# Nike Reviews Scraper (`shahidirfan/nike-reviews-scraper`) Actor Extract Nike product reviews, ratings & customer feedback at scale. Scrape review text, scores, verified purchase badges & user details. Perfect for market research, sentiment analysis & competitive intelligence. Fast, reliable data extraction. - **URL**: https://apify.com/shahidirfan/nike-reviews-scraper.md - **Developed by:** [Shahid Irfan](https://apify.com/shahidirfan) (community) - **Categories:** E-commerce, AI, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Extract customer reviews from any Nike product page at scale. Collect verified star ratings, detailed review text, fit and comfort assessments, reviewer profiles, and aggregate product data — all without writing a single line of code. Perfect for product research, sentiment analysis, and competitive intelligence. ### Features - **Product URL or ID input** — Paste any Nike product URL or enter a style code directly - **Full review data** — Captures title, text, rating, date, fit, comfort, and recommendation status - **Aggregate product stats** — Overall rating, total review count, and rating breakdowns - **Smart pagination** — Automatically pages through all available reviews up to your limit - **Flexible sorting** — Sort by most recent, most helpful, highest, or lowest rating - **Deduplication** — Each review is saved only once, even across retries - **Proxy support** — Works with Apify Proxy residential IPs for high-volume runs - **Clean output** — No null fields, no empty strings — only meaningful data --- ### Use Cases #### Product Research Before sourcing or buying Nike products, analyse customer feedback at scale. Understand common complaints, sizing issues, and what buyers love most about specific models. #### Sentiment Analysis Feed collected reviews into NLP pipelines to measure brand sentiment, track satisfaction trends over time, and identify recurring themes such as comfort problems or quality praise. #### Competitor Benchmarking Compare review volume, average ratings, and fit assessments across multiple Nike product lines to identify which products outperform others in customer satisfaction. #### E-commerce & Retail Intelligence Retailers and drop-shippers can validate product demand by studying verified buyer reviews before stocking items, reducing returns and improving customer satisfaction. #### Academic & Market Research Researchers studying consumer behaviour, product lifecycle, or sports footwear trends can extract structured review datasets for statistical analysis. --- ### Input Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `startUrl` | String | No* | — | Full Nike product page URL (e.g. `https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004`) | | `productId` | String | No* | — | Nike style code such as `HQ3950-004` or base SKU `HQ3950`. Used when no URL is provided. | | `results_wanted` | Integer | No | `20` | Maximum number of reviews to collect | | `max_pages` | Integer | No | `10` | Safety cap on API page requests (each page = ~10 reviews) | | `sort_by` | String | No | `RECENT` | Sort order: `RECENT`, `HELPFUL`, `HIGHEST_RATING`, `LOWEST_RATING` | | `proxyConfiguration` | Object | No | — | Apify Proxy settings for reliable large-scale runs | \* Either `startUrl` or `productId` must be provided. --- ### Output Data Each item in the dataset contains: | Field | Type | Description | |-------|------|-------------| | `review_id` | Integer | Unique review identifier | | `product_sku` | String | Nike base style code (e.g. `HQ3950`) | | `product_title` | String | Name of the reviewed product | | `product_url` | String | Link to the Nike product page | | `overall_rating` | Number | Aggregate product rating (e.g. `4.6`) | | `review_rating` | Integer | Star rating for this review (1–5) | | `review_title` | String | Short headline of the review | | `review_text` | String | Full review body text | | `reviewer_name` | String | Display name of the reviewer | | `reviewer_location` | String | Location reported by reviewer | | `size_worn` | String | Shoe size the reviewer normally wears | | `fit` | String | Fit assessment: `Runs Small`, `True to Size`, or `Runs Big` | | `comfort` | String | Comfort level: `Uncomfortable`, `Average`, or `Very Comfortable` | | `recommended` | String | Whether reviewer recommends the product (`Yes` / `No`) | | `helpful_votes` | Integer | Number of helpful up-votes on this review | | `not_helpful_votes` | Integer | Number of not-helpful down-votes | | `date_posted` | String | Human-readable review date (e.g. `May 18, 2026`) | | `date_posted_ms` | Integer | Review creation timestamp in milliseconds | | `locale` | String | Review locale (e.g. `en_US`) | | `verified_purchase` | Boolean | Whether review is from a verified buyer | | `has_media` | Boolean | Whether review includes photos or videos | --- ### Usage Examples #### Scrape by Product URL The most straightforward method — paste the full Nike product URL: ```json { "startUrl": "https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004", "results_wanted": 50 } ```` #### Scrape by Product ID / Style Code If you only have a style code, enter it directly: ```json { "productId": "HQ3950-004", "results_wanted": 100, "sort_by": "HELPFUL" } ``` #### Collect All Reviews Sorted by Lowest Rating Ideal for identifying product issues and support patterns: ```json { "startUrl": "https://www.nike.com/t/air-jordan-1-retro-high-og-shoes-KHXHc2/DZ5485-612", "results_wanted": 200, "sort_by": "LOWEST_RATING", "max_pages": 20 } ``` #### High-Volume Run with Proxy For large datasets, enable residential proxies for reliability: ```json { "productId": "FQ2432", "results_wanted": 500, "max_pages": 50, "sort_by": "RECENT", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ``` *** ### Sample Output ```json { "review_id": 1687533, "product_sku": "HQ3950", "product_title": "Air Jordan MVP 92 Men's Shoes", "product_url": "https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-401", "overall_rating": 4.6, "review_rating": 5, "review_title": "1st Jordan's", "review_text": "First pair of Jordans I have ever purchased and I'm not disappointed. They are so comfortable and the style can be worn with just about any outfit!", "reviewer_name": "MichelleF703285291", "reviewer_location": "US", "size_worn": "8.5", "fit": "True to Size", "comfort": "Very Comfortable", "recommended": "Yes", "helpful_votes": 0, "not_helpful_votes": 0, "date_posted": "May 18, 2026", "date_posted_ms": 1779129695000, "locale": "en_US", "verified_purchase": false, "has_media": false } ``` *** ### Tips for Best Results #### Find Your Product URL Navigate to any Nike product page and copy the URL from your browser's address bar. The scraper accepts any Nike `.com` product URL regardless of colorway or region. #### Use Base SKU for All Colorways Entering style code `HQ3950` (without a colorway suffix like `-004`) fetches reviews for the entire product family across all colorways, giving you more reviews in a single run. #### Choose the Right Sort Order - **RECENT** — Best for tracking new feedback and monitoring product sentiment over time - **HELPFUL** — Best for surfacing the most insightful community-vetted reviews - **LOWEST\_RATING** — Best for quality assurance and identifying product problems #### Proxy Configuration For runs collecting more than 100 reviews, enabling residential proxies reduces the risk of rate limiting and ensures uninterrupted data collection. *** ### Integrations Connect your Nike review data with: - **Google Sheets** — Export for team analysis and dashboards - **Airtable** — Build searchable review databases by product or rating - **Slack** — Receive notifications when new reviews appear for tracked products - **Make** — Automate weekly review collection workflows - **Zapier** — Trigger alerts when low-rated reviews are detected - **Webhooks** — Push data directly to your own API or analytics platform #### Export Formats Download collected reviews in multiple formats: - **JSON** — For developers and API integrations - **CSV** — For spreadsheet analysis in Excel or Google Sheets - **Excel** — For business reporting and pivot tables - **XML** — For system integrations and data pipelines *** ### Frequently Asked Questions #### What URLs does the scraper support? Any Nike product page URL from `www.nike.com` is supported. Both standard product URLs (`/t/product-name/STYLE-CODE`) and style codes entered directly are accepted. #### How many reviews can I collect? The scraper can collect all publicly available reviews for a product. Set `results_wanted` to a high number (e.g. 1000) and adjust `max_pages` accordingly. Each page returns approximately 10 reviews. #### Does the scraper need a Nike account? No. Reviews are publicly available and no login is required. #### What is the base SKU vs style code? A full style code like `HQ3950-004` includes a colorway suffix. The base SKU (`HQ3950`) aggregates reviews across all colorways of the same model. Both are accepted as input. #### Can I scrape multiple products at once? Run the actor multiple times with different URLs or product IDs. You can also schedule runs or use the Apify API to trigger parallel scrapes. #### What is the `sort_by` parameter? It controls review ordering: `RECENT` shows newest first, `HELPFUL` shows most voted first, `HIGHEST_RATING` and `LOWEST_RATING` filter by star count. #### Are reviews from all regions included? The scraper fetches reviews in `en_US` locale by default, which includes reviews submitted on the US Nike website. *** ### Support For issues or feature requests, contact support through the Apify Console. #### Resources - [Apify Documentation](https://docs.apify.com/) - [API Reference](https://docs.apify.com/api/v2) - [Scheduling Runs](https://docs.apify.com/schedules) *** ### Legal Notice This actor is designed for legitimate data collection purposes. Users are responsible for ensuring compliance with Nike's terms of service and applicable laws. Use collected data responsibly and respect rate limits. This tool is intended for research, analysis, and business intelligence purposes only. # Actor input Schema ## `startUrl` (type: `string`): Nike product page URL. Example: https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004 ## `productId` (type: `string`): Nike style code such as HQ3950-004 or base SKU like HQ3950. Used when no URL is provided. ## `results_wanted` (type: `integer`): Maximum number of reviews to collect per run. ## `max_pages` (type: `integer`): Safety cap on paginated API requests. Each page returns up to 10 reviews. ## `sort_by` (type: `string`): Sort order for reviews: RECENT, HELPFUL, HIGHEST\_RATING, or LOWEST\_RATING. ## `proxyConfiguration` (type: `object`): Use Apify Proxy for stable access. Residential proxies recommended for large runs. ## Actor input object example ```json { "startUrl": "https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004", "results_wanted": 20, "max_pages": 10, "sort_by": "RECENT", "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `overview` (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 = { "startUrl": "https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004", "results_wanted": 20, "max_pages": 10, "sort_by": "RECENT" }; // Run the Actor and wait for it to finish const run = await client.actor("shahidirfan/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 = { "startUrl": "https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004", "results_wanted": 20, "max_pages": 10, "sort_by": "RECENT", } # Run the Actor and wait for it to finish run = client.actor("shahidirfan/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 '{ "startUrl": "https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004", "results_wanted": 20, "max_pages": 10, "sort_by": "RECENT" }' | apify call shahidirfan/nike-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=shahidirfan/nike-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Nike Reviews Scraper", "description": "Extract Nike product reviews, ratings & customer feedback at scale. Scrape review text, scores, verified purchase badges & user details. Perfect for market research, sentiment analysis & competitive intelligence. Fast, reliable data extraction.", "version": "0.0", "x-build-id": "tpyn2PFP6LBPJvAHX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/shahidirfan~nike-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-shahidirfan-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/shahidirfan~nike-reviews-scraper/runs": { "post": { "operationId": "runs-sync-shahidirfan-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/shahidirfan~nike-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-shahidirfan-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": { "startUrl": { "title": "Product URL", "type": "string", "description": "Nike product page URL. Example: https://www.nike.com/t/air-jordan-mvp-92-mens-shoes-uOkaWWqF/HQ3950-004" }, "productId": { "title": "Product ID (Style Code)", "type": "string", "description": "Nike style code such as HQ3950-004 or base SKU like HQ3950. Used when no URL is provided." }, "results_wanted": { "title": "Maximum number of reviews", "minimum": 1, "type": "integer", "description": "Maximum number of reviews to collect per run.", "default": 20 }, "max_pages": { "title": "Maximum number of pages", "minimum": 1, "type": "integer", "description": "Safety cap on paginated API requests. Each page returns up to 10 reviews.", "default": 10 }, "sort_by": { "title": "Sort reviews by", "enum": [ "RECENT", "HELPFUL", "HIGHEST_RATING", "LOWEST_RATING" ], "type": "string", "description": "Sort order for reviews: RECENT, HELPFUL, HIGHEST_RATING, or LOWEST_RATING.", "default": "RECENT" }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Use Apify Proxy for stable access. Residential proxies recommended for large runs.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```