Walmart Scraper

Scrape Walmart products, prices and reviews at scale. Products from $1 / 1,000, reviews from $0.60 / 1,000, full product detail $3.60 / 1,000. Search the catalog, browse categories, pull best sellers and rollback deals, get full product detail and collect reviews, then export thousands of clean rows in a single run. Pay only for the rows you keep.

No setup, no browser, no infrastructure to manage. Pick what you need under What to scrape, press Start, and get flat tables out: Products and Reviews.

Prefer a single-purpose tool? Data Forge also ships the focused Walmart Product Scraper and Walmart Reviews Scraper.

Why this Actor?

One umbrella Actor covers 6 Walmart data surfaces and can combine them in a single run, so you skip wiring separate tools together and joining their output by hand. Winning cells are in bold.

Capability	This Actor	Typical single-purpose Walmart actors
Walmart surfaces in one Actor	6: search, product detail, best sellers, deals, category URLs, reviews	1 surface per actor
Product detail + reviews in one run	Yes - the Product 360 mode below	Run 2 actors, then join the output yourself
Search-to-detail enrichment	1 toggle - includeProductDetails	Not offered
Sort orders on search and deals	5: best match, price low, price high, best seller, newest	Limited or none
Best sellers and rollback deals by category	Both, category-scoped	Separate actors, or missing
Combined product + review intelligence	1 dataset, 6 row types	2 datasets to reconcile
Billing	Pay per result, $5 free monthly credit	Often per-run or a subscription

What does the Walmart Scraper do?

It turns a keyword, a product ID, a category or a deals list into structured Walmart data. Tick 1 or more data types and the Actor pulls exactly that:

Data type	What it returns
🔎 Search	Products matching your keyword, paginated.
📦 Product detail	A full record for specific products (specs, images, model, brand, seller).
🏆 Best sellers / 🔥 Deals	Best-seller and rollback / clearance lists by category.
🗂 Category	Browse a Walmart category.
⭐ Reviews	Product reviews, sorted and paginated.

The dataset opens on ready-made views (Products, Reviews), so the right columns are in front of you.

What data can you get from Walmart?

Per product: item ID, title, brand, price, was-price, rollback flag, rating, review count, in-stock status, seller name, model number, UPC, images and the product URL.

Per review: reviewer name, star rating, review title, review text, date, helpful votes and verified-purchase flag.

Each row also carries the raw source object under a data field, so nothing the page exposes is dropped.

Input modes

4 published example tasks map 1:1 to the common jobs below. Copy a JSON block into the input editor, or open the matching example task and press Start.

1. Product 360 - detail plus reviews in one run

Sellers and product teams: pull a product's full spec sheet and up to 100 recent reviews for the same item in a single run.

{
  "productIds": ["18533160127"],
  "dataTypes": ["product", "reviews"],
  "maxReviewsPerProduct": 100
}

2. Market snapshot - search enriched with full details

Category managers: map a keyword's top 40 listings and enrich each one with a full product-detail record.

{
  "searchQueries": ["air fryer"],
  "dataTypes": ["search"],
  "includeProductDetails": true,
  "maxResultsPerType": 40
}

3. Category intelligence with details

Merchandisers: walk a Walmart category page and enrich the first 40 items with full detail.

{
  "categoryUrls": ["https://www.walmart.com/browse/electronics/3944"],
  "dataTypes": ["category"],
  "includeProductDetails": true,
  "maxResultsPerType": 40
}

4. Best-sellers deep-dive

Trend and sourcing analysts: rank a category's best sellers and enrich the top 40 with full detail.

{
  "dataTypes": ["bestsellers"],
  "bestsellersDealsCategory": "electronics",
  "includeProductDetails": true,
  "maxResultsPerType": 40
}

How to scrape Walmart

1. Under What to scrape, tick the data types you want. Search is prefilled, so the Actor runs on the first click.
2. Fill the matching input: keywords for Search, item IDs or product URLs for Product detail / Reviews, a category URL for Category. Product input is adaptive: an item ID or a product URL both resolve.
3. Set the sort, deals category and reviews options in the collapsible sections.
4. Press Start. Export to JSON, CSV, Excel or Google Sheets, or pull from the Apify API.

Input example

{
  "dataTypes": ["search"],
  "searchQueries": ["air fryer"],
  "sort": "best_seller",
  "maxResultsPerType": 40,
  "includeProductDetails": true
}

Output

Each dataset item has a row_type field, so the 6 surfaces stay easy to filter and split.

row_type	What it is	Key fields
search_result	1 listing from a keyword search	name, brand, price, rating, seller_name, in_stock, url
category_result	1 listing from a category browse	name, brand, price, rating, in_stock, url
product_detail	Full detail record for 1 product	name, brand, price, model_number, upc, rating, review_count, image_url
bestseller	1 item from a category best-sellers list	name, brand, price, rating, url
deal	1 rollback / clearance item	name, brand, price, original_price, url
review	1 product review	author, rating, title, text, date, verified_purchase, helpful_count

Output examples

Search-result row:

{
  "query": "air fryer",
  "row_type": "search_result",
  "us_item_id": "967557625",
  "name": "Ninja AF101 Air Fryer, 4 Qt",
  "brand": "Ninja",
  "price": 89.0,
  "original_price": 119.0,
  "rating": 4.8,
  "review_count": 38400,
  "seller_name": "Walmart.com",
  "in_stock": true,
  "url": "https://www.walmart.com/ip/967557625"
}

Product-detail row:

{
  "query": "18533160127",
  "row_type": "product_detail",
  "us_item_id": "18533160127",
  "name": "Ninja AF101 Air Fryer, 4 Qt, Black and Grey",
  "brand": "Ninja",
  "price": 89.0,
  "original_price": 119.0,
  "rating": 4.8,
  "review_count": 38400,
  "model_number": "AF101",
  "upc": "622356561105",
  "url": "https://www.walmart.com/ip/18533160127"
}

Review row:

{
  "query": "18533160127",
  "row_type": "review",
  "review_id": "a1b2c3d4",
  "author": "Jamie R.",
  "rating": 5,
  "title": "Works great",
  "text": "Crispy results each time, easy to clean.",
  "date": "2026-05-22",
  "verified_purchase": true,
  "helpful_count": 12
}

How much does it cost to scrape Walmart?

You pay per result, billed by Apify, with no subscription. With the $5 free monthly credit you can pull, for example:

• ~8,300 reviews (reviews from $0.60 / 1,000), or
• ~5,000 product listings (products from $1 / 1,000), or
• ~1,380 full product details ($3.60 / 1,000).

Detail fan-out is opt-in, so a default search run stays cheap. Failed items (a product that no longer exists, an out-of-stock region) are returned for visibility and are never charged.

What can you use Walmart data for?

• Price and assortment monitoring - track price, rollback status and availability across a catalog.
• Competitor and market research - compare brands, ratings and price bands in a category.
• Best-seller and deal tracking - watch what is rising and discounted by category.
• Product intelligence - specs, images, model and seller for catalog enrichment.
• Review mining and sentiment - feed product reviews into NLP for CX insight.
• Reseller and arbitrage sourcing - spot clearance and rollback opportunities at scale.
• MAP and pricing compliance - monitor seller prices against policy.

Is it legal to scrape Walmart?

Scraping publicly available Walmart data is legal in most jurisdictions when you collect only public information and respect personal-data laws such as GDPR and CCPA. This Actor returns only data a visitor can see on Walmart.com. You are responsible for how you use the output, so consult a lawyer for your specific case.

FAQ

Can I run just 1 data type? Yes. Tick only what you need under What to scrape; the rest stays idle and uncharged.

Can I get product detail and reviews for the same item in 1 run? Yes - that is the Product 360 mode. Pass productIds and set dataTypes to ["product", "reviews"]; both surfaces land in the same dataset, keyed by us_item_id.

When should I use this Actor vs the split actors? Use this umbrella when you want 2 or more surfaces, or a product + review combo, in a single run. Reach for Walmart Product Scraper or Walmart Reviews Scraper when you only need 1 surface at high volume and want the leanest input form.

What happens with a bad product ID or a dead listing? The Actor writes a free error row (with error_code and error_message), then keeps going with the next item. You are not charged for error rows, and 1 bad input does not stop the run.

How fresh is the data? Rows are fetched live from Walmart on each run, so prices, stock and ratings reflect the moment the Actor runs.

How many reviews can I get per product? Up to the maxReviewsPerProduct cap you set (1 to 1,000), in your chosen sort order.

Can I enrich a search or category with full detail? Yes. Turn on includeProductDetails and each listing row is enriched with a product-detail record (adds a product-detail charge per enriched row).

Can I call it from code? Yes. Run it via the Apify API, the Apify client SDKs, or an MCP server, and read results from the dataset.

Related actors

Part of the Data Forge Walmart and marketplace fleet:

• Walmart Product Scraper - focused product search, category, best sellers, deals and detail.
• Walmart Reviews Scraper - focused, high-volume review extraction.
• Amazon Scraper - products, prices and reviews across Amazon marketplaces.

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