default": "" }, "enrichContact": { "title": "Find host website, email & phone", "type": "boolean", "description": "**Checked:** Search for the host's external website, email address, and phone number via Google + AI validation. Billed at **$0.05 per host** (Pay-Per-Event) — only when this option is enabled.", "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 } } } } } } } } } } ```