# Kimkim Reviews Spider (`getdataforme/kimkim-reviews-spider`) Actor The Kimkim Reviews Spider is an Apify Actor that scrapes authentic reviews from Kimkim, extracting ratings, descriptions, images, and metadata for travel activities.... - **URL**: https://apify.com/getdataforme/kimkim-reviews-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** E-commerce, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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. 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 ## Kimkim Reviews Spider ### Introduction The Kimkim Reviews Spider is a powerful Apify Actor designed to scrape and extract detailed reviews from Kimkim, a popular travel platform. It enables users to gather authentic traveler feedback on activities, tours, and experiences across various destinations, providing valuable insights for travel businesses, researchers, and marketers. By automating the collection of structured review data, this Actor saves time and ensures access to high-quality, real-time information for informed decision-making. ### Features - **Comprehensive Review Extraction**: Captures full review details including ratings, descriptions, images, and metadata from Kimkim's extensive database. - **Geographic Targeting**: Allows filtering by country to focus on specific regions, ensuring relevant and localized data. - **High Data Quality**: Extracts clean, structured JSON data with consistent formatting, minimizing manual cleanup efforts. - **Scalable Performance**: Built for efficiency, handling large volumes of reviews without compromising speed or reliability. - **Flexible Output**: Supports multiple export formats like JSON, CSV, and Excel for seamless integration with analytics tools. - **Real-Time Insights**: Pulls the latest reviews to provide up-to-date market intelligence on travel trends. - **Easy Integration**: Designed for Apify's ecosystem, with simple API access for automation in workflows. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|-------------|---------| | Country | array | No | Specifies the countries to target for review extraction. Use ISO country codes or full names. If not provided, defaults to Japan. | ["japan", "thailand"] | ### Example Usage #### Input Configuration ```json { "Country": ["japan"] } ```` #### Output Example ```json [ { "type": "activity_review", "review_id": "review_72142", "name": "Takayama Full-Day Walking Tour", "location": "Takayama", "rating": 5, "image": "https://cdn.kimkim.com/files/a/images/5151f8d28214299e5d7304b1021330d109118106/medium-9c87baa171a49b518a536eb0b673fbcb.jpg", "description": "This was an enjoyable walking tour of the marketplace and walks along the river. Tomoko san comes from that area, so our tour was more personal because she gave us information as a native of the city. She stopped often and offered to take photos of us at scenic places. She took us to a family operated noodle shop, which was a real treat. We enjoyed Takayama\nvery much.", "categories": {}, "actor_id": "D4mi76PSn0zgj8CS9", "run_id": "K1Bor3f6lAWd24Jzq" } ] ``` ### Use Cases - **Market Research and Analysis**: Analyze traveler sentiments to identify popular destinations and emerging trends in the travel industry. - **Competitive Intelligence**: Monitor competitor tours and activities by gathering reviews to benchmark performance and pricing. - **Price Monitoring**: Track feedback on pricing and value for money to optimize your own offerings. - **Content Aggregation**: Build databases of user-generated content for blogs, travel guides, or marketing campaigns. - **Academic Research**: Collect qualitative data for studies on tourism, customer satisfaction, and cultural experiences. - **Business Automation**: Integrate with CRM systems to automate feedback analysis for travel agencies and tour operators. ### Installation and Usage 1. Search for "Kimkim Reviews Spider" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The Actor outputs an array of JSON objects, each representing a single review. Key fields include: - `type`: Indicates the review category (e.g., "activity\_review"). - `review_id`: Unique identifier for the review. - `name`: Title of the reviewed activity or tour. - `location`: Geographic location of the activity. - `rating`: Numerical rating (typically 1-5). - `image`: URL to an associated image. - `description`: Full text of the review. - `categories`: Additional categorization data (may be empty). - `actor_id` and `run_id`: Metadata for tracking the extraction run. This structured format ensures easy parsing and analysis in tools like spreadsheets or databases. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** # Actor input Schema ## `Country` (type: `array`): The country for the spider. ## Actor input object example ```json { "Country": [ "japan" ] } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/kimkim-reviews-spider").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/kimkim-reviews-spider").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 '{}' | apify call getdataforme/kimkim-reviews-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/kimkim-reviews-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Kimkim Reviews Spider", "description": "The Kimkim Reviews Spider is an Apify Actor that scrapes authentic reviews from Kimkim, extracting ratings, descriptions, images, and metadata for travel activities....", "version": "0.0", "x-build-id": "ETR93ZaLSUWpr7sap" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~kimkim-reviews-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-kimkim-reviews-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~kimkim-reviews-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-kimkim-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~kimkim-reviews-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-kimkim-reviews-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Country": { "title": "Country", "type": "array", "description": "The country for the spider.", "default": [ "japan" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```