# Musinsa Product Search Scraper (`stealth_mode/musinsa-product-search-scraper`) Actor Scrape Musinsa product search results with precision. This scraper collects product names, prices, images, brand details, ratings, and 21+ fields per item — perfect for price monitoring, inventory tracking, and market analysis on Asia's leading fashion platform. - **URL**: https://apify.com/stealth\_mode/musinsa-product-search-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Developer tools, E-commerce, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 ## Musinsa Product Search Scraper: Extract Fashion & Beauty Data Fast --- ### What Is Musinsa? Musinsa is one of Asia's largest online fashion and beauty marketplaces, featuring hundreds of thousands of products from local and international brands. The platform serves millions of shoppers across Singapore, South Korea, and the region, making it a critical source for competitive intelligence, trend analysis, and product data. Manually collecting product information from search results is tedious — the **Musinsa Product Search Scraper** automates the entire process, delivering clean, structured data in seconds. --- ### Overview The **Musinsa Product Search Scraper** extracts product listings from Musinsa search result pages, transforming each item into a detailed record with pricing, images, brand info, and customer ratings. It is ideal for: - **E-commerce analysts** monitoring competitor pricing and product assortments - **Market researchers** studying fashion and beauty trends across regions - **Retailers** tracking product availability and price fluctuations - **Aggregators & comparison platforms** feeding product data into their systems - **Data scientists** building fashion market datasets for ML models The scraper excels at handling paginated search results, respecting rate limits, and extracting rich metadata across multiple product categories and brand portfolios. --- ### Input Format The scraper accepts a JSON configuration to define which products to extract: ```json { "urls": [ "https://global.musinsa.com/sg/search?gender=A&keyword=lips&page=1&sortCode=RECOMMEND" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` | Parameter | Type | Description | |---|---|---| | `urls` | Array of strings | Search result page URLs from Musinsa. Include query parameters for gender, keyword, page number, and sort order. | | `ignore_url_failures` | Boolean | If `true`, the scraper continues if some URLs fail. If `false`, it stops on first error. | | `max_items_per_url` | Integer | Maximum number of products to extract per URL (e.g., `200`). Useful for controlling data volume. | > **Example URL anatomy:**\ > `https://global.musinsa.com/sg/search?gender=A&keyword=lips&page=1&sortCode=RECOMMEND` > > - `gender=A` → All genders > - `keyword=lips` → Search term > - `page=1` → First page > - `sortCode=RECOMMEND` → Recommendation sorting *** ### Output Format **Sample output** ```json { "goods_no": 3882622, "goods_name": "Unseen Balloon Tint 16 Types", "image": "//image.msscdn.net/thumbnails/global_images/goods_img/20240220/3882622/3882622_17687842869849_big.jpg", "image_url": "//image.msscdn.net/thumbnails/global_images/goods_img/20240220/3882622/3882622_17687842869849_big.jpg", "brand_id": "oddtype", "brand_name": "ODDTYPE", "brand_landing_url": "/sg/brands/oddtype", "status": "SALE", "status_name": "Sale", "label_list": [], "badge_list": [ { "type": "isExclusive", "text": "Exclusive", "key_color": "#8A8A8A1A" } ], "global_yn": "Y", "normal_price": 25, "price": 13, "currency_symbol": "SG $", "currency_code": "SGD", "sale_rate": 48, "campaign": { "badge": { "text": "SIGNITURE DEAL", "key_color": "#FA783F" } }, "like_count": 91515, "is_member_like": false, "estimate_count": 23666, "estimate_average": 4.6, "landing_url": "/sg/goods/3882622", "from_url": "https://global.musinsa.com/sg/search?gender=A&keyword=lips&page=1&sortCode=RECOMMEND" } ``` Each product returns a comprehensive record with 21 fields covering identity, pricing, imagery, brand, and customer engagement: #### Product Identification | Field | Meaning | |---|---| | `Goods No` | Unique Musinsa product ID | | `Goods Name` | Full product name as displayed on Musinsa | | `Landing URL` | Direct link to the product detail page | | `Status` | Current product status code (e.g., available, discontinued) | | `Status Name` | Human-readable status (e.g., "Active", "Discontinued") | #### Imagery & Media | Field | Meaning | |---|---| | `Image` | Product thumbnail or main image (file or embedded data) | | `Image URL` | Direct URL to the product image for external use | #### Pricing & Currency | Field | Meaning | |---|---| | `Normal Price` | Standard retail price before discounts | | `Price` | Current selling price (may include discounts) | | `Currency Symbol` | Currency symbol (e.g., $, ₩, SGD) | | `Currency Code` | ISO 4217 code (e.g., "USD", "KRW", "SGD") | | `Sale Rate` | Discount percentage (e.g., `20` for 20% off) | #### Brand Information | Field | Meaning | |---|---| | `Brand ID` | Unique identifier for the brand on Musinsa | | `Brand Name` | Official brand name | | `Brand Landing URL` | Link to the brand's Musinsa storefront | #### Promotions & Labels | Field | Meaning | |---|---| | `Campaign` | Active promotion or campaign name (e.g., "Summer Sale") | | `Label List` | Product labels or tags (e.g., "New", "Trending", "Limited Edition") | | `Badge List` | Badges assigned by Musinsa (e.g., "Best Seller", "Recommended") | | `Global YN` | Whether the product is available globally (`Y` or `N`) | #### Customer Engagement & Ratings | Field | Meaning | |---|---| | `Like Count` | Total number of likes/favorites the product has received | | `Is Member Like` | Whether the current user has liked the product | | `Estimate Count` | Number of customer ratings/reviews | | `Estimate Average` | Average rating score (e.g., 4.5 out of 5) | *** ### How to Use 1. **Build a search URL** — Navigate to Musinsa, use filters (gender, keyword, sort), and copy the full URL. 2. **Paste URL** — Add the search result URL to the `urls` array in the configuration. 3. **Set limits** — Configure `max_items_per_url` to control the number of products (default: 20, max: 200+). 4. **Enable resilience** — Set `ignore_url_failures: true` for large scraping runs. 5. **Execute** — Start the scraper and monitor progress in the run log. 6. **Download** — Export results as JSON, CSV, or Excel. **Best practices:** - Use multiple URLs for different search queries to build a comprehensive dataset. - Sort by "RECOMMEND" or "NEWEST" to capture different product angles. - For large batches, set `max_items_per_url` conservatively to avoid timeouts. - If a URL fails, the scraper logs the error and moves to the next URL. *** ### Use Cases & Business Value - **Price intelligence:** Track competitor pricing in real-time across product categories. - **Trend analysis:** Identify bestselling items, emerging brands, and seasonal shifts. - **Inventory management:** Monitor stock levels and availability across regions. - **Product catalog sync:** Automatically update your own product database with Musinsa data. - **Market research:** Analyze fashion consumer preferences and customer satisfaction scores. The scraper delivers actionable insights in seconds — perfect for fast-moving fashion and beauty markets where data freshness is critical. *** ### Conclusion The **Musinsa Product Search Scraper** is an essential tool for anyone competing in the Asian fashion and beauty market. With 21 data fields per product and flexible filtering, it transforms search results into intelligence that drives pricing decisions, inventory planning, and trend forecasting. Start scraping today and stay ahead of the competition. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the product search list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `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://global.musinsa.com/sg/search?gender=A&keyword=lips&page=1&sortCode=RECOMMEND" ], "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://global.musinsa.com/sg/search?gender=A&keyword=lips&page=1&sortCode=RECOMMEND" ], "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/musinsa-product-search-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://global.musinsa.com/sg/search?gender=A&keyword=lips&page=1&sortCode=RECOMMEND"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/musinsa-product-search-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://global.musinsa.com/sg/search?gender=A&keyword=lips&page=1&sortCode=RECOMMEND" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/musinsa-product-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/musinsa-product-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Musinsa Product Search Scraper", "description": "Scrape Musinsa product search results with precision. This scraper collects product names, prices, images, brand details, ratings, and 21+ fields per item — perfect for price monitoring, inventory tracking, and market analysis on Asia's leading fashion platform.", "version": "0.0", "x-build-id": "USp3uIr1te0e9zvaN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~musinsa-product-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-musinsa-product-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~musinsa-product-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-musinsa-product-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~musinsa-product-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-musinsa-product-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 product search list urls to scrape", "type": "array", "description": "Add the URLs of the product search list 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" } }, "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 } } } } } } } } } } ```