# Klook Reviews Scraper (`stealth_mode/klook-reviews-scraper`) Actor Scrape verified traveler reviews from Klook.com including ratings, review content, user info, check-in details, and images. Perfect for hospitality businesses, travel analysts, and reputation management teams needing structured review data. - **URL**: https://apify.com/stealth\_mode/klook-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 ## Klook.com Reviews Scraper: Extract Hotel & Activity Reviews at Scale --- ### What Is Klook.com? Klook is a leading travel experiences and accommodation booking platform serving millions of travelers across Asia and beyond. Its review system contains verified, post-stay feedback on hotels, tours, and activities — making it a valuable source for sentiment analysis, competitive benchmarking, and reputation monitoring. Manually collecting this data is impractical at scale; the **Klook Reviews Scraper** automates the extraction into clean, structured records. --- ### Overview The **Klook.com Reviews Scraper** targets review pages for both hotels and activities, collecting rich traveler feedback data. Designed for: - **Hotel & attraction managers** monitoring guest sentiment - **Travel analysts** tracking rating trends over time - **Researchers** studying traveler behavior and language patterns - **OTA aggregators** building review datasets across platforms It supports sorting options, pagination control, and configurable item limits — giving you precise control over what data is collected. --- ### Input Format The scraper accepts a JSON configuration: ```json { "ignore_url_failures": true, "max_items_per_url": 200, "page": 1, "item_id": "285841", "sort_by": "sort_most_relevant", "type": "hotels" } ```` #### Field Reference | Field | Type | Description | |---|---|---| | `item_id` | `string` | The numeric ID found in the Klook URL. Examples: `en-US/activity/107259-parapharmacie-monge.../` → `107259`; `hotels/detail/285841-hotel-gracery-shinjuku/` → `285841` | | `type` | `string` | Type of listing. Accepted values: `"activity"` or `"hotels"` | | `sort_by` | `string` | Sort order for reviews. Options: `"sort_most_relevant"` (Relevant), `"sort_review_time_desc"` (Newest), `"sort_score_high_to_low"`, `"sort_score_low_to_high"` | | `page` | `integer` | Page number to start scraping from. Defaults to `1` | | `max_items_per_url` | `integer` | Maximum reviews to collect per run. Default: `20`; set higher (e.g., `200`) for bulk collection | | `ignore_url_failures` | `boolean` | If `true`, skips failed requests instead of stopping the run. Recommended: `true` for reliability | > **Tip:** To find an `item_id`, open a Klook hotel or activity page and extract the number from the URL path (e.g., `.../285841-hotel-name/` → `285841`). *** ### Output Format #### Sample Record (Abbreviated) ```json { "review_id": 14215787, "user_info": { "user_name": "LAM ********", "user_avatar": "https://cdn.klook.com/upload/img200X200/7030dc178eb8486b5869aee21b7eb986.jpg", "user_rating": "5.0", "rating_desc": "", "rating_time": "2024-12-01T05:41:48.000Z" }, "review_content": "當日剛巧還遇上Black Friday Sale, 部份產品還可以用上這張購物優惠券，購物滿100歐元後還可以退稅", "translate_content": "..", "has_reply": false, "show_translation": true, "has_liked": false, "liked_count": 0, "product_info": { "id": 362471, "product_name": "Shopping coupon", "deeplink": "", "is_booking_now": true }, "review_image_list": [ { "id": 16351779, "resize_url": "https://cdn.klook.com/user_review/product/1947978/120e330f-ba51-44af-72d1-c1d62882df0c.250*0.jpeg", "url": "https://cdn.klook.com/user_review/product/1947978/120e330f-ba51-44af-72d1-c1d62882df0c.1200*0.jpeg" }, { "id": 16351778, "resize_url": "https://cdn.klook.com/user_review/product/1947978/5874823f-d846-487e-4b4c-4fb9c96c47e4.0*250.jpeg", "url": "https://cdn.klook.com/user_review/product/1947978/5874823f-d846-487e-4b4c-4fb9c96c47e4.0*1200.jpeg" }, { "id": 16351782, "resize_url": "https://cdn.klook.com/user_review/product/1947978/13ece126-d143-4021-516e-d13fd58223d1.0*250.jpeg", "url": "https://cdn.klook.com/user_review/product/1947978/13ece126-d143-4021-516e-d13fd58223d1.0*1200.jpeg" }, { "id": 16351777, "resize_url": "https://cdn.klook.com/user_review/product/1947978/9ba8b1aa-0a84-4b41-6a3b-1710d87d48ec.0*250.jpeg", "url": "https://cdn.klook.com/user_review/product/1947978/9ba8b1aa-0a84-4b41-6a3b-1710d87d48ec.0*1200.jpeg" }, { "id": 16351780, "resize_url": "https://cdn.klook.com/user_review/product/1947978/d54ab03d-f19e-4d39-5ff7-9d394c4e6f99.0*250.jpeg", "url": "https://cdn.klook.com/user_review/product/1947978/d54ab03d-f19e-4d39-5ff7-9d394c4e6f99.0*1200.jpeg" }, { "id": 16351781, "resize_url": "https://cdn.klook.com/user_review/product/1947978/7143c819-5934-4d26-6d27-8fca9c9cf4c4.0*250.jpeg", "url": "https://cdn.klook.com/user_review/product/1947978/7143c819-5934-4d26-6d27-8fca9c9cf4c4.0*1200.jpeg" } ], "check_in_info": null, "language": null, "review_time": null, "review_score": null, "from_url": null } ``` Each review returns a structured record with the following fields: | Field | Meaning | |---|---| | `Review ID` | Unique identifier for the review | | `User Info` | Reviewer's display name, nationality, and profile metadata | | `Review Content` | Full original review text as submitted by the traveler | | `Translate Content` | Machine-translated version of the review (if applicable) | | `Show Translation` | Boolean flag indicating whether a translation is displayed | | `Has Reply` | Whether the property or operator has responded to the review | | `Has Liked` | Whether the current session user has liked the review | | `Liked Count` | Total number of likes the review has received | | `Review Score` | Numeric rating given by the reviewer (typically 1–5) | | `Review Time` | Timestamp of when the review was submitted | | `Language` | Detected language of the original review content | | `Check In Info` | Check-in or experience date, and room/activity variant if available | | `Product Info` | Name and ID of the hotel or activity being reviewed | | `Review Image List` | Array of image URLs uploaded by the reviewer | *** ### How to Use 1. **Find the Item ID** — Open any Klook hotel or activity page. Extract the numeric ID from the URL (the number before the slug). 2. **Set the type** — Use `"hotels"` for accommodation, `"activity"` for tours and experiences. 3. **Choose sort order** — Use `"sort_review_time_desc"` for the latest reviews, or `"sort_most_relevant"` for highest-signal feedback. 4. **Set page and limit** — Start from `page: 1` and set `max_items_per_url` to your target volume (up to `200` per run). 5. **Run and export** — Download results as JSON or CSV for analysis. **Common issues:** - If no results return, double-check that `type` matches the URL type (`hotels` vs `activity`). - For items with fewer reviews than `max_items_per_url`, the scraper will simply return all available records. *** ### Use Cases & Business Value - **Reputation management:** Aggregate guest feedback across properties for QA teams - **Sentiment analysis:** Feed review text into NLP pipelines to detect recurring themes - **Competitive benchmarking:** Compare scores and feedback patterns across similar listings - **Content research:** Identify what travelers highlight most (location, service, cleanliness) *** ### Conclusion The **Klook.com Reviews Scraper** delivers structured, detailed traveler review data without manual effort. With flexible sorting, language metadata, image lists, and check-in context per record, it provides everything needed for meaningful analysis of guest experience on one of Asia's most active travel platforms. # Actor input Schema ## `item_id` (type: `string`): Enter Item ID. For example, en-US/activity/107259-parapharmacie-monge-shopping-coupon-paris/ -> 68846 | hotels/detail/285841-hotel-gracery-shinjuku/ -> 285841 ## `type` (type: `string`): Select Item Type ## `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 { "item_id": "107259", "type": "activity", "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 = { "item_id": "107259", "type": "activity", "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/klook-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 = { "item_id": "107259", "type": "activity", "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/klook-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 '{ "item_id": "107259", "type": "activity", "page": 1, "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/klook-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/klook-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Klook Reviews Scraper", "description": "Scrape verified traveler reviews from Klook.com including ratings, review content, user info, check-in details, and images. Perfect for hospitality businesses, travel analysts, and reputation management teams needing structured review data.", "version": "0.0", "x-build-id": "dnqRTboKByZxXEWQl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~klook-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-klook-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~klook-reviews-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-klook-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~klook-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-klook-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "item_id": { "title": "Item ID (Item ID on klook.com tour review page url, e.g. en-US/activity/107259-parapharmacie-monge-shopping-coupon-paris/ -> 107259 | hotels/detail/285841-hotel-gracery-shinjuku/ -> 285841", "type": "string", "description": "Enter Item ID. For example, en-US/activity/107259-parapharmacie-monge-shopping-coupon-paris/ -> 68846 | hotels/detail/285841-hotel-gracery-shinjuku/ -> 285841" }, "type": { "title": "Item Type", "enum": [ "activity", "hotels" ], "type": "string", "description": "Select Item Type" }, "sort_by": { "title": "Sort by", "enum": [ "sort_most_relevant", "sort_review_time_desc", "sort_score_high_to_low", "sort_score_low_to_high" ], "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 } } } } } } } } } } ```