Walmart Data Extractor — Products, Prices, Reviews & Sellers

Production-grade scraper that extracts structured product data from Walmart.com: titles, brands, current and list prices, savings, ratings, review counts, stock status, seller name and type (Walmart vs marketplace), pickup/shipping availability, images, variants, breadcrumbs, and specifications. Optionally pulls individual customer reviews. Built on Walmart's __NEXT_DATA__ JSON blob (richer and more reliable than DOM scraping) and runs through Apify Residential proxies to clear Walmart's Akamai + PerimeterX defense.

One actor, four modes — search, category, direct product URLs, or raw Walmart item IDs.

What you get per product

Field	Description
itemId	Walmart numeric item ID (a.k.a. usItemId).
productUrl	Canonical Walmart product page URL.
title	Product title.
brand	Brand name.
model	Manufacturer model number, when available.
category	Leaf category (Laptops, Wireless Headphones, etc.).
breadcrumbs[]	Full category path from root → leaf.
currentPrice	Current selling price (USD).
listPrice	MSRP / strikethrough price, when shown.
savings	listPrice - currentPrice, when both present.
onSale	true if savings > 0.
currency	Currency code (USD).
rating	Average customer rating (0–5).
reviewCount	Total number of customer reviews.
inStock	Boolean parsed from availabilityStatus.
sellerName	Selling entity (Walmart.com or marketplace seller).
sellerType	walmart / marketplace / walmart_or_marketplace.
pickupAvailable	Local store pickup available.
shippingAvailable	Ships from any fulfillment channel.
freeShipping	Free shipping flagged.
imageUrl	Primary image URL.
images[]	Full image gallery.
variants[]	Color / size / configuration variants (when includeVariants).
specifications{}	Manufacturer spec sheet as a {key: value} map (when includeSpecifications).
description	Short product description.
badges[]	Promotional badges (Rollback, Reduced Price, Bestseller, etc.).
scrapedAt	ISO timestamp the record was captured.

When includeReviews = true, the same dataset also receives review records tagged _type: "review":

Field	Description
reviewId	Walmart review identifier.
itemId	Parent product item ID.
rating	Star rating (1–5).
title	Review title.
text	Review body.
author	Reviewer display name.
verifiedPurchaser	Verified buyer flag.
helpfulVotes / unhelpfulVotes	Community vote counts.
photos[]	Review-attached photos.
pros[] / cons[]	Bullet pros/cons (when present).
submittedAt	ISO date of the review.

When to use this actor

• Walmart Marketplace sellers tracking competitor SKUs, Buy Box wins, and MAP violations.
• Retail price-monitoring SaaS building cross-retailer feeds (pair with our Amazon, eBay, and Google Shopping actors).
• Dropshipping / arbitrage agents comparing Walmart prices against Amazon/Walmart pricing in real time.
• Brand teams monitoring review sentiment and rating drift on their SKUs.
• AI shopping agents that need current Walmart prices/stock as a tool call (apify--walmart-data-extractor via Apify MCP).

When NOT to use

• Walmart Canada / Mexico — this actor targets walmart.com only. Walmart.ca and walmart.com.mx have different DOM/JSON shapes.
• Bulk catalogs > 500 products per run — split into multiple runs. Walmart's anti-bot pool degrades with sustained heavy concurrency.
• Walmart Grocery delivery — grocery uses a separate API surface; out of scope here.

Modes

mode: search

Run a keyword search.

{ "mode": "search", "searchQuery": "samsung 65 inch tv", "maxProducts": 50 }

mode: category

Crawl a Walmart category/listing URL.

{ "mode": "category", "categoryUrls": ["https://www.walmart.com/shop/electronics/laptops"] }

mode: productUrls

Direct product detail pages.

{ "mode": "productUrls", "productUrls": [
  "https://www.walmart.com/ip/Apple-AirPods-Pro/588402301",
  "https://www.walmart.com/ip/123456789"
] }

mode: itemIds

Bulk catalog enrichment from a list of Walmart item IDs.

{ "mode": "itemIds", "itemIds": ["588402301", "210384701"] }

Pricing — Pay Per Event

This actor uses Apify's pay-per-event billing — you only pay for results you actually receive, plus a tiny start fee.

Event	Price
apify-actor-start	$0.00005 (one-time per run)
product-extracted	$0.003 per product
review-extracted	$0.002 per review (only when includeReviews = true)

Typical costs:

• 50 products: ~$0.15
• 50 products + 10 reviews each: ~$1.15
• 500 products: ~$1.50

Pay-per-usage (compute + proxy) is also enabled for heavy power-user jobs — buyers self-select at run time.

Usage examples

Via Apify console

1. Pick a mode and supply the matching field (searchQuery, categoryUrls, productUrls, or itemIds).
2. Optionally set includeReviews: true and maxReviewsPerProduct.
3. Run.

Via API (Node.js)

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('khadinakbar/walmart-data-extractor').call({
    mode: 'search',
    searchQuery: 'wireless headphones',
    maxProducts: 50,
    includeReviews: false,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Via API (Python)

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('khadinakbar/walmart-data-extractor').call(run_input={
    'mode': 'productUrls',
    'productUrls': ['https://www.walmart.com/ip/588402301'],
    'includeReviews': True,
    'maxReviewsPerProduct': 20,
})
items = list(client.dataset(run['defaultDatasetId']).iterate_items())
print(items)

Via Apify MCP (Claude / GPT / Gemini agents)

Tool name: apify--walmart-data-extractor. The actor's input schema is wired for AI-agent consumption — every property has a 4-sentence description with a literal example and disambiguator.

How it works

• PlaywrightCrawler (Chromium) with realistic Chrome 120+ fingerprint pool (Windows + macOS desktop, en-US locale).
• Apify Residential proxy pinned to US — non-US IPs see different (or missing) Walmart inventory due to geo-locking.
• Session pool with cookie persistence — PerimeterX scores per-session, so we keep sessions warm. Sessions are retired on 403/429/503 or block-page detection.
• Resource blocking — images, fonts, stylesheets, and media are aborted in preNavigationHooks for ~3x faster page loads (we don't need them, the data lives in __NEXT_DATA__).
• Multi-path defensive extraction — parsers.js walks several known Next.js layouts so a single Walmart schema change rarely breaks the extractor.
• Silent-failure guard — runs that complete with 0 products and >0 errors fail with an actionable status message rather than charging the start fee on an empty dataset.

Known limits

• Walmart caps search at 25 pages (~1,000 results). Use category URLs or split keyword variants for larger catalogs.
• Reviews shape may vary for some product types (auto, grocery, books). The extractor falls back gracefully — partial review records over no review records.
• Akamai + PerimeterX rate-limits the residential pool under heavy concurrent load. If a run produces 0 items, retry in 10–15 minutes or lower maxProducts.
• Geo-locking — Walmart shows different prices/availability per ZIP. The default US residential proxy yields the "default" US view; ZIP-aware pricing is on the roadmap for v0.2.

Legal

This actor scrapes publicly available product information from walmart.com. By using it, you assume responsibility for your compliance with Walmart's Terms of Use and applicable scraping/data laws in your jurisdiction. The actor does not require any Walmart account login and does not extract account-only or personal data. Use at your own risk.

Related actors in the Khadin Akbar portfolio

• Amazon Product Intelligence
• Amazon Reviews Scraper
• Amazon Competitor Price Tracker
• eBay All-in-One Scraper
• Etsy All-in-One Scraper
• Shopify All-in-One Scraper
• Google Shopping Scraper