# Walmart Product & Reviews Scraper (`metqo/walmart-product-reviews`) Actor Walmart product details (price, stock, seller, UPC, specs, variants) and every review with verified-only, star, date, keyword and photo filters. Monitoring mode charges only for new reviews. No login, errors never charged. - **URL**: https://apify.com/metqo/walmart-product-reviews.md - **Developed by:** [Tanusree Halder](https://apify.com/metqo) (community) - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.80 / 1,000 reviews 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/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Walmart Product & Reviews Scraper Get Walmart **product details and reviews** in one run, with filters other Walmart scrapers don't have. No login, no cookies. **You never pay for failed items.** - **Every review, not just the first page.** Tested live to review #2,000 on a single product. - **Filters:** verified purchases only, star ratings, "since" date, keywords, photo/video reviews only. - **Topic filter with sentiment:** ask for reviews about Walmart's own topics ("Freshness", "Value For Money", "Battery Life"). Each review says which topics it covers and whether it's **positive or negative** about each one. Example: *1–2★ reviews about Freshness* on a gallon of milk gives "I bought 3 gallons of milk and it was spoiled." → `Freshness: negative`. - **Monitoring mode:** run it on a schedule and get **only reviews posted since your last run**. You pay only for new reviews, and runs with nothing new cost almost nothing. - **Product details:** price, was-price, stock, seller and seller rating, UPC, model, specs, variants, delivery date, return policy, category, badges, images, rating breakdown. - **Honest run summary:** each product gets a free summary row saying how many reviews matched your filters, how many you received, and why the run stopped (`limit`, `since-date`, `end`, `caught-up`, `blocked`). ### Switching from another Walmart scraper? Paste your existing input: `product_ids`, `limit` (pages), `ratings`, `vp`, `include_personal_information` and `startUrls` are understood as-is. ### Input Paste item IDs or URLs: ```json { "products": ["604342441", "https://www.walmart.com/ip/Apple-AirPods/604342441"], "maxReviewsPerProduct": 200, "sort": "submission-desc", "stars": [1, 2], "verifiedOnly": true, "reviewsSince": "2026-01-01", "keywords": ["battery", "stopped working"] } ``` | Field | Default | What it does | |---|---|---| | `products` | — | Walmart item IDs, `/ip/` URLs or `/reviews/product/` URLs | | `scrapeProductDetails` | `true` | One product record per item | | `maxReviewsPerProduct` | `100` | `0` = product details only; up to 5,000. With several stars, the limit is split across them | | `sort` | newest first | newest, oldest, most helpful, relevance, highest or lowest rating | | `stars` | all | e.g. `[1, 2]` for complaints | | `verifiedOnly` | `false` | Verified purchases only | | `withMediaOnly` | `false` | Only reviews with photos/videos | | `reviewsSince` | — | Stop at reviews older than this date (newest-first sort) | | `keywords` | — | Keep reviews mentioning any of these words | | `topics` | — | Walmart review topics, e.g. `["Freshness"]`. Each summary row lists the product's topics and how often they're mentioned | | `onlyNewReviews` | `false` | Monitoring mode (see above) | | `includePersonalInfo` | `false` | Reviewer nickname and location; enable only with a lawful basis (GDPR/CCPA) | ### Output One dataset with three record types (use the **Products**, **Reviews** and **Run summary** views). **Review** ```json { "recordType": "review", "itemId": "604342441", "reviewId": "419508380", "rating": 1, "title": null, "text": "Not working", "submittedAt": "2026-03-15", "verifiedPurchase": true, "helpfulVotes": 0, "unhelpfulVotes": 0, "badges": ["Verified Purchase"], "mediaUrls": [], "sellerName": "Adorama", "fulfilledBy": "Seller", "clientResponse": null, "language": "English", "variant": {"Color": "White"}, "topics": [{"topic": "Freshness", "sentiment": "negative"}], "scrapedAt": "2026-09-29T06:10:15+00:00" } ``` **Product** ```json { "recordType": "product", "itemId": "604342441", "name": "Restored Apple AirPods (2nd Generation) ...", "brand": "Apple", "model": "MV7N2AM/A", "upc": "190199098428", "price": 84.99, "wasPrice": null, "currency": "USD", "availability": "IN_STOCK", "sellerName": "TheRightOne", "sellerRating": 3.72, "sellerReviewCount": 2335, "deliveryDate": "2026-10-03", "returnPolicy": "Free 30-day returns", "category": ["Electronics", "Audio", "Headphones", "..."], "specifications": {"Battery life": "3 h"}, "averageRating": 4.6, "reviewCount": 51618, "reviewsWithText": 13959, "ratingBreakdown": {"5": 44348, "4": "...", "1": 3071} } ``` **Summary (free)** ```json {"recordType": "summary", "itemId": "10450114", "status": "OK", "reviewsAvailable": 202, "reviewsDelivered": 15, "stoppedBecause": "limit", "error": null, "topics": [{"topic": "Flavor", "mentions": 2276}, {"topic": "Freshness", "mentions": 294}]} ``` ### Pricing Pay per result: **$0.003 per product** and **$0.0008 per review** ($0.80 per 1,000). Summaries and failed or blocked items are free. There's no charge per run and no compute billing, so a blocked run costs you nothing. Set a maximum charge per run and the actor stops cleanly when it's reached. **What typical runs cost:** | Run | Cost | |---|---| | 1 product, details only | $0.003 | | 1 product + 100 reviews | $0.083 | | 50 products + 200 reviews each | $8.15 | | Daily monitoring of 20 products (~5 new reviews each) | about $0.08/day ($2.40/month) | | A monitoring run with no new reviews | $0.00 | ### Limits (stated plainly) - Walmart.com (US) only. - Keyword *search* for products isn't offered, because Walmart's robots.txt disallows `/search`. Give item IDs or URLs. - Product pages show the buy-box offer only; other sellers' offers aren't included yet. - Walmart shows 10 reviews per page. Very large pulls take about 1 second per page. ### Use cases - **Brands:** track new 1–2★ reviews every day and act before ratings slip. - **Sellers:** mine competitors' complaints for product gaps ("battery", "size runs small"). - **Researchers / AI:** verified-only, dated review datasets for sentiment and product analysis. ### Use it from Claude, Cursor or other AI assistants (MCP) Your AI assistant can call this scraper directly and pay per result like any other run. Add Apify's MCP server with the Metqo tools: ``` https://mcp.apify.com?tools=metqo/walmart-product-reviews,metqo/amazon-public-reviews ``` - **Claude** (desktop or claude.ai): Settings → Connectors → *Add custom connector* → paste the URL → sign in to Apify. - **Cursor / VS Code:** add to your MCP config: ```json { "mcpServers": { "metqo": { "url": "https://mcp.apify.com?tools=metqo/walmart-product-reviews,metqo/amazon-public-reviews" } } } ``` Then just ask, e.g. *"What do verified buyers complain about most for Walmart item 10450114? Group by topic."* ### More from Metqo Data - **[Amazon Reviews & Customers Say Scraper](https://apify.com/metqo/amazon-public-reviews)**: top reviews across 12 Amazon marketplaces plus Amazon's AI "Customers say" topics with sentiment. Compare how the same product is reviewed on Walmart and Amazon. - Need scheduled feeds or other retailers? **support@metqo.com** # Actor input Schema ## `products` (type: `array`): Walmart item IDs (e.g. 604342441), product URLs (walmart.com/ip/...) or review URLs (walmart.com/reviews/product/...). ## `scrapeProductDetails` (type: `boolean`): One record per product: price, was-price, stock, seller, seller rating, UPC, specs, variants, delivery date, rating breakdown. ## `maxReviewsPerProduct` (type: `integer`): 0 = product details only. Up to 5,000. ## `sort` (type: `string`): Order in which reviews are collected. Newest first is needed for 'Reviews since' and monitoring mode. ## `stars` (type: `array`): e.g. \[1, 2] for complaints only. Empty = all stars. ## `verifiedOnly` (type: `boolean`): Only reviews from verified purchases. ## `withMediaOnly` (type: `boolean`): Only reviews that include photos or videos. ## `reviewsSince` (type: `string`): YYYY-MM-DD. Stops at older reviews. Needs sort = Newest first. ## `keywords` (type: `array`): Keep only reviews whose title or text contains any of these words (case-insensitive). ## `topics` (type: `array`): Walmart's own review topics, e.g. "Freshness", "Value For Money", "Quality", "Battery Life". Filtered by Walmart itself, so it's fast. Every run lists each product's topics with mention counts in its summary row. ## `onlyNewReviews` (type: `boolean`): Skip reviews delivered by your earlier runs of this actor, and stop paging once caught up. You pay only for new reviews. Best with sort = Newest first on a schedule. ## `includePersonalInfo` (type: `boolean`): Off by default. Enable only if you have a lawful basis under GDPR/CCPA. ## `maxAgeHours` (type: `integer`): Data fetched by anyone in the last N hours may be returned instantly from our cache (same price, faster, each row marked fromCache). 0 = always fetch live. ## `maxConcurrency` (type: `integer`): How many products to process in parallel. ## `proxyConfiguration` (type: `object`): US residential proxies are recommended. ## Actor input object example ```json { "products": [ "604342441" ], "scrapeProductDetails": true, "maxReviewsPerProduct": 100, "sort": "submission-desc", "stars": [], "verifiedOnly": false, "withMediaOnly": false, "onlyNewReviews": false, "includePersonalInfo": false, "maxAgeHours": 24, "maxConcurrency": 3, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # Actor output Schema ## `results` (type: `string`): Every record: products, reviews and the per-item run summary (field recordType tells them apart). ## `products` (type: `string`): One record per product: price, stock, seller, UPC, specs, rating breakdown. ## `reviews` (type: `string`): One record per review: rating, text, date, verified status, photos, topic sentiment. ## `summary` (type: `string`): Per product: reviews available vs delivered and why the run stopped. # 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 = { "products": [ "604342441" ] }; // Run the Actor and wait for it to finish const run = await client.actor("metqo/walmart-product-reviews").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 = { "products": ["604342441"] } # Run the Actor and wait for it to finish run = client.actor("metqo/walmart-product-reviews").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "products": [ "604342441" ] }' | apify call metqo/walmart-product-reviews --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,metqo/walmart-product-reviews" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/9pF3PPhfaUHXBaExv/builds/ZmgMFzQIrOkby5ePM/openapi.json