# Asos Product Reviews Scraper (`nifty.codes/asos-reviews-scraper`) Actor Extract customer reviews, ratings, and verified purchaser status from Asos product pages. Powered by Asos Scraper. - **URL**: https://apify.com/nifty.codes/asos-reviews-scraper.md - **Developed by:** [Nifty](https://apify.com/nifty.codes) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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 ## Asos Product Reviews Scraper This actor extracts Product Reviews from Asos. It collects user ratings, review text, and metadata directly from specific product pages. This tool helps monitor customer sentiment and product feedback. #### Data Fields | Field Name | Description | Example | | --- | --- | --- | | Review ID | Unique identifier for the review | 182736455 | | Product ID | ID of the product being reviewed | 20455678 | | Author ID | Unique identifier for the reviewer | user_99283 | | Rating | Numerical score from 1 to 5 | 5 | | Is Ratings Only | Boolean indicating if no text was provided | false | | Is Recommended | Whether the user recommends the item | true | | Is Verified Purchaser | If the user bought the item on Asos | true | | Submission Time | Date and time of the review | 2023-11-15T10:30:00Z | | Review Text | The main body of the review | Great fit and high quality material. | | Review Title | Short summary of the review | Perfect fit | | User Nickname | Display name of the reviewer | Alex J | | Is Syndicated | If the review came from another site | false | | Syndication Source | Original site for syndicated reviews | null | | Secondary Ratings | Specific scores for fit or quality | {"Quality": 5, "Value": 4} | #### Input - `urls`: Array of Asos product page URL strings. Only product detail pages are supported. - `maxItems`: Maximum number of reviews to extract per URL. Default is 100. #### Example Input ```json { "urls": ["https://www.asos.com/example-product/prd/12345"], "maxItems": 50 } ```` #### Example Output ```json [ { "reviewId": "182736455", "productId": "20455678", "authorId": "user_99283", "rating": 5, "isRatingsOnly": false, "isRecommended": true, "isVerifiedPurchaser": true, "submissionTime": "2023-11-15T10:30:00Z", "reviewText": "Great fit and high quality material.", "reviewTitle": "Perfect fit", "userNickname": "Alex J", "isSyndicated": false, "syndicationSource": null, "secondaryRatings": { "Fit": 5 } }, { "reviewId": "182736456", "productId": "20455678", "authorId": "user_11223", "rating": 4, "isRatingsOnly": false, "isRecommended": true, "isVerifiedPurchaser": false, "submissionTime": "2023-11-16T14:20:00Z", "reviewText": "Slightly larger than expected but nice.", "reviewTitle": "Good quality", "userNickname": "Sam Smith", "isSyndicated": true, "syndicationSource": "Brand Site", "secondaryRatings": { "Fit": 3 } } ] ``` #### Want more from Asos? This actor only covers **Product Reviews**. The full **Asos Scraper** browser extension also includes **Products in a List, Product Details, Shopping Bag Details, Shopping Bag Items** with unlimited personal use, real-time scraping with your logged-in sessions, CSV/Excel/JSON export, field customization, and scheduled monitoring. **[Get the Asos Scraper extension](https://nifty.codes/e/asos-scraper)** #### Disclaimer This tool extracts publicly available data. Users are responsible for compliance with applicable terms of service. # Actor input Schema ## `urls` (type: `array`): URLs to scrape. Must match: asos.com ## `maxItems` (type: `integer`): Maximum number of items to extract per URL ## `enablePagination` (type: `boolean`): Load more results beyond the first page. ## `maxPages` (type: `integer`): Maximum number of pagination actions (pages, scrolls, or loads) ## Actor input object example ```json { "urls": [ "https://www.asos.com/the-north-face/the-north-face-retro-nuptse-down-puffer-jacket-in-black/prd/209010008" ], "maxItems": 100, "enablePagination": true, "maxPages": 1 } ``` # 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("nifty.codes/asos-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 = {} # Run the Actor and wait for it to finish run = client.actor("nifty.codes/asos-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 '{}' | apify call nifty.codes/asos-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nifty.codes/asos-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Asos Product Reviews Scraper", "description": "Extract customer reviews, ratings, and verified purchaser status from Asos product pages. Powered by Asos Scraper.", "version": "3.2", "x-build-id": "QannI4hn65iePx4ol" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nifty.codes~asos-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nifty.codes-asos-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nifty.codes~asos-reviews-scraper/runs": { "post": { "operationId": "runs-sync-nifty.codes-asos-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nifty.codes~asos-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-nifty.codes-asos-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "urls" ], "properties": { "urls": { "title": "URLs", "type": "array", "description": "URLs to scrape. Must match: asos.com", "items": { "type": "string" }, "default": [ "https://www.asos.com/the-north-face/the-north-face-retro-nuptse-down-puffer-jacket-in-black/prd/209010008" ] }, "maxItems": { "title": "Max items", "minimum": 1, "type": "integer", "description": "Maximum number of items to extract per URL", "default": 100 }, "enablePagination": { "title": "Paginate", "type": "boolean", "description": "Load more results beyond the first page.", "default": true }, "maxPages": { "title": "Max pagination steps", "minimum": 1, "type": "integer", "description": "Maximum number of pagination actions (pages, scrolls, or loads)", "default": 1 } } }, "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 } } } } } } } } } } ```