# Agoda Activities Reviews Scraper (`stealth_mode/agoda-activities-reviews-scraper`) Actor Scrape reviews from Agoda Activities detail pages in bulk. Collect review text, scores, author info, media, replies, and more — up to 200 items per URL, with flexible sorting and pagination support. - **URL**: https://apify.com/stealth\_mode/agoda-activities-reviews-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Automation, Developer tools, Travel - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results 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 ## Agoda Activities Reviews Scraper: Extract Reviews & Ratings **Excerpt:** Scrape reviews from Agoda Activities detail pages in bulk. Collect review text, scores, author info, media, replies, and more — up to 200 items per URL, with flexible sorting and pagination support. --- ### What Is Agoda Activities? Agoda is a major travel booking platform operating across Asia and globally. Beyond hotels, its **Activities** section lists tours, experiences, and attractions that travelers can book directly. Each activity accumulates user-generated reviews — a valuable source of sentiment data, quality signals, and traveler insights. Manually collecting this review data at scale is impractical. The **Agoda Activities Reviews Scraper** automates extraction from activity detail pages, returning clean, structured records ready for analysis or integration. --- ### Overview This scraper targets Agoda activity detail pages and extracts all available review content. It is useful for: - **Travel businesses** monitoring competitor activity ratings - **Data analysts** building sentiment or NLP datasets from travel reviews - **Tour operators** benchmarking their reputation against similar offerings - **Researchers** studying traveler behavior and experience patterns It supports pagination, sorting options, and graceful failure handling for bulk runs. --- ### Input Format ```json { "urls": [ "https://www.agoda.com/activities/detail?activityId=974450&cityId=15470&cid=1922896&tag=7adbeb35-4108-414c-9559-32893b4cdfe5¤cy=USD#activity-nav-tabs-panel-8" ], "sort_by": "Default", "page": 3, "max_items_per_url": 200, "ignore_url_failures": true } ```` #### Input Fields | Field | Type | Description | |---|---|---| | `urls` | Array of strings | URLs of Agoda activity detail pages to scrape. Add one per line or use bulk edit. Must point to a valid `/activities/detail?activityId=...` page. | | `sort_by` | String (select) | Controls review sort order. Options: `Default`, `ReviewDateTime-Descending` *(Newest)*, `Rating-Descending` *(Score high to low)*, `Rating-Ascending` *(Score low to high)*. | | `page` | Integer | Page number to start scraping from. Use `1` to begin from the first page, or a higher value to resume mid-dataset. Default prefill: `1`. | | `max_items_per_url` | Integer | Maximum number of reviews to collect per URL. Default: `20`. Can be increased up to your needs (e.g., `200` for broader coverage). | | `ignore_url_failures` | Boolean | If `true`, the scraper skips failed URLs and continues the run instead of stopping. Recommended for bulk runs. | > **Tip:** To collect the most recent reviews, set `sort_by` to `ReviewDateTime-Descending` and `page` to `1`. *** ### Output Format #### Sample Output Record ```json { "review_id": 18987181, "review_source": "VIATOR", "author_name": "Adeer_S", "title": " 💯 Recommend", "review_text": "We had such a a good time. The cruise was amazing, the food was delicious and seeing the Eiffel Tower lit up was so gorgeous!!! 💯 Recommend!!!", "review_date_time": "2025-10-13T15:23:37", "review_score": 5, "helpful_vote_count": 0, "is_translation_required": true, "media": [], "replies": [], "from_url": "https://www.agoda.com/vi-vn/activities/detail?activityId=974450&cityId=15470&cid=1922896&tag=7adbeb35-4108-414c-9559-32893b4cdfe5¤cy=USD#activity-nav-tabs-panel-8" } ``` Each record represents one user review with the following fields: #### Review Identity | Field | Meaning | |---|---| | `Review ID` | Unique internal identifier for the review | | `Review Source` | Platform or channel the review was submitted through (e.g., Agoda, third-party) | | `Title` | Review headline written by the author | | `Review Text` | Full body text of the review | | `Review Date Time` | Timestamp of when the review was submitted | #### Author & Engagement | Field | Meaning | |---|---| | `Author Name` | Display name of the reviewer | | `Review Score` | Numeric rating given by the reviewer (typically on a 1–10 scale) | | `Helpful Vote Count` | Number of users who marked the review as helpful | | `Is Translation Required` | Boolean flag indicating if the review is in a language different from the display locale | #### Media & Responses | Field | Meaning | |---|---| | `Media` | Array of image or video URLs attached to the review, if any | | `Replies` | Responses from the activity provider or Agoda to the review | *** ### How to Use 1. **Get activity URLs** — Open an Agoda activity page (e.g., a tour or experience), copy the full URL from your browser including the `activityId` parameter. 2. **Configure input** — Paste URLs into the `urls` array. Set `sort_by`, `page`, and `max_items_per_url` to match your collection goal. 3. **Run the scraper** — Start the actor and monitor progress in the run log. 4. **Export** — Download results as JSON, CSV, or Excel. **Tips & best practices:** - Use `sort_by: "ReviewDateTime-Descending"` to always capture the freshest reviews first. - For large activities with hundreds of reviews, increase `max_items_per_url` and use `page` to paginate across the full dataset. - Set `ignore_url_failures: true` when running multiple URLs to avoid interruptions from occasional page errors. *** ### Use Cases & Business Value - **Sentiment analysis:** Feed `Review Text` and `Review Score` into NLP pipelines to classify traveler satisfaction - **Reputation monitoring:** Track score trends over time for specific activities or destinations - **Competitor benchmarking:** Compare rating distributions across similar offerings in the same city - **Content research:** Identify common praise or complaints to improve service descriptions *** ### Conclusion The **Agoda Activities Reviews Scraper** turns traveler reviews into structured, actionable data. With support for sorting, pagination, and bulk URL handling, it adapts to both targeted lookups and large-scale research projects. Start scraping today to unlock the review intelligence hidden across Agoda's activity catalog. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the Activities details urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `sort_by` (type: `string`): Select your option to sort reviews ## `page` (type: `integer`): Page to start from ## `ignore_url_failures` (type: `boolean`): If true, the scraper will continue running even if some URLs fail to be scraped. ## `max_items_per_url` (type: `integer`): The maximum number of items to scrape per URL. ## Actor input object example ```json { "urls": [ "https://www.agoda.com/activities/detail?activityId=974450&cityId=15470&cid=1922896&tag=7adbeb35-4108-414c-9559-32893b4cdfe5¤cy=USD#activity-nav-tabs-panel-8" ], "page": 1, "ignore_url_failures": true, "max_items_per_url": 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 = { "urls": [ "https://www.agoda.com/activities/detail?activityId=974450&cityId=15470&cid=1922896&tag=7adbeb35-4108-414c-9559-32893b4cdfe5¤cy=USD#activity-nav-tabs-panel-8" ], "page": 1, "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("stealth_mode/agoda-activities-reviews-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 = { "urls": ["https://www.agoda.com/activities/detail?activityId=974450&cityId=15470&cid=1922896&tag=7adbeb35-4108-414c-9559-32893b4cdfe5¤cy=USD#activity-nav-tabs-panel-8"], "page": 1, "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/agoda-activities-reviews-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 '{ "urls": [ "https://www.agoda.com/activities/detail?activityId=974450&cityId=15470&cid=1922896&tag=7adbeb35-4108-414c-9559-32893b4cdfe5¤cy=USD#activity-nav-tabs-panel-8" ], "page": 1, "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/agoda-activities-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/agoda-activities-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Agoda Activities Reviews Scraper", "description": "Scrape reviews from Agoda Activities detail pages in bulk. Collect review text, scores, author info, media, replies, and more — up to 200 items per URL, with flexible sorting and pagination support.", "version": "0.0", "x-build-id": "AJSKKM1mynPNYHgGp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~agoda-activities-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-agoda-activities-reviews-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~agoda-activities-reviews-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-agoda-activities-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~agoda-activities-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-agoda-activities-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "urls": { "title": "URLs of the Activities details urls to scrape", "type": "array", "description": "Add the URLs of the Activities details urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.", "items": { "type": "string" } }, "sort_by": { "title": "Sort by", "enum": [ "Default", "ReviewDateTime-Descending", "Rating-Descending", "Rating-Ascending" ], "type": "string", "description": "Select your option to sort reviews" }, "page": { "title": "Page", "type": "integer", "description": "Page to start from" }, "ignore_url_failures": { "title": "Continue running even if some URLs fail to be scraped", "type": "boolean", "description": "If true, the scraper will continue running even if some URLs fail to be scraped." }, "max_items_per_url": { "title": "Max items per URL", "type": "integer", "description": "The maximum number of items to scrape per URL." } } }, "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 } } } } } } } } } } ```