# Walmart Reviews Scraper ⭐ (`shahidirfan/walmart-reviews-scraper`) Actor Extract Walmart product reviews at scale. Scrape ratings, text, verified badges, and reviewer details. Perfect for competitive analysis, sentiment tracking, and market research. Fast, reliable, Walmart-compliant data collection. - **URL**: https://apify.com/shahidirfan/walmart-reviews-scraper.md - **Developed by:** [Shahid Irfan](https://apify.com/shahidirfan) (community) - **Categories:** E-commerce, Automation, Developer tools - **Stats:** 4 total users, 3 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 ## Walmart Reviews Scraper Extract structured customer reviews from Walmart product review pages using a product URL or product ID. Collect ratings, review text, reviewer metadata, and product-level summary signals in a clean dataset ready for analysis, monitoring, and reporting. ### Features - **Flexible input** - Start with a Walmart review URL, product URL, product ID, or other URL fields (`startUrl`, `url`, `startUrls`). - **Paginated collection** - Automatically walks review pages until your limits are reached. - **Configurable sorting** - Pull most relevant, most helpful, newest, oldest, highest-rated, or lowest-rated reviews. - **Clean dataset output** - Removes empty values and keeps records consistent for downstream use. - **Production-oriented limits** - Control both `results_wanted` and `max_pages` for reliable run time. ### Use Cases #### Product Research Review real customer feedback before sourcing products or launching campaigns. Spot recurring praise and complaints quickly. #### Reputation Monitoring Track how customer sentiment changes over time for your own catalog or competitor products. #### Merchandising Insights Identify feature-level pain points and strengths from review text and star ratings. #### Data Pipelines Export review datasets to BI tools, warehouses, or spreadsheets for ongoing analysis. --- ### Input Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `productUrl` | String | No | `https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom` | Walmart product/review URL. | | `productId` | String | No | `18023573301` | Numeric Walmart product ID. | | `sort` | String | No | `relevancy` | Review order: `relevancy`, `helpful`, `submission-desc`, `submission-asc`, `rating-desc`, `rating-asc`. | | `results_wanted` | Integer | No | `20` | Maximum number of reviews to collect. | | `max_pages` | Integer | No | `10` | Maximum number of review pages to fetch. | | `proxyConfiguration` | Object | No | Not set | Optional proxy options for reliability. Enable Apify Proxy when you need more anti-blocking stability. | --- ### Output Data Each dataset item includes product-level and review-level fields. | Field | Type | Description | |-------|------|-------------| | `productId` | String | Walmart product ID. | | `productName` | String | Product title. | | `productUrl` | String | Walmart review page URL. | | `canonicalProductUrl` | String | Canonical Walmart product URL when available. | | `reviewId` | String | Unique review identifier. | | `reviewReferenceId` | String | Review reference token. | | `reviewTitle` | String | Review headline. | | `reviewText` | String | Full review text. | | `rating` | Number | Star rating value. | | `recommended` | Boolean | Whether reviewer recommends the product. | | `reviewSubmissionTime` | String | Submission date string from source. | | `userNickname` | String | Reviewer display name when available. | | `userLocation` | String | Reviewer location. | | `positiveFeedback` | Number | Helpful/upvote count. | | `negativeFeedback` | Number | Unhelpful/downvote count. | | `mediaUrls` | Array | List of review image/media URLs. | | `averageOverallRating` | Number | Product average rating. | | `totalReviewCount` | Number | Total review count for product. | | `filteredReviewsCount` | Number | Filtered review count under current view. | | `currentPage` | Number | Source page number for the review item. | --- ### Usage Examples #### Basic Run With Product URL ```json { "productUrl": "https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom", "results_wanted": 20 } ```` #### Run With Product ID ```json { "productId": "18023573301", "results_wanted": 50, "max_pages": 10 } ``` #### Sorted Reviews With Proxy ```json { "productUrl": "https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom", "sort": "rating-desc", "results_wanted": 100, "max_pages": 20, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ``` *** ### Sample Output ```json { "productId": "18023573301", "productName": "Free Assembly Women's and Women's Plus Sleeveless Belted Cotton Midi Dress, Sizes XS-4X", "productUrl": "https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom", "reviewId": "417671463", "reviewReferenceId": "9c6dc3b4-a217-5833-91db-ba1e422e0a1a", "reviewTitle": "Beautiful 100% cotton dress", "reviewText": "This dress is 100% cotton...", "rating": 5, "recommended": true, "reviewSubmissionTime": "2/25/2026", "userLocation": "Florida", "positiveFeedback": 12, "negativeFeedback": 1, "mediaUrls": [ "https://i5.walmartimages.com/dfw/...jpg" ], "averageOverallRating": 4.3, "totalReviewCount": 355, "filteredReviewsCount": 51, "currentPage": 1 } ``` *** ### Tips For Best Results #### Start Small First - Begin with `results_wanted: 20` to validate your input quickly. - Increase limits after confirming output quality. #### Use Reliable Inputs - Prefer direct review URLs or numeric product IDs. - If using URL inputs, include a Walmart product/review URL with any query tags. #### Tune Pagination - Increase `max_pages` only when needed. - Keep `results_wanted` aligned with your analysis scope. #### Use Proxy For Stability - Keep `useApifyProxy: true` for automatic Apify proxy rotation. - For strict targets, set `apifyProxyGroups` to `["RESIDENTIAL"]`. *** ### Integrations Connect your dataset with: - **Google Sheets** - Share review datasets with non-technical teams. - **Airtable** - Build searchable feedback repositories. - **Make** - Trigger automations from new review runs. - **Zapier** - Route review data to downstream apps. - **Webhooks** - Push results into custom services. #### Export Formats - **JSON** - API and engineering workflows. - **CSV** - Spreadsheet workflows. - **Excel** - Business reporting. - **XML** - Legacy integrations. *** ### Frequently Asked Questions #### Can I scrape by product ID only? Yes. Provide `productId` and the actor will resolve the review page automatically. #### Does this support pagination? Yes. The actor paginates review pages up to `max_pages` and stops early when `results_wanted` is reached. #### Can I control review order? Yes. Use `sort` to choose relevancy, helpfulness, recency, or rating-based ordering. #### Why are some fields missing in some reviews? Not all reviewers provide every field (for example location or media), so only available values are saved. #### Can I run this on multiple products? Run the actor separately per product input for clean, product-specific datasets. *** ### Support For issues or feature requests, contact support through the Apify Console. #### Resources - [Apify Documentation](https://docs.apify.com/) - [Apify 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 website terms of service and applicable laws, and for using collected data responsibly. # Actor input Schema ## `productUrl` (type: `string`): Walmart product or reviews URL. ## `productId` (type: `string`): Walmart product ID. Used if URL is not provided. ## `sort` (type: `string`): Review sort order. ## `results_wanted` (type: `integer`): Maximum number of reviews to save. ## `max_pages` (type: `integer`): Maximum review pages to fetch. ## `proxyConfiguration` (type: `object`): Optional proxy settings. Use Apify Proxy for best anti-blocking stability. ## Actor input object example ```json { "productUrl": "https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom", "productId": "18023573301", "sort": "relevancy", "results_wanted": 20, "max_pages": 3, "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 = { "productUrl": "https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom", "productId": "18023573301", "sort": "relevancy", "results_wanted": 20, "max_pages": 3 }; // Run the Actor and wait for it to finish const run = await client.actor("shahidirfan/walmart-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 = { "productUrl": "https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom", "productId": "18023573301", "sort": "relevancy", "results_wanted": 20, "max_pages": 3, } # Run the Actor and wait for it to finish run = client.actor("shahidirfan/walmart-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 '{ "productUrl": "https://www.walmart.com/reviews/product/18023573301?entryPoint=viewAllReviewsBottom", "productId": "18023573301", "sort": "relevancy", "results_wanted": 20, "max_pages": 3 }' | apify call shahidirfan/walmart-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=shahidirfan/walmart-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Walmart Reviews Scraper ⭐", "description": "Extract Walmart product reviews at scale. Scrape ratings, text, verified badges, and reviewer details. Perfect for competitive analysis, sentiment tracking, and market research. Fast, reliable, Walmart-compliant data collection.", "version": "0.0", "x-build-id": "HJRYlbESfMxXOgFFI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/shahidirfan~walmart-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-shahidirfan-walmart-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~walmart-reviews-scraper/runs": { "post": { "operationId": "runs-sync-shahidirfan-walmart-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~walmart-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-shahidirfan-walmart-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": { "productUrl": { "title": "Product URL", "type": "string", "description": "Walmart product or reviews URL." }, "productId": { "title": "Product ID", "type": "string", "description": "Walmart product ID. Used if URL is not provided." }, "sort": { "title": "Sort Order", "enum": [ "relevancy", "helpful", "submission-desc", "submission-asc", "rating-desc", "rating-asc" ], "type": "string", "description": "Review sort order.", "default": "relevancy" }, "results_wanted": { "title": "Results wanted", "minimum": 1, "type": "integer", "description": "Maximum number of reviews to save.", "default": 20 }, "max_pages": { "title": "Max pages", "minimum": 1, "type": "integer", "description": "Maximum review pages to fetch.", "default": 10 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional proxy settings. Use Apify Proxy for best anti-blocking stability.", "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 } } } } } } } } } } ```