Walmart Reviews Scraper

Extract Walmart product reviews at scale. Scrape full review text, star ratings, verified purchase status, helpful vote counts, reviewer names, review photos, pros, cons, and product-level rating breakdowns for any Walmart product.

Features

• Scrape reviews by product URL or search query
• Extract full review text, title, rating, and date
• Verified purchase identification
• Helpful vote counts
• Review photos extraction
• Pros and cons extraction
• Reviewer name
• Product-level info: name, price, overall rating, total reviews, brand, seller, category
• Rating breakdown (5-star to 1-star percentages)
• Filter by star rating range (e.g., only 1-2 star reviews)
• Sort by most recent, highest, lowest, or most relevant
• Verified-only mode for trustworthy reviews
• Multiple extraction strategies: NEXT_DATA JSON, embedded review JSON, DOM parsing
• Automatic pagination with deduplication
• Anti-bot detection with User-Agent rotation
• Clean, structured JSON output

Input

Field	Type	Default	Description
productUrls	array	[]	Walmart product page URLs to scrape reviews from
searchQuery	string	""	Search Walmart for products, then scrape their reviews
maxReviews	number	500	Max reviews per product (0 = unlimited)
sortBy	string	"relevant"	Sort: "recent", "highest", "lowest", "relevant"
verifiedOnly	boolean	false	Only scrape verified purchase reviews
maxSearchResults	number	5	How many search results to process
minRating	number	1	Minimum star rating filter (1-5)
maxRating	number	5	Maximum star rating filter (1-5)
proxyConfiguration	object	Apify Residential	Proxy settings (residential recommended)

Output — Individual Review

{
  "productName": "Apple AirPods Pro (2nd Generation)",
  "productId": "1752657021",
  "productUrl": "https://www.walmart.com/ip/1752657021",
  "productPrice": "$189.99",
  "brand": "Apple",
  "seller": "Walmart.com",
  "category": "Electronics/Headphones",
  "overallRating": 4.7,
  "totalReviews": 8234,
  "ratingBreakdown": {
    "5": "74%",
    "4": "12%",
    "3": "6%",
    "2": "3%",
    "1": "5%"
  },
  "reviewId": "review-abc123",
  "reviewTitle": "Best earbuds I've ever owned",
  "reviewText": "The noise cancellation on these is incredible. I use them daily on my commute and in the office. Battery life is great and they fit perfectly...",
  "rating": 5,
  "reviewer": "TechBuyer42",
  "date": "2026-02-15",
  "dateRaw": "Feb 15, 2026",
  "verified": true,
  "helpfulCount": 23,
  "photos": [
    "https://i5.walmartimages.com/review-image-1.jpg"
  ],
  "pros": ["Great sound quality", "Comfortable fit"],
  "cons": ["Pricey"],
  "scrapedAt": "2026-03-02T12:00:00.000Z"
}

Use Cases

• Product Research: Understand what customers love and hate before making purchasing decisions
• Competitor Analysis: Monitor competitor product feedback and identify weaknesses
• Sentiment Analysis: Analyze customer sentiment at scale across product categories
• Brand Monitoring: Track reviews for your own products sold on Walmart
• Quality Control: Detect emerging product quality issues from negative review patterns
• Market Research: Identify unmet customer needs and feature gaps in product categories
• Price Monitoring: Combine review data with pricing to understand value perception
• Content Generation: Extract real customer language for marketing copy and product descriptions

Pricing

Pay per review scraped — you only pay for what you extract. See the Pricing tab for details.

$0.004 per review scraped.

Example — Scrape by Product URLs

{
  "productUrls": [
    "https://www.walmart.com/ip/Apple-AirPods-Pro-2nd-Generation/1752657021",
    "https://www.walmart.com/ip/Samsung-Galaxy-Buds2-Pro/394875830"
  ],
  "maxReviews": 200,
  "sortBy": "recent"
}

Example — Search and Scrape Reviews

{
  "searchQuery": "wireless headphones",
  "maxSearchResults": 10,
  "maxReviews": 100,
  "sortBy": "relevant"
}

Example — Negative Reviews Only

{
  "productUrls": ["https://www.walmart.com/ip/1752657021"],
  "maxReviews": 500,
  "minRating": 1,
  "maxRating": 2,
  "sortBy": "recent"
}

Example — Verified 5-Star Reviews

{
  "productUrls": ["https://www.walmart.com/ip/1752657021"],
  "maxReviews": 300,
  "minRating": 5,
  "maxRating": 5,
  "verifiedOnly": true
}

Tips

• Use residential proxies for best success rates — Walmart detects datacenter IPs
• Start small — Test with 50-100 reviews before running large jobs
• Sort by "recent" for the latest reviews, "lowest" to find product issues quickly
• Combine with Walmart Product Scraper — search for products first, then deep-dive into reviews
• Use rating filters to focus on just positive or negative feedback
• Products with 10K+ reviews may take significant time — use maxReviews to limit

Integration — Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("sovereigntaylor/walmart-reviews-scraper").call(run_input={
    "searchTerm": "walmart reviews",
    "maxResults": 50
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item.get('title', item.get('name', 'N/A'))}")

Integration — JavaScript

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('sovereigntaylor/walmart-reviews-scraper').call({
    searchTerm: 'walmart reviews',
    maxResults: 50
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => console.log(item.title || item.name || 'N/A'));