Walmart Data Extractor

This tool digs through Walmart’s catalog and pulls back rich product data without the usual friction. It handles everything from item details to reviews, variations, and filtered category results. If you need structured Walmart data at scale, this scraper keeps things simple and fast.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

This project collects product information directly from Walmart’s site and organizes it into clean, consumable data. It’s built for analysts, developers, researchers, and anyone who depends on accurate ecommerce insights.

Why This Matters

• Helps you work around the lack of an official data source for Walmart listings.
• Captures detailed attributes including variations, sellers, pricing, and images.
• Supports keyword search, category scraping, and location-based discovery.
• Pulls full product reviews and optional review-only exports.
• Built to handle large runs with stable performance and minimal overhead.

Features

Feature	Description
Product detail extraction	Collects names, prices, brands, IDs, images, variants, and seller information.
Review harvesting	Retrieves complete review lists for any supported product.
Search scraping	Extracts structured data from Walmart keyword search results.
Category and subcategory scraping	Handles nested categories and custom filtering.
Location-based results	Allows ZIP-based location targeting to get region-specific product data.
Pagination control	Limits scraping to a defined number of pages for tighter control.
Item caps	Stops scraping after a user-defined item limit.
Output mapping	Lets you reformat results using custom transformation functions.

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What Data This Scraper Extracts

Field Name	Field Description
id	Unique identifier of the product.
name	Product title as shown in listings.
brand	Brand associated with the item.
price	Current displayed price.
images	Array of product image URLs.
seller	Information about the seller or marketplace provider.
variants	Color, size, style, and other variations.
reviews	Optional block containing user reviews.
url	Original Walmart link scraped.
category	Category or subcategory where the product was discovered.

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Example Output

[
  {
    "id": "155345382",
    "name": "Mainstays Blue Sunflower Mix Bouquet",
    "brand": "Mainstays",
    "price": 14.98,
    "images": [
      "https://i5.walmartimages.com/...."
    ],
    "seller": "Walmart",
    "variants": [],
    "reviews": [],
    "url": "https://www.walmart.com/ip/Mainstays-Blue-Sunflower-Mix-Bouquet/155345382",
    "category": "Home"
  }
]

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Directory Structure Tree

Walmart Data Extractor/
├── src/
│   ├── index.js
│   ├── engine/
│   │   ├── fetcher.js
│   │   ├── parser.js
│   │   └── reviews.js
│   ├── helpers/
│   │   ├── http.js
│   │   └── pagination.js
│   ├── outputs/
│   │   └── formatter.js
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample-input.json
│   └── sample-output.json
├── package.json
└── README.md

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Use Cases

• Retail analysts use it to track product changes so they can keep pricing models competitive.
• Ecommerce teams pull inventory data to benchmark categories and adjust merchandising strategies.
• Data scientists harvest reviews to build sentiment analysis pipelines and market research models.
• Developers incorporate structured product feeds into apps without relying on unreliable manual data.
• Marketplace operators monitor competing listings to refine catalog mapping and dynamic pricing rules.

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FAQs

Does it support ZIP-based location targeting? Yes. You can use a ZIP code to fetch regionally adjusted product data.

Can I scrape only reviews? Absolutely. Setting the appropriate flag retrieves only reviews while skipping all other product data.

What if I only need a few pages? You can define a page limit to keep runs short and focused.

Can I reshape the output? Yes—custom mapping functions let you extract or transform fields any way you want.

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Performance Benchmarks and Results

Primary Metric: Processes roughly 50 product detail requests in about two minutes under typical network conditions.

Reliability Metric: Maintains a high completion rate with stable handling of pagination, variations, and mixed content pages.

Efficiency Metric: Optimized request flow ensures lightweight resource usage even during long scraping sessions.

Quality Metric: Delivers high-fidelity product data with full attribute coverage, including optional reviews and variants.

"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington Marketer ★★★★★

"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza SEO Affiliate Expert ★★★★★

"Exceptional results, clear communication, and flawless delivery. Bitbash nailed it." Syed Digital Strategist ★★★★★