Walmart Reviews Scraper

Walmart Reviews Scraper

Walmart Reviews Scraper is a fast, reliable Apify actor that helps you scrape Walmart product reviews at scale. It solves the pain of manual copy-paste by turning public review pages into clean, structured records you can analyze and export. Built for marketers, developers, data analysts, and researchers, this Walmart product review scraper lets you extract and sort customer feedback for sentiment analysis, product research, and automation via a Walmart reviews API workflow—so you can extract Walmart product reviews efficiently and turn them into insights.

What data / output can you get?

Below are the exact JSON fields this Walmart reviews scraping tool outputs to the Apify Dataset. Each record is pushed as it’s discovered for streaming-friendly pipelines and quick exports (e.g., download Walmart reviews CSV).

Data type	Description	Example value
itemType	Record type identifier	"Review"
productUrl	Source Walmart product page URL	"https://www.walmart.com/ip/Free-Assembly-Men-s-Everyday-Cotton-Tee.../888475689"
rating	Numeric star rating (1–5)	5
title	Review title (may be null)	"Solid shirt"
text	Full review text	"Good shirt, I bought it to run to the store or around town..."

Note: This actor focuses on core review content (rating, title, text) tied to each productUrl. Titles can be null if not present on the page. Results are available in the Apify Dataset for export (e.g., JSON and CSV) or via API.

Key features

• 🚀 Accurate review extraction Extracts core review fields (rating, title, text) from public Walmart product review pages and saves them alongside the productUrl for clean analysis.

• 🔎 Search-to-product discovery Start from Walmart search URLs or plain keywords—the scraper converts them into product URLs and crawls reviews, respecting your maxProductsPerStartUrl limit. Ideal for Walmart reviews crawler workflows.

• 🧭 Review sorting control Choose your preferred sorting via sortOrder: relevancy, submission-desc, helpful, rating-desc, or rating-asc. Great for Walmart ratings and reviews scraper use cases.

• 📄 Automatic pagination with limits The scraper paginates through review pages and stops when it reaches your maxComments per product, making large jobs predictable and efficient.

• 🛡️ Built-in proxy & block handling Includes robust request logic with proxy support and fallbacks to reduce blocks and improve uptime on Walmart. Reliable alternative to brittle Walmart review scraping Python scripts.

• 💻 Developer-friendly and automation ready Python-based actor with structured outputs in the Apify Dataset. Integrate via the Apify API to build a Walmart reviews API pipeline and download Walmart reviews CSV for dashboards or BI.

• 🔓 No login required Works on public Walmart product pages—no cookies, sessions, or accounts needed.

How to use Walmart Reviews Scraper - step by step

1. Create or log in to your Apify account.
2. Open the “Walmart Reviews Scraper” actor in the Apify Store.
3. Add input data in startUrls:
   • Paste Walmart product URLs, search URLs (e.g., https://www.walmart.com/search?q=tshirt), or plain keywords (e.g., tshirt). Bulk input is supported.
4. Configure key settings:
   • sortOrder to control review order.
   • maxComments to limit reviews per product.
   • maxProductsPerStartUrl to cap products discovered from search URLs.
   • skipProductsWithoutReviews to skip empty listings.
   • proxyConfiguration if you need to adjust proxy behavior.
5. Start the run:
   • The Walmart reviews crawler will process search terms/URLs, collect product pages, and extract reviews based on your limits.
6. Monitor progress in logs and the Dataset:
   • Records are pushed as they’re found for near real-time access.
7. Export results:
   • Download from the Apify Dataset or access programmatically via API (e.g., JSON or CSV) to feed analytics, dashboards, or data pipelines.

Pro tip: For recurring monitoring or product benchmarking, schedule runs and fetch results through the API to keep your Walmart reviews dataset fresh automatically.

Use cases

Use case name	Description
Market research & benchmarking	Aggregate customer feedback to compare products and categories, using the Walmart product review scraper to quantify themes and star ratings.
SEO & content insights	Extract Walmart product reviews to surface phrases and pain points that inform on-page copy and FAQs.
Product management & QA	Track post-launch feedback trends to prioritize fixes and improvements based on real customer inputs.
Data science & sentiment analysis	Build a labeled Walmart reviews dataset for NLP workflows, modeling sentiment shifts over time.
Competitive analysis	Monitor competing SKUs and categories with a repeatable Walmart reviews crawler workflow.
Developer pipelines & APIs	Use the Apify API to integrate this Walmart reviews scraping tool with internal ETL, warehouses, or apps that need structured review data.

Why choose Walmart Reviews Scraper?

This Walmart product ratings scraper focuses on precision, automation, and production reliability for teams that need consistent, structured review data.

• 🎯 Precision on core fields: Extracts rating, title, text, and productUrl cleanly—no noisy extras.
• 🧩 Flexible inputs: Start from product URLs, search URLs, or keywords to capture relevant SKUs quickly.
• 🗂️ Sort and limit controls: Use sortOrder, maxComments, and maxProductsPerStartUrl for predictable jobs.
• 🔁 Resilient operations: Built-in proxy support and fallback logic reduce blocks vs. fragile browser extensions.
• 💻 Developer access: Results stream to the Apify Dataset for easy API consumption—perfect for automation.
• 🔒 Public-only data: Targets public Walmart product pages; no login or private data access.
• 📈 Scales with you: From quick one-offs to repeatable pipelines for large product sets.

In short, it’s a production-ready Walmart reviews scraping tool—without the instability of ad hoc scripts or browser add-ons.

Is it legal / ethical to use Walmart Reviews Scraper?

Yes—when done responsibly. This Walmart review extractor targets publicly available product review pages and does not require login.

Guidelines for compliant use:

• Only access public, non-authenticated pages.
• Review and respect Walmart’s Terms of Service.
• Comply with applicable data regulations (e.g., GDPR, CCPA).
• Avoid scraping private or restricted content.
• Consult your legal team for edge cases and specific jurisdictions.

Input parameters & output format

Example JSON input

{
  "proxyConfiguration": {
    "useApifyProxy": false
  },
  "skipProductsWithoutReviews": true,
  "startUrls": [
    "https://walmart.com/search?q=tshirt"
  ],
  "sortOrder": "relevancy",
  "maxComments": 10,
  "maxProductsPerStartUrl": 20
}

Parameters (from the actor input schema):

• startUrls (array, required)
  • Description: List of Walmart product URLs (e.g., https://www.walmart.com/ip/product-name/123456), search URLs (e.g., https://walmart.com/search?q=tshirt), or keywords (e.g., tshirt). Supports bulk input.
  • Default: none
• sortOrder (string, optional)
  • Description: How to sort the reviews. Options: relevancy (most relevant), submission-desc (newest first), helpful (most helpful), rating-desc (highest rating first), rating-asc (lowest rating first).
  • Default: "relevancy"
• maxComments (integer, optional)
  • Description: Maximum number of reviews to extract per product. Set to 0 for unlimited (not recommended).
  • Default: 10
• maxProductsPerStartUrl (integer, optional)
  • Description: Maximum number of products to process from each start URL (for search URLs). Set to 0 for unlimited.
  • Default: 20
• skipProductsWithoutReviews (boolean, optional)
  • Description: If enabled, products with no reviews will be skipped to speed up processing.
  • Default: true
• proxyConfiguration (object, optional)
  • Description: Proxy settings. By default, starts with no proxy. If Walmart blocks requests, automatically falls back to datacenter proxy, then residential proxy with retries.
  • Default: {"useApifyProxy": false}

Example JSON output

[
  {
    "itemType": "Review",
    "productUrl": "https://walmart.com/ip/Free-Assembly-Men-s-Everyday-Cotton-Tee-with-Short-Sleeves-Sizes-S-3XL/888475689?classType=VARIANT&from=/search",
    "rating": 5,
    "title": "Solid shirt",
    "text": "Good shirt, I bought it to run to the store or around town. Neckline is good."
  },
  {
    "itemType": "Review",
    "productUrl": "https://walmart.com/ip/Free-Assembly-Men-s-Everyday-Cotton-Tee-with-Short-Sleeves-Sizes-S-3XL/888475689?classType=VARIANT&from=/search",
    "rating": 4,
    "title": "Good basic tee",
    "text": "Nice basic tee for the price. Bought to wear under sweaters and jackets..."
  }
]

Notes:

• title may be null if the reviewer didn’t provide one.
• Each record is pushed to the Apify Dataset during the run for easy streaming, export, or API access.

FAQ

Can I start from keywords instead of URLs?

Yes. Add plain keywords (e.g., "tshirt") to startUrls and the actor will convert them into Walmart search URLs, discover products, and extract reviews from those pages.

Does it support Walmart.ca?

This version targets Walmart.com product pages. Provide Walmart.com product URLs, search URLs, or keywords for the best results.

Can I filter reviews by star rating or verified purchase?

Filtering by rating or verified purchase is not supported. However, you can control sorting with sortOrder (relevancy, submission-desc, helpful, rating-desc, rating-asc) to prioritize the type of reviews you need.

How many reviews can I scrape per product?

Use maxComments to set the per-product limit (default 10). The scraper paginates review pages until the limit is reached.

Can I scrape multiple products from a search results page?

Yes. Provide a Walmart search URL or keyword and use maxProductsPerStartUrl to cap how many products are processed from that search.

Is there an API to access the results?

Yes. Every run writes to the Apify Dataset, which you can access via the Apify API. This enables a Walmart reviews API workflow and lets you download Walmart reviews CSV or JSON for downstream use.

Do I need to log in or use cookies?

No. The Walmart review extractor works on public product pages—no login or cookies required.

Is this built with Python? Can I integrate it into my pipeline?

Yes. The actor is implemented in Python and designed for automation. You can trigger runs and retrieve results programmatically, making it a solid choice for Walmart review scraping Python pipelines.

Closing CTA / Final thoughts

Walmart Reviews Scraper is built to turn public Walmart product feedback into structured, analysis-ready data. With flexible inputs (keywords, search URLs, product URLs), smart sorting and limits, and reliable block handling, it helps marketers, developers, analysts, and researchers extract Walmart product reviews at scale. Access results via the Apify Dataset and API to automate reporting, download Walmart reviews CSV, or feed your analytics stack. Start extracting smarter insights from Walmart today.