Walmart Product Scraper

Scrape Walmart products by keyword, product ID, or category URL and get clean, structured rows: title, brand, price, rollback, rating, review count, stock, seller, specs, and images. Products from $1 / 1,000 results, and you can pull thousands of products in one run. Pay only per result, no subscription.

Why this Actor?

Most Walmart scrapers stop at keyword search. This one pulls 5 data surfaces, sorts by price and recency, resolves item IDs to full product pages, and keeps running when one input goes bad.

Capability	Walmart Product Scraper (Data Forge)	Typical Walmart scrapers
Data surfaces in one run	5: search, product detail, best sellers, deals, category URLs	Search only
Sorting	Price low to high, price high to low, best seller, newest	Relevance only
Detail lookup by item ID	Resolve a us_item_id to its full product page	Not available
Bad input handling	Free error row, the run keeps going	One bad input fails the run
Billing	Pay per result	Flat monthly pricing

What does the Walmart Product Scraper do?

The Walmart Product Scraper turns Walmart.com into structured data you can analyze. Feed it search keywords, product IDs, or category URLs and it returns a flat row per product with pricing, ratings, stock, and seller fields. Pick one mode or combine several in a single run.

Mode	What you give it	What you get back
🔎 Search	A keyword like laptop	Paginated listing rows for the search
📦 Product detail	A product ID or Walmart URL	Detail rows with specs, model, UPC, images
🏆 Bestsellers	A category (optional)	Ranked top-selling listing rows
🔥 Deals	A category (optional)	Discounted and rollback listing rows
🗂 Category browse	A category path or URL	Listing rows for that category

Turn on Fan out to product detail and each listing row is enriched with a second call that pulls its product page (specifications, images, model number).

What data can you get from a Walmart product?

Each row carries top-level columns plus the complete product object nested under data:

• name - product title
• brand - manufacturer brand
• price - current selling price
• original_price - pre-discount list price (rollback signal)
• rating - average star rating, 1.0 to 5.0
• review_count - number of customer reviews
• seller_name - Walmart.com or the marketplace seller
• availability / in_stock - stock status as text and boolean
• id / us_item_id - catalog ID and the numeric item ID used for reviews and offers
• model_number / upc - manufacturer model and barcode (detail rows)
• url / image_url - product link and primary image
• data - the complete payload, including specifications and the image gallery

Output row types

The row_type field labels each row so mixed runs stay easy to split:

row_type	Emitted by	What the row holds
search_result	Search mode	Listing row for a keyword search
product_detail	Product mode or fan-out	Full detail row with specs, model, UPC, images
bestseller	Bestsellers mode	Ranked top-selling listing row
deal	Deals mode	Rollback or clearance listing row
category_result	Category mode	Listing row for a category page

Input modes

Seven ready-to-run recipes. Paste one into the input, press Start, and export JSON, CSV, or Excel.

1. Search with prices and ratings

A merchandiser pulling a 100-row price-and-rating snapshot for one keyword.

{
  "searchQueries": ["laptop"],
  "dataTypes": ["search"],
  "maxResultsPerType": 100
}

2. Cheapest first

A deal hunter who wants the lowest-priced listings sorted to the top.

{
  "searchQueries": ["tv"],
  "dataTypes": ["search"],
  "sort": "price_low",
  "maxResultsPerType": 100
}

3. Best sellers by category

A category manager tracking the top-selling products in electronics.

{
  "dataTypes": ["bestsellers"],
  "bestsellersDealsCategory": "electronics",
  "maxResultsPerType": 100
}

4. Daily deals monitor

An arbitrage seller watching fresh rollbacks and clearance each morning.

{
  "dataTypes": ["deals"],
  "maxResultsPerType": 100
}

5. Product details by item ID

An analyst resolving a known us_item_id to specs, model number, and images.

{
  "productIds": ["18533160127"],
  "dataTypes": ["product"]
}

6. Category page by URL

A researcher mapping a category straight from its Walmart browse URL.

{
  "categoryUrls": ["https://www.walmart.com/browse/electronics/3944"],
  "dataTypes": ["category"],
  "maxResultsPerType": 100
}

7. New arrivals

A trend-spotter surfacing the newest laptops added to Walmart.

{
  "searchQueries": ["laptop"],
  "dataTypes": ["search"],
  "sort": "new",
  "maxResultsPerType": 100
}

How to scrape Walmart products

1. Open the actor. The Search queries field is prefilled with laptop, so a first run returns real data with zero setup.
2. In Data types to scrape, choose the modes you want: Search, Product detail, Bestsellers, Deals, or Category browse.
3. Add your inputs: keywords in Search queries, product IDs or URLs in Product IDs, or paths in Category URLs.
4. Set Max results per type (20 for a quick sample, 100 for a solid dataset).
5. Optionally turn on Fan out to product detail to enrich each listing with its product page.
6. Click Start and export the dataset as JSON, CSV, or Excel.

Input example

{
  "searchQueries": ["laptop", "4k tv"],
  "dataTypes": ["search"],
  "maxResultsPerType": 50,
  "sort": "best_match",
  "includeProductDetails": false
}

Output example

A search listing row:

{
  "query": "laptop",
  "row_type": "search_result",
  "id": "5EI9XQX3W2YN",
  "us_item_id": "853065593",
  "name": "HP 15.6\" Laptop, Intel Core i5, 8GB RAM, 256GB SSD, Silver",
  "brand": "HP",
  "price": 379.00,
  "original_price": 499.00,
  "rating": 4.4,
  "review_count": 1283,
  "seller_name": "Walmart.com",
  "availability": "In stock",
  "in_stock": true,
  "url": "https://www.walmart.com/ip/HP-15-6-Laptop/853065593",
  "image_url": "https://i5.walmartimages.com/asr/abc123.jpeg",
  "data": { "...": "complete product object" }
}

A product detail row:

{
  "query": "853065593",
  "row_type": "product_detail",
  "id": "5EI9XQX3W2YN",
  "us_item_id": "853065593",
  "name": "HP 15.6\" Laptop, Intel Core i5-1334U, 8GB RAM, 256GB SSD, Windows 11, Silver",
  "brand": "HP",
  "price": 379.00,
  "original_price": 499.00,
  "rating": 4.4,
  "review_count": 1283,
  "availability": "In stock",
  "model_number": "15-fd0083wm",
  "upc": "196068861234",
  "url": "https://www.walmart.com/ip/HP-15-6-Laptop/853065593",
  "image_url": "https://i5.walmartimages.com/asr/abc123.jpeg",
  "data": { "specifications": { "Processor": "Intel Core i5-1334U", "RAM": "8 GB", "Storage": "256 GB SSD", "Screen Size": "15.6 in" }, "images": ["https://i5.walmartimages.com/asr/abc123.jpeg"] }
}

How much does it cost to scrape Walmart products?

You pay per result, billed by Apify on top of your plan.

• Listing rows (search, category, bestsellers, deals): $0.001 each, so $1 per 1,000 products.
• Product detail rows: $0.0036 each, so $3.60 per 1,000 detail rows.

Worked math: the $5 in free monthly credits on the Apify free plan covers about 5,000 listing rows ($5 / $0.001). Want the deep dataset? Scrape 1,000 search listings and fan out product detail on each for roughly $4.60 ($1 for listings + $3.60 for detail). Error rows stay free, so failed lookups never cost you.

What can you use Walmart product data for?

• Price monitoring - track price and rollback changes across thousands of SKUs on a schedule.
• Competitor research - benchmark your catalog against Walmart pricing, ratings, and stock.
• Assortment analysis - map what brands and products sell in a category and at what price points.
• Arbitrage sourcing - surface rollbacks and clearance deals to flip on other marketplaces.
• MAP compliance - watch for sellers breaking minimum advertised price.
• Stock and availability tracking - know when products go in and out of stock.
• Review and rating intelligence - rank products by review volume and average rating.
• Catalog enrichment - fill your product database with model numbers, UPCs, specs, and images.
• Dynamic repricing - feed live Walmart prices into your own pricing engine.

Is it legal to scrape Walmart?

Scraping publicly available data is generally legal in the US, and this actor collects only public product information that any shopper can see, without private or account-gated data. You are responsible for how you use the output. Review Walmart's terms of service, respect copyright and database rights, and avoid collecting personal data. If in doubt, consult a lawyer.

Related actors

Part of the Data Forge marketplace fleet:

• Walmart Reviews Scraper - pull product reviews with rating, title, text, author, date, and verified-purchase status.
• Walmart Intelligence Scraper - the umbrella actor combining product search, detail, and reviews in one run.
• Amazon Products Scraper - the same structured-row approach for Amazon search and product detail.

FAQ

Do I need a Walmart account? No. You provide keywords, product IDs, or category URLs. No credentials are required.

Is it legal to scrape Walmart product data? Collecting public data is generally legal in the US, and this actor reads only public catalog fields a shopper sees, with no account-gated or personal data. You are responsible for how you use the output, so review Walmart's terms and your local law. See the legality note above for detail.

How fresh is the data? Each run pulls the current Walmart catalog, so prices, rollbacks, ratings, and stock reflect what is live when the run starts. Re-run on a schedule to keep a fresh dataset.

What happens if one of my queries is bad? A dead keyword, missing product ID, or broken URL returns a free error row and the run keeps going. One bad input never kills the batch, and error rows are not billed.

Can I schedule this for price monitoring? Yes. Use Apify Schedules to run the actor hourly, daily, or on a custom cron, then diff each dataset to track price, rollback, and stock moves over time.

What input formats work for products? Use a catalog ID, a numeric item ID, or a Walmart product URL. The actor normalizes each one for you.

Can I run this from my own code or an AI agent? Yes. Start runs and read results through the Apify API, the JavaScript and Python SDKs, or MCP for AI agents and assistants. JSON, CSV, and Excel exports are available programmatically.

Why are some fields empty? Listing rows carry fewer fields than detail rows. An empty value means the field does not apply to that row type or was not published for that product. Model number and UPC appear on detail rows.

How many products can I scrape per run? Set Max results per type up to 500 per vertical, and combine modes to pull thousands of products in a single run.

How do I get specs and the product image gallery? Use Product detail mode, or turn on Fan out to product detail so each listing row is enriched with its product page.

Support