Walmart Product Scraper

What is Walmart Product Scraper?

The Walmart Product Scraper lets you extract structured product data from Walmart in bulk using keywords. Just enter one or more search terms, and the scraper will automatically collect the core product data you need. It is built for product research, competitor monitoring, and smarter operational decision-making.

• Scrape multiple product results in one run
• Extract rich, multi-dimensional product fields
• Set the number of result pages to scrape
• Support multiple Walmart domains
• Optionally extract all product variants

Compared with manual search, this scraper makes it much easier to collect Walmart product results at scale and turn them into structured output for research, monitoring, and downstream workflows.

Use cases for the Walmart Product Scraper

Efficient product research: Collect product names, prices, ratings, reviews, and category data in bulk to identify promising products faster. Competitor monitoring: Track how competing products are positioned across different keywords, including pricing, review signals, and seller activity. Price and shelf analysis: Monitor product prices, brands, specifications, and variants over time to support pricing analysis and shelf strategy optimization. Customer insight discovery: Use reviews, ratings, and tags to uncover what customers care about most and identify opportunities for product or content improvement. Automated product data collection: Replace manual search with repeatable workflows so your datasets stay accurate, consistent, and up to date.

What data can you extract from Walmart?

How to scrape Walmart data

The Walmart Product Scraper is designed to be simple to use, so you can start extracting data quickly even without prior scraping experience.

1. Sign up and create your CoreClaw account with your email address.
2. Open the Walmart Product Scraper.
3. Add one or more Walmart product keywords.
4. Choose optional filters such as the Walmart domain, number of pages to scrape, and whether to extract all product variants.
5. Click Start and wait for the extraction to finish.
6. Download the results in JSON or CSV format.

➡️ Input

Enter the product keywords you want to search on Walmart, such as iPhone or leggings. To cover more results, you can combine multiple related but non-duplicative keywords. This usually helps you discover a wider range of products.

⬅️ Output

When the run is complete, the collected Walmart data is organized under the Output tab as a structured dataset. For easier review, results are displayed in tables and tabs, and can be downloaded in CSV or JSON format.

JSON example

1[
2  {
3    "url": "https://www.walmart.com/ip/Starburst-Pink-Yellow-Mix-Chewy-Fruit-Candy-3-lbs-Original-Strawberry-Lemon-Soft-Chew-Candies-Bulk-Family-Size-Assortment-Pack-Individually-Wrapped-4/1016450755",
4    "sku": "1016450755",
5    "product_id": "1016450755",
6    "upc": "808887055096",
7    "gtin": "808887055096",
8    "title": "Starburst Strawberry and Lemon Soft Chew - 3 lbs (48 oz) Family Size Pack Individually Wrapped, Pink and Yellow Mix",
9    "seller": "Fire Deals",
10    "seller_url": "https://www.walmart.com/global/seller/2165",
11    "image_urls": [
12      "https://i5.walmartimages.com/seo/example-1.jpeg",
13      "https://i5.walmartimages.com/asr/example-2.jpeg"
14    ],
15    "main_image": "https://i5.walmartimages.com/seo/example-1.jpeg",
16    "review_count": 0,
17    "rating": null,
18    "offers": [
19      {
20        "seller": "Fire Deals",
21        "final_price": 20
22      }
23    ],
24    "categories": [
25      "Food",
26      "Candy",
27      "Gummy & Chewy Candy",
28      "Chewy Candy"
29    ],
30    "breadcrumb_text": "Food > Candy > Gummy & Chewy Candy > Chewy Candy",
31    "brand": "Starburst",
32    "condition": "New",
33    "location": {
34      "postal_code": "45011",
35      "province_code": "OH",
36      "city": "Hamilton",
37      "store_id": "3502"
38    },
39    "store_name": "Hamilton Supercenter",
40    "description": "<ul><li>Example product description</li></ul>",
41    "short_description": "Example short description",
42    "variants": [],
43    "product_name": "Starburst Strawberry and Lemon Soft Chew - 3 lbs (48 oz) Family Size Pack Individually Wrapped, Pink and Yellow Mix",
44    "category": {
45      "category_url": "https://www.walmart.com/browse/food/chewy-gummy-candy",
46      "category_name": "Chewy Candy",
47      "root_category_name": "Food"
48    },
49    "sizes": [],
50    "colors": [],
51    "ingredients": null,
52    "success": true,
53    "error_code": 200,
54    "error": ""
55  }
56]

FAQ

How does the Walmart Product Scraper work?

The Walmart Product Scraper automatically visits Walmart search result pages and converts unstructured page content into structured CSV and JSON output. You only need to provide product keywords and related parameters, and the scraper handles the collection process for you.

What kind of data can it extract?

The scraper can typically return product URLs, prices, SKUs, currency, GTINs, brands, reviews, descriptions, product names, categories, images, ratings, sizes, colors, seller information, nutrition facts, and product variants. Exact fields may vary depending on the product type and page content.

Does it support API integration?

Yes. In addition to the visual dashboard, the scraper can also be integrated into API-based workflows, making it easier for developers to connect collection jobs to internal systems, data pipelines, or automation tasks.

Is the data real-time?

Yes. Each run collects the latest publicly available Walmart data rather than relying on cached results, which helps keep the output fresh and useful.

Do I need coding skills to use this scraper?

No. The Walmart Product Scraper is a no-code solution built for both technical and non-technical users. You can configure tasks, run jobs, and download results through a simple graphical interface.

Can it extract all product variants?

Yes. You can use the all_variations parameter to control whether all product variants should be extracted. This is especially useful for products with multiple sizes, colors, or packaging options.

Which export formats are supported?

The output can be exported in structured formats such as CSV and JSON, making it easy to use in spreadsheets, BI tools, databases, and internal systems.

Is scraping Walmart product data legal?

Publicly available product data is commonly used for research, analytics, and business intelligence. That said, users should still comply with local data privacy regulations and review the target website’s terms of service and compliance requirements.