Walmart Product Scraper — Prices, Deals & Stock

Walmart Product Scraper

Scrape Walmart products from keywords, category pages, or product URLs. Get prices, was prices and savings, stock, ratings, sellers, deal badges, UPC, specifications, and variants. Filter by price and brand.

What does Walmart Scraper do?

Walmart Scraper extracts product data from Walmart search results, Walmart category pages (categoryUrls), and known Walmart.com product URLs or item IDs (productUrls). Get structured product details including prices, discounts, inventory availability, ratings, review counts, seller information, deal badges, and images. Search by keyword with sort options and price or brand filters, fetch full details for specific products, or combine all of them in one run.

Use it for price monitoring, competitive intelligence, dropshipping research, market analysis, and deal tracking.

Who is it for?

Walmart Scraper is built for e-commerce analysts, dropshippers, price comparison services, market researchers, and data analysts who need structured Walmart product data at scale. Whether you're monitoring competitor pricing, building a product comparison tool, or analyzing market trends, this scraper gives you clean, structured data from Walmart search results.

Use cases

• Price monitoring — Track product prices across categories or submit known Walmart.com product URLs for repeatable product-level checks. Compare current prices with original prices and savings amounts.
• Competitive intelligence — Research product listings, seller distribution, and pricing strategies on Walmart.
• Dropshipping research — Find products with high ratings and strong seller reviews. Identify pricing arbitrage opportunities.
• Market analysis — Analyze product availability, rating distributions, and seller competition across product categories.
• Deal tracking — Monitor rollback deals, clearance items, and "best seller" badges to find the best offers.
• E-commerce analytics — Track new arrivals, price trends, and review counts for product categories.

Why use Walmart Scraper?

• Rich data extraction — Every product includes price, normalized stock availability, original price, savings, rating, review count, seller name, deal badges, and product image.
• Category pages and filters — Paste /browse/... category URLs or copied search URLs, and narrow results with minPrice, maxPrice, and brands.
• Full product details — Add Walmart.com US URLs or item IDs through productUrls to get UPC, model, specifications, variants, all images, seller rating, and return policy.
• Multiple sort options — Sort by best match, best seller, price (low/high), highest rating, or new arrivals.
• You get what you ask for — Pagination follows maxProductsPerSearch, up to everything Walmart serves for that search (at most 25 pages, ~40 products per page). The run's status message says how many you got and why it stopped.
• Deal detection — Automatically identifies products on sale with savings amounts and deal badges like "Rollback" and "Best seller".
• Seller information — Extract seller names to identify Walmart.com vs. third-party sellers.
• Managed proxy recovery — Uses bounded US residential and Apify Unblocker fallback when the direct request is blocked.
• Pay-per-event pricing — You only pay for products scraped. No monthly subscription.

What data can you extract?

Each product in the output includes:

Field	Description
usItemId	Walmart item identifier
name	Product name
price	Current price (number)
priceString	Formatted price string (e.g., "$199.69")
wasPrice	Original price before discount
savings	Savings text (e.g., "SAVE $269.31")
onSale	Whether the product is discounted
rating	Average rating (0-5)
reviewCount	Number of customer reviews
seller	Seller name (e.g., "Walmart.com")
fulfillmentType	Delivery/fulfillment method
flag	Deal badge (e.g., "Rollback", "Best seller", "100+ bought since yesterday")
thumbnail	Product image URL
url	Direct link to the Walmart product page
isSponsored	Whether the listing is a sponsored placement
availabilityStatus	Normalized Walmart inventory status, such as IN_STOCK or OUT_OF_STOCK; null when Walmart does not provide it
inStock	true or false only when Walmart provides a clear stock signal; otherwise null
wasPriceValue, savingsAmount, discountPercent	The same discount as numbers, ready to sort on; null when there is no discount
sellerId	Walmart seller identifier
category, productType	Walmart category path and product type
description	Plain-text description; search rows carry the short version when Walmart provides it
fulfillmentOptions, deliveryDate	Delivery or pickup options and the estimated delivery date for Walmart's default location
additionalOfferCount	Other seller offers Walmart reports
searchQuery, position	The keyword or category URL the row came from, and its rank there; null on rows from productUrls
scrapedAt	Timestamp when the data was extracted

Rows from productUrls also include upc, model, manufacturerProductId, condition, sellerType, sellerRating, sellerReviewCount, images, specifications, variants, returnable, freeReturns, and returnWindowDays.

Output example

{
  "usItemId": "17828556665",
  "name": "JLab Go Air Pop Bluetooth Earbuds, True Wireless with Charging Case",
  "price": 23.78,
  "priceString": "$23.78",
  "wasPrice": "$29.38",
  "savings": "SAVE $5.60",
  "onSale": true,
  "rating": 4.5,
  "reviewCount": 34286,
  "seller": "Walmart.com",
  "fulfillmentType": "",
  "flag": "500+ bought since yesterday",
  "thumbnail": "https://i5.walmartimages.com/seo/...",
  "url": "https://www.walmart.com/ip/JLab-Go-Air-Pop-Bluetooth-Earbuds/...",
  "isSponsored": false,
  "availabilityStatus": "IN_STOCK",
  "inStock": true,
  "wasPriceValue": 29.38,
  "savingsAmount": 5.6,
  "discountPercent": 19,
  "sellerId": "F55CDC31AB754BB68FE0B39041159D63",
  "category": "Electronics/Headphones/Earbuds",
  "productType": "Headphones",
  "description": "True wireless earbuds with a charging case.",
  "fulfillmentOptions": ["DELIVERY"],
  "deliveryDate": "2026-03-05T22:59:00.000Z",
  "additionalOfferCount": null,
  "searchQuery": "wireless earbuds",
  "position": 1,
  "scrapedAt": "2026-03-03T01:40:32.821Z"
}

Input parameters

Parameter	Type	Default	Description
searchQueries	array	[]	Optional keywords to search on Walmart. Each keyword runs a separate search.
categoryUrls	array	[]	Optional https://www.walmart.com/browse/... category pages or copied /search?q=... URLs. Filters already in the URL are kept.
productUrls	array	[]	Optional Walmart.com product URLs or numeric item IDs for full product details and price monitoring. Duplicate item IDs are fetched once.
maxProductsPerSearch	integer	100	Maximum number of products to return for each keyword or category URL.
maxSearchPages	integer	none	Optional hard limit on result pages per keyword or category. Leave it out to keep paging until maxProductsPerSearch is reached or Walmart has no more results.
sort	string	"best_match"	Sort: best_match, best_seller, price_low, price_high, rating_high, new.
minPrice, maxPrice	number	none	Only return products within this USD price range.
brands	array	[]	Only return products from these brands, spelled as on Walmart. Walmart's trending and recommendation carousels are left out, so a narrow filter can return fewer products than you asked for.
maxRequestRetries	integer	5	Upper bound on attempts per request (1–10). Recovery can stop earlier for unusable delivered pages or exhausted routes.

How to scrape Walmart products

1. Open Walmart Scraper in Apify Console.
2. Enter search keywords or categoryUrls (for discovery), Walmart.com US product URLs or item IDs in productUrls (for known-product details), or any mix.
3. For searches and categories, choose a sort order, optional price and brand filters, and the maximum products.
4. Click Start and download results as JSON, CSV, or Excel.

At least one search keyword, category URL, or product URL is required. Invalid or non-US Walmart URLs are skipped with an explicit warning; valid URLs continue independently. A run with no valid input at all fails right away, with no charge.

How much does it cost to scrape Walmart?

Walmart Scraper uses pay-per-event pricing. The pricing shown in Console for your run and subscription tier is authoritative. There is a $0.001 start event once the input is valid, including runs that then cannot extract a product.

Result billing

• Search and category records use product; any detail enrichment of those search records is included, with no second result charge.
• Useful records retrieved from submitted productUrls use product-detail instead of product. Proxy selection never changes the event.
• Repeated submitted URLs for the same item are fetched once. Direct URLs run first. A successfully returned direct item is not emitted or charged again if it appears in search in that run. If direct retrieval fails, a later search record may still be returned and charged as product. Search continues to deduplicate within each keyword; a record returned for two different keywords remains two listing records, each charged once.
• Failed extraction attempts have no result charge. Unknown prices remain null; an identified product with truthful unknown fields is still a useful record.

Current result prices (since November 2, 2026):

Tier	Search record	Submitted URL record
FREE	$0.0046	$0.0069591
BRONZE	$0.004	$0.0060514
SILVER	$0.00312	$0.0047201
GOLD	$0.00112	$0.0036308
PLATINUM	$0.00112	$0.0036308
DIAMOND	$0.00112	$0.0036308

BRONZE examples, including the start event:

• Ten search records: $0.041.
• Ten submitted-URL records: $0.061514.
• Three successful submitted URLs plus seven other search records: $0.0471542. Repeating those three URLs or seeing them again in search adds no extra direct-item charge.

Older pinned builds that emit only product keep that event mapping. No monthly subscription. Platform compute and proxy costs are included in the event prices.

API usage

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('automation-lab/walmart-scraper').call({
    searchQueries: ['laptop'],
    maxProductsPerSearch: 40,
    sort: 'price_low',
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(product => {
    console.log(`$${product.price} - ${product.name} (${product.availabilityStatus ?? 'availability unknown'})`);
});

Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')

run = client.actor('automation-lab/walmart-scraper').call(run_input={
    'searchQueries': ['laptop'],
    'maxProductsPerSearch': 40,
    'sort': 'price_low',
})

items = client.dataset(run['defaultDatasetId']).list_items().items
for product in items:
    status = product.get('availabilityStatus') or 'availability unknown'
    print(f"${product['price']} - {product['name']} ({status})")

cURL

curl "https://api.apify.com/v2/acts/automation-lab~walmart-scraper/runs" \
  -X POST \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "searchQueries": ["organic coffee"],
    "maxProductsPerSearch": 40,
    "sort": "best_match"
  }'

Use with AI agents via MCP

Walmart Scraper is available as a tool for AI assistants that support the Model Context Protocol (MCP).

Setup for Claude Code

$claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/walmart-scraper"

Setup for Claude Desktop, Cursor, or VS Code

Add this to your MCP config file:

{
    "mcpServers": {
        "apify": {
            "url": "https://mcp.apify.com?tools=automation-lab/walmart-scraper"
        }
    }
}

Example prompts

Once connected, try asking your AI assistant:

• "Search Walmart for 'organic coffee' and get prices"
• "Compare Walmart prices for this product list"
• "Find the best-selling laptops on Walmart under $500"

Learn more in the Apify MCP documentation.

Integrations

Walmart Scraper works with all standard Apify integrations:

• Webhooks — Get notified when a scraping run finishes.
• API — Start runs and fetch results programmatically with REST API or official clients.
• Scheduling — Run daily to track price changes and new deals.
• Storage — Export as JSON, CSV, or Excel. Push to Google Sheets, Slack, or email.
• Zapier / Make / n8n — Connect Walmart data to thousands of apps and workflows.
• Walmart → Google Sheets price comparison — Auto-export Walmart prices to a spreadsheet alongside Amazon and Target data for cross-retailer comparison dashboards.
• Walmart → Slack deal alerts — Get notified when Rollback deals appear on products you are tracking.

Data handling, AI, and retention

The Actor processes public Walmart.com product pages and the search terms or public product URLs you submit. It does not accept Walmart credentials, call an AI model, or send input or output to an AI provider. The MCP integration only lets a user-selected AI assistant call this deterministic scraper.

Requests may use Apify US residential proxies and managed Unblocker when Walmart blocks the direct route. Unblocker processes the public Walmart URL, including the submitted search term, to return page content. It does not receive Walmart credentials, customer cookies, or the full Actor input. Results are written only to the run's default Apify dataset; the Actor creates no external cache or account. Inputs, datasets, key-value records, and logs follow your Apify account's retention settings, and you can delete them in Apify Console. Logs contain product URLs, search terms, and operational status, so avoid submitting private or sensitive values as search terms.

Failed operations send sanitized diagnostic input, exceptions, and Actor/build/run IDs to our private GlitchTip service for repair. Secret fields and URL query strings are removed; diagnostic reports are retained for 30 days.

For help with a run, open an issue from the Actor's Issues tab and include a shareable run URL plus a sanitized input.

Tips and best practices

• Use price_low sort — For deal hunting, sort by price_low to find the cheapest options first.
• Check onSale flag — Products with onSale: true have both current and original prices for easy comparison.
• Monitor deal badges — The flag field contains valuable signals like "Rollback", "Best seller", and "100+ bought since yesterday".
• Seller comparison — Use the seller field to identify Walmart.com direct listings vs. third-party marketplace sellers.
• Schedule for price and stock tracking — Run daily with the same keywords, or use productUrls when you already know the exact products to monitor. Alert only when inStock is true or false; preserve null as unknown.
• Multiple keywords — Add several search queries in one run to compare products across categories.

Limitations

• Walmart uses aggressive bot detection. Bounded attempts escalate from direct HTTP to a fresh US residential identity, then to managed US Unblocker requests. Exhausted challenges fail explicitly; recovery is not guaranteed.
• Returns ~40 products per page, up to 25 pages. Walmart often ends a keyword sooner: "tv" stopped at about 11 pages, so the real total depends on the search.
• Brand field may be empty on search rows — Walmart's search results don't always include brand data. Rows from productUrls carry it.
• Results and delivery dates reflect Walmart's default location. There is no ZIP code or store input.
• Availability is location- and time-sensitive. availabilityStatus and inStock are null when Walmart omits an explicit signal; the Actor never guesses stock from price or page presence.
• Only supports Walmart.com (US). Does not support international Walmart sites.
• The productUrls workflow fetches public product details for known Walmart.com US items. It does not extract review text or seller profiles; for review text use Walmart Reviews Scraper.

FAQ

The scraper returns 0 results for my keyword. What's wrong? Walmart's bot detection may occasionally block a request. Try increasing maxRequestRetries to 7-10. Also verify the keyword returns results on walmart.com directly — very niche or misspelled terms may return empty pages.

Can I filter results by seller (Walmart.com vs third-party)? There is no input filter for seller, but the output includes a seller field. Filter results in your pipeline by checking seller === "Walmart.com" to isolate first-party listings.

Can I monitor a specific Walmart product without searching for it? Yes. Add its Walmart.com US URL or item ID to productUrls. The Actor normalizes duplicate URLs, fetches current product details, and preserves the normalized product URL and Walmart item ID in the output.

Can I scrape a whole Walmart category? Yes. Paste the /browse/... page URL into categoryUrls and set maxProductsPerSearch. Walmart serves at most 25 pages per category; split a large category with minPrice and maxPrice to reach more of it.

Why did I get fewer products than I asked for? Read the run's status message: it gives the count against your limit and the reason, such as Walmart having no more results or your maxSearchPages value.

How do you scrape Walmart without getting blocked?

Walmart runs one of the most aggressive bot detection systems of any major retailer. It uses a combination of behavioral fingerprinting, IP reputation scoring, TLS fingerprinting, and CAPTCHA challenges to block automated requests. Standard HTTP scrapers hitting Walmart from datacenter IPs get blocked almost immediately.

Walmart Scraper first tries direct HTTP, then a fresh US residential proxy identity, and uses managed Apify Unblocker when needed. Unblocker handles protection at the provider level and does not use sticky sessions. Routing is automatic; you do not supply proxy credentials. Each request permits one body-bearing managed response, with at most one additional managed attempt after an empty response (as observed for provider 502 errors) or a transport exception. Empty responses/timeouts do not prove zero provider billing; the absolute managed-attempt cap remains two. An identified page without the requested product/price is not repeatedly purchased. Exhaustion stops that query's pagination, preserving earlier rows and later independent queries. Requests have bounded timeouts and zero-output exhaustion fails explicitly.

Additional mitigation techniques built into the scraper:

• Bounded retry logic with configurable maxRequestRetries (default 5, maximum 10); higher limits do not force redundant paid responses or guarantee recovery.

If a keyword exists on Walmart but every route is challenged, the run fails with a clear error instead of claiming successful extraction. Logs report route, attempt, response size and status; additional retries do not guarantee recovery. Very niche keywords that return few results on Walmart.com directly will also return 0 in the scraper.

The isSponsored field in the output lets you filter out paid placements if you want to analyze only organic search results.

How does Walmart pricing work — and how do you track it?

Walmart uses dynamic pricing, meaning product prices can change multiple times per day based on demand, competitor pricing, inventory levels, and time-sensitive promotions. Understanding the price fields in the output:

• price — Current selling price at the time of the scrape
• wasPrice — The "was" price shown in strikethrough on the product listing (Walmart's reference price for calculating savings)
• savings — The savings text displayed on the listing (e.g., "SAVE $5.60")
• onSale — Boolean flag indicating the product is discounted
• flag — Deal badge from Walmart's merchandising system: "Rollback" (sustained price reduction), "Clearance" (markdown to clear inventory), "Best seller", or "100+ bought since yesterday" (social proof)

For price tracking over time, the standard approach is:

1. Run Walmart Scraper daily with your target keywords
2. Store each run's results with the scrapedAt timestamp
3. For each usItemId, compare price across dates to build a price history
4. Alert when price drops below a threshold or when onSale changes from false to true

At $0.004 per product, tracking 200 products daily costs $0.80/day ($24/month) — significantly cheaper than most commercial price intelligence tools.

Legality — is it legal to scrape Walmart product data?

Scraping publicly accessible product data from Walmart.com — prices, ratings, and other information visible to any shopper without logging in — is generally legal based on established case law.

The key precedent is the US Ninth Circuit's ruling in hiQ Labs v. LinkedIn (2022), which held that automated access to publicly available data does not violate the Computer Fraud and Abuse Act (CFAA). Walmart product pages are publicly accessible and indexed by Google.

Walmart Scraper:

• Does not require authentication or bypass any login
• Does not access private account data, order history, or restricted pages
• Does not download or reproduce copyrighted content beyond facts (prices, ratings, product names)
• Uses publicly visible search results that any shopper can see

Caveats:

• Walmart's Terms of Use prohibit scraping. For personal research or small-scale use, enforcement is rare. Large-scale commercial operations (reselling price data to third parties, etc.) carry more risk.
• Do not use scraped data in ways that misrepresent Walmart's content or compete with their advertising products.
• For enterprise or legally sensitive use cases, consult legal counsel about the specific application.

Price monitoring for competitive intelligence, dropshipping research, and market analysis are all widely practiced uses that fall within the gray area of acceptable behavior.

How do you find the best deals on Walmart using a scraper?

Walmart's deal detection goes beyond just checking onSale: true. The scraper gives you several signals to identify genuinely compelling deals:

Rollback deals (most valuable): The flag field contains "Rollback" for products where Walmart has committed to a sustained price reduction. These aren't flash sales — Walmart holds Rollback prices for weeks. Filter for flag.includes("Rollback") and onSale: true.

High savings percentage: Sort by discountPercent to find the deepest discounts. A $50 savings on a $200 item (25% off) is more significant than $50 off a $500 item (10% off).

Clearance items: flag containing "Clearance" signals markdown-to-clear items. These often have the deepest discounts but may have limited inventory in specific variants.

Social proof indicators: flag values like "100+ bought since yesterday" or "Best seller" indicate current demand. Combining high demand with a discount (onSale: true + social proof flag) identifies hot deals.

Price vs. competitors: Use the sort: "price_low" option to find the cheapest products for a category. Cross-reference with Amazon Scraper or Target Scraper data to identify items where Walmart has the best price across retailers.

A practical deal-hunting workflow: run the scraper on category keywords (e.g., "wireless earbuds", "air fryer", "coffee maker") sorted by price_low, filter for onSale: true and rating >= 4, then rank remaining products by savings percentage. This surfaces high-quality products at meaningful discounts without manually browsing hundreds of listings.

How do you compare Walmart prices against Amazon and other retailers?

Price comparison across retailers is one of the highest-value applications of retail scrapers. A multi-retailer setup:

Building the comparison pipeline:

1. Run Walmart Scraper, Amazon Scraper, and Target Scraper with the same product keywords
2. Match products across retailers using product name similarity or UPC/ASIN mapping
3. Store all prices in a shared database or spreadsheet with the retailer as a column

Matching challenges: Product names aren't identical across retailers — a product may be "JLab Go Air Pop Earbuds" on Walmart and "JLab Go Air POP True Wireless Earbuds" on Amazon. Fuzzy string matching (Levenshtein distance) or UPC-based matching gives better results than exact string comparison.

What to track in your comparison:

• Price delta: is one retailer consistently cheaper for a product category?
• Sale timing: do Walmart and Amazon discount the same products at the same time, or stagger their promotions?
• Availability differences: is a product out of stock on Amazon but available on Walmart (opportunity for arbitrage)?
• Seller quality: seller field on Walmart lets you distinguish Walmart.com direct from marketplace sellers; third-party Walmart marketplace sellers often have different prices and return policies than walmart.com direct

Automation: Use Apify Schedules to run all three scrapers on the same schedule, then use a Zapier or Make workflow to aggregate the datasets and push to a comparison dashboard in Google Sheets or Airtable.

Related ecommerce scrapers

• Amazon Scraper -- scrape Amazon product data, prices, and reviews
• eBay Scraper -- scrape eBay listings, prices, and seller info
• Etsy Scraper -- scrape Etsy product listings, seller data, and shop reviews
• Craigslist Scraper -- scrape Craigslist listings by keyword and city
• Target Scraper -- scrape Target product data and prices
• Shopify Scraper -- scrape any Shopify store's products and collections

Use with AI agents via x402 (no Apify account)

Agent workflows can run this actor through Apify MCP without an Apify account when the MCP client uses a funded x402 wallet. Use the actor-specific MCP endpoint:

https://mcp.apify.com?tools=automation-lab/walmart-scraper&payment=x402

This keeps existing Apify MCP/API usage unchanged; x402 only changes payment/authentication for clients that support it. Learn more in Apify's x402 integration docs.

Server API: get one Walmart product or search page over HTTP

Walmart Product Scraper is also a Server Actor. Besides normal runs, it answers short HTTP requests directly, without starting a run for each lookup. Copy the server URL from the Actor's Server tab (do not build it from the Actor name) and authenticate with your Apify token. Use normal Actor runs for many products, many keywords or categories, and more than one result page.

curl -sS "$SERVER_URL/product?url=https://www.walmart.com/ip/5113183757" -H "Authorization: Bearer $APIFY_TOKEN"
curl -sS "$SERVER_URL/search?query=coffee+maker&maxProducts=10&sort=price_low" -H "Authorization: Bearer $APIFY_TOKEN"

Method and path	Input	Output and charge
GET /	None	ready: true, the routes and limits; no scraping or charge
GET /product	Query url: a Walmart.com product URL such as https://www.walmart.com/ip/5113183757, or a numeric item ID	{ok,count,results} with the same record as a normal run's productUrls dataset item; one Submitted product URL result event (product-detail); no start fee
GET /search	Query query (search keywords, 1–200 characters) or url (a Walmart.com /browse/... or /search?q=... URL), not both; optional sort (best_match, best_seller, price_low, price_high, rating_high, new; default best_match), minPrice, maxPrice, brands (up to 10, comma-separated), maxProducts 1–40 (default 20), page 1–25 (default 1)	{ok,count,results} with up to 40 products from that one result page, the same records as a normal run's search dataset items; one Product scraped event (product) per returned product; no start fee

An empty search page returns an error and is free. Missing listing prices are filled from product pages, as in a normal run, while time allows. Each request has a 120-second deadline and a 512 KiB response cap, and one server works on at most six requests at once. Nothing is cached. Errors use { "ok": false, "error": { "code": "...", "message": "...", "retryable": false } }: 400 INVALID_URL, INVALID_QUERY, INVALID_SORT, INVALID_PRICE, INVALID_LIMIT or INVALID_INPUT; 402 spending limit; 404 NO_RESULTS, PRODUCT_NOT_FOUND (Walmart has no product with this item ID; do not retry) or unknown route; 405 wrong method; 502 BLOCKED (Walmart blocked or failed the page within 4 attempts), UPSTREAM_ERROR or charging failure; 503 server busy or stopping; 504 TIMEOUT. Failed requests are free. Retry only when retryable is true. The Server tab shows the full OpenAPI description.