# Nike Reviews Scraper (`getdataforme/nike-reviews-scraper`) Actor The Nike Reviews Scraper efficiently extracts detailed customer reviews from Nike product pages, offering insights into consumer opinions for market analysis.... - **URL**: https://apify.com/getdataforme/nike-reviews-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 ## Nike Reviews Scraper ### Introduction The Nike Reviews Scraper is designed to efficiently extract customer reviews from Nike product pages. This Actor provides valuable insights into consumer opinions, helping businesses and researchers understand market trends and product performance. ### Features - **Efficient Data Extraction**: Quickly gathers reviews from specified Nike product URLs. - **Comprehensive Review Details**: Captures detailed review information including ratings, comments, and reviewer profiles. - **Customizable Crawling**: Allows configuration of start URLs and maximum requests for tailored data collection. - **Proxy Support**: Utilizes Apify's residential proxies to ensure anonymity and avoid IP blocking. - **Reliable Performance**: Built on Apify's robust infrastructure for consistent and dependable data scraping. - **Structured Output**: Delivers data in a well-organized JSON format for easy analysis and integration. - **Scalable Solution**: Handles large volumes of data efficiently, suitable for extensive market research. ### Input Parameters | Parameter | Type | Required | Description | Example | |---------------------|---------|----------|-----------------------------------------------------------------------------|-------------------------------------------------------------------------| | `startUrls` | Array | Yes | URLs to start with. | `["https://www.nike.com/t/lebron-xxiii-masked-menace-basketball-shoes-1EPyFJde/IH1513-004"]` | | `maxItems` | Integer | No | Maximum number of requests that can be made by this crawler. | `100` | | `proxyConfiguration`| Object | No | Specifies proxy servers that will be used by the scraper to hide its origin.| `{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}` | ### Example Usage #### Example Input JSON ```json { "startUrls": [ { "url": "https://www.nike.com/t/lebron-xxiii-masked-menace-basketball-shoes-1EPyFJde/IH1513-004" } ], "maxItems": 100, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` #### Example Output JSON ```json [ { "review_id": "1675829", "product_id": "IH1513", "catalog_item_id": 179728, "sku": "IH1513", "reviewer_name": "tamarcus h", "reviewer_nickname": "tamarcush53128218", "reviewer_location": "US", "date_posted": "Apr 28, 2026", "date_posted_millis": 1777373377000, "rating": 1, "title": "Fits but squeaks", "review_text": "Love the shoes when i first got it. They fit my feet perfectly but as i wore them through the day became very comfortable and they squeak when i walked in them. Super disappointed", "recommended": false, "incentivized": false, "locale": "en_US", "up_votes": 0, "down_votes": 0, "dimensions": { "How did this product fit?": "True to Size", "How comfortable was this product?": "Uncomfortable", "Would you recommend this product?": "No" }, "profile_attributes": { "Size you normally wear": "13.5 or over", "Where do you usually play basketball?": "Not applicable" }, "photos": [], "videos": [], "scraped_at": "2026-04-29T07:15:22.124Z" } ] ``` ### Use Cases - **Market Research and Analysis**: Understand consumer preferences and product performance. - **Competitive Intelligence**: Monitor competitor products and customer feedback. - **Price Monitoring**: Track pricing trends and customer sentiment. - **Content Aggregation**: Collect reviews for content creation and analysis. - **Academic Research**: Study consumer behavior and market dynamics. - **Business Automation**: Automate data collection for strategic decision-making. ### Installation and Usage 1. Search for "Nike Reviews Scraper" 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 output is structured in JSON format, including fields such as `review_id`, `product_id`, `reviewer_name`, `rating`, `review_text`, and more. This format ensures easy integration and analysis of the data. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: We're here to help you get the most out of this Actor! # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `maxItems` (type: `integer`): Maximum number of requests that can be made by this crawler. ## `proxyConfiguration` (type: `object`): Specifies proxy servers that will be used by the scraper in order to hide its origin. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.nike.com/t/lebron-xxiii-masked-menace-basketball-shoes-1EPyFJde/IH1513-004" } ], "maxItems": 100, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "startUrls": [ { "url": "https://www.nike.com/t/lebron-xxiii-masked-menace-basketball-shoes-1EPyFJde/IH1513-004" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/nike-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 = { "startUrls": [{ "url": "https://www.nike.com/t/lebron-xxiii-masked-menace-basketball-shoes-1EPyFJde/IH1513-004" }], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("getdataforme/nike-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 '{ "startUrls": [ { "url": "https://www.nike.com/t/lebron-xxiii-masked-menace-basketball-shoes-1EPyFJde/IH1513-004" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call getdataforme/nike-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/nike-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Nike Reviews Scraper", "description": "The Nike Reviews Scraper efficiently extracts detailed customer reviews from Nike product pages, offering insights into consumer opinions for market analysis....", "version": "0.0", "x-build-id": "0srzeeejZE1yjkd7a" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~nike-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-nike-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~nike-reviews-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-nike-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~nike-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-nike-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Max Requests per Crawl", "type": "integer", "description": "Maximum number of requests that can be made by this crawler.", "default": 100 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Specifies proxy servers that will be used by the scraper in order to hide its origin.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```