Walmart Data Extractor

📌 What is Walmart Data Extractor?

Walmart is a major US retail marketplace where shoppers compare products, prices, sellers, availability, ratings, and customer feedback. Walmart Data Extractor is a ready-made Walmart product scraper that collects product and review data from Walmart US product pages, listing pages, search pages, item IDs, or keywords. It returns product identity, price, stock status, seller, category, brand, rating, and review text in a consistent row structure for product research, price monitoring, assortment analysis, and customer-feedback workflows.

💰 Pricing

Walmart Data Extractor charges by output lines. The price is $1.00 per 1,000 output lines for Free and Standard users, $0.80 per 1,000 output lines for Professional users, and $0.60 per 1,000 output lines for Enterprise users.

📦 Output

Walmart Data Extractor creates a product row for each discovered item. When review collection is enabled, it also creates separate review rows and copies the related product context into each review row. The itemType field distinguishes Product rows from Review rows, while usItemId and productUrl keep both row types tied to the same Walmart item.

Walmart Data Extractor returns these fields:

• itemType: Identifies the row as a product or review.
• availability: Shows the product's availability status.
• priceInfo.price: Contains the displayed product price.
• name: Contains the product name.
• averageRating: Contains the product's average customer rating.
• sellerName: Contains the displayed seller name.
• productUrl: Contains the normalized Walmart product URL.
• usItemId: Contains the Walmart US item ID.
• category: Contains the product category or breadcrumb path when available.
• brand: Contains the product brand when available.
• rating: Contains the individual review rating on review rows.
• title: Contains the individual review title on review rows.
• text: Contains the individual review text on review rows.

Data Preview

The following product and review rows were collected in a live cloud run on September 10, 2026. Prices, availability, ratings, and review content can change on Walmart.

Product Row

{
  "itemType": "Product",
  "availability": "IN_STOCK",
  "priceInfo.price": "$2.84",
  "name": "Great Value Whole Vitamin D Milk, Gallon",
  "averageRating": "4.6",
  "sellerName": "Walmart.com",
  "productUrl": "https://walmart.com/ip/Great-Value-Whole-Vitamin-D-Milk-Gallon-Plastic-Jug-128-Fl-Oz/10450114",
  "usItemId": "10450114",
  "category": "Food > Dairy & Eggs > Milk > Dairy Milk > Whole Milk",
  "brand": "Great Value",
  "rating": "",
  "title": "",
  "text": ""
}

Review Row

{
  "itemType": "Review",
  "availability": "IN_STOCK",
  "priceInfo.price": "$2.84",
  "name": "Great Value Whole Vitamin D Milk, Gallon",
  "averageRating": "4.6",
  "sellerName": "Walmart.com",
  "productUrl": "https://walmart.com/ip/Great-Value-Whole-Vitamin-D-Milk-Gallon-Plastic-Jug-128-Fl-Oz/10450114",
  "usItemId": "10450114",
  "category": "Food > Dairy & Eggs > Milk > Dairy Milk > Whole Milk",
  "brand": "Great Value",
  "rating": "5",
  "title": "My Milky Experience",
  "text": "I have been buying great value brand milk from Walmart now for over 20yrs and I have never once gotten a gallon that I did not finish or could not finish because of the quality in the product or packaging. I am a lifelong purchaser of this product for sure at least as long as I can swallow and get it down I am forever loyal 100% to this  Milk."
}

🎯 Use Cases

• Monitor prices and availability: Track priceInfo.price and availability for the same usItemId across scheduled exports.
• Compare sellers and assortments: Use sellerName, brand, category, and productUrl to compare which products and sellers appear in selected Walmart searches or categories.
• Research product demand signals: Combine averageRating, brand, category, and product identity fields to organize product-research datasets.
• Analyze customer feedback: Filter rows where itemType is Review, then analyze rating, title, and text while retaining the matching usItemId and product context.
• Enrich product catalogs: Join name, brand, category, usItemId, productUrl, price, seller, and availability with internal product records.

🐙 Why Octoparse

• Ready-made Walmart workflow: Walmart Data Extractor handles Walmart US product URLs, listing and search URLs, item IDs, and keyword-based discovery without requiring users to build a new scraper.
• Flexible collection scope: Separate controls set list or search pagination, review collection, and review pagination for each product.
• Analysis-ready results: Product and review rows share the same 13 fields, making it easier to filter, join, deduplicate, and export the dataset.
• Cloud execution: Walmart Data Extractor runs in Octoparse Cloud, so collection does not depend on keeping a local computer running.
• Reusable web data platform: Octoparse combines a gallery of 680+ maintained ready-made scrapers, visual point-and-click authoring in Octoparse Desktop, cloud execution infrastructure, and an Open Platform. Existing templates and tasks can be run through supported API and MCP workflows, then exported for spreadsheets, dashboards, databases, and downstream AI analysis.

📝 Input

• Walmart URLs or Item IDs (MainKeys): Enter at least one Walmart US product-detail URL, listing URL, search URL, or bare item ID. This field is required and accepts multiple entries.
• Search Keywords (SearchKeys): Enter optional Walmart search keywords. Multiple keywords are supported; products discovered from them are added to the same run.
• Collect Reviews (includeReviews): Choose whether to create individual review rows. Review collection is enabled by default.
• Listing/Search Pages (pageSize): Set the number of listing or search-result pages to collect for each listing or keyword input. Leave blank to continue until a natural stop, subject to the template's 100-page safety limit.
• Review Pages per Product (reviewPageSize): Set the number of review-list pages to collect for each product. Leave blank to continue until a natural stop, subject to the template's 100-page-per-product safety limit.

🚀 How to Use

1. Open Walmart Data Extractor and click Try it!.
2. Enter one or more Walmart US URLs or item IDs in Walmart URLs or Item IDs (MainKeys), then add optional values in Search Keywords (SearchKeys).
3. Choose whether to collect reviews and set the two page-count controls when you want a bounded run.
4. Start the task in Octoparse Cloud.
5. Review Product and Review rows in Data Preview, then export the results in the needed format.

⚠️ Limitations

• Walmart Data Extractor targets the US marketplace at www.walmart.com; it does not switch to other Walmart country sites.
• Walmart Data Extractor stops listing or search pagination after 100 pages per input, even when Listing/Search Pages (pageSize) is blank or set above that limit.
• Walmart Data Extractor stops review pagination after 100 pages per product, even when Review Pages per Product (reviewPageSize) is blank or set above that limit.
• Walmart Data Extractor omits empty review shells and rating-only entries that contain neither a review title nor review text.

💡 Tips

• Start with one known Walmart product URL and a small review-page value, then confirm the product and review rows before expanding the batch.
• Use usItemId as the stable product key and itemType to separate product rows from review rows after export.
• Set explicit page values for repeatable scheduled runs; leaving either page control blank can produce a larger dataset as Walmart's result count changes.
• Deduplicate repeated products by usItemId when URLs, list pages, and keywords may discover the same Walmart item.

❓ FAQ

Can Walmart Data Extractor collect both product details and customer reviews?

Yes. Walmart Data Extractor creates product rows with fields such as priceInfo.price, availability, sellerName, and averageRating; when Collect Reviews (includeReviews) is enabled, it also creates review rows with rating, title, and text.

Can Walmart Data Extractor start from keywords as well as Walmart URLs?

Yes. Walmart Data Extractor accepts Walmart US product, listing, or search URLs and bare item IDs in Walmart URLs or Item IDs (MainKeys), and it accepts additional search keywords in Search Keywords (SearchKeys). The current form still requires at least one value in Walmart URLs or Item IDs (MainKeys).

How does Walmart Data Extractor keep reviews linked to products?

Walmart Data Extractor copies usItemId, productUrl, product name, seller, price, availability, category, brand, and average rating into each Review row, so exported reviews retain their product context.

Can I schedule and export data collected by Walmart Data Extractor?

Yes. Walmart Data Extractor runs in Octoparse Cloud and can be used with supported Octoparse scheduling and export workflows. Available schedules, formats, and API access depend on the user's Octoparse plan and enabled platform features.

How much does Walmart Data Extractor cost?

Walmart Data Extractor costs $1.00 per 1,000 output lines for Free and Standard users, $0.80 per 1,000 output lines for Professional users, and $0.60 per 1,000 output lines for Enterprise users.

🔗 Related Templates

• Target Product Details Scraper — Collect product names, descriptions, prices, unit prices, categories, and images from Target product URLs for an adjacent US retail dataset.
• Amazon Details Scraper — Collect a broader Amazon product-detail schema from URLs or ASINs across supported marketplaces for cross-retailer product research.
• Google Shopping Price Monitor (by Keyword) — Track shopping results by keyword when the workflow needs cross-store price discovery rather than Walmart-only product and review rows.