Walmart Reviews Scraper

Walmart Reviews Scraper

Walmart Reviews Scraper is a production-ready Apify actor that collects customer reviews from Walmart.com into clean, structured JSON for analysis and automation. It eliminates manual copy-paste and brittle scripts by discovering products from search URLs or keywords, paginating review pages reliably with residential proxies, and streaming results directly to your dataset. Built for marketers, developers, data analysts, and researchers, this Walmart reviews scraper enables large-scale sentiment analysis, QA workflows, and e‑commerce research with predictable performance.

What data / output can you get?

This scraper saves a concise, analysis-ready schema to the Apify dataset. Below are the exact fields pushed per review with examples.

Data type	Description	Example value
itemType	Static label to identify the record type	“Review”
productUrl	URL of the reviewed Walmart product	https://walmart.com/ip/Free-Assembly-Men-s-Everyday-Cotton-Tee-with-Short-Sleeves-Sizes-S-3XL/888475689?classType=VARIANT&from=/search
rating	Star rating given by the reviewer (number)	5
title	Review headline/title if present (nullable)	“Solid shirt”
text	Full review text	“Good shirt, I bought it to run to the store or around town. Neckline is good.”

Notes:

• The scraper focuses on high-signal review fields for reliability: rating, title, text, and the product URL.
• Results are stored in the Apify dataset and can be downloaded as JSON, CSV, or Excel for BI tools and pipelines.

Key features

• 🔒 Robust proxy & block handling
  Always uses Apify Residential proxy for Walmart with smart fallback and retries, plus block-page detection and rate-limit handling for reliable scraping.

• 🔍 Search URL & keyword support
  Paste a Walmart search URL or just a keyword (e.g., “tshirt”). The scraper converts it to a Walmart search URL and discovers product pages automatically.

• 🔄 Automatic pagination
  Navigates Walmart search results (page parameter) and review pages until your limits are reached, making this a dependable Walmart reviews crawler.

• 🧭 Review sorting control
  Choose how reviews are ordered with sortOrder: relevancy, submission-desc, helpful, rating-desc, or rating-asc.

• 🎚️ Configurable limits
  Control scope via maxComments (per product) and maxProductsPerStartUrl (per search URL) for efficient runs and predictable costs.

• 📡 Live dataset streaming
  Reviews are pushed to the dataset as they are discovered, enabling near real-time consumption via the Apify API.

• 🛠️ Developer-friendly & API-ready
  Built in Python and deployed on Apify. Access every run programmatically to integrate this Walmart review extractor into your data pipelines.

• 📤 Easy exports
  Export Walmart reviews to CSV, JSON, or Excel from the dataset UI or via the Apify API for downstream analytics.

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 on Apify.
3. Add input in startUrls:
   • Product URLs (e.g., https://www.walmart.com/ip/…/123456)
   • Search URLs (e.g., https://www.walmart.com/search?q=tshirt)
   • Keywords (e.g., tshirt)
4. Configure options (optional):
   • sortOrder: relevancy | submission-desc | helpful | rating-desc | rating-asc
   • maxComments: maximum reviews per product (default 10)
   • maxProductsPerStartUrl: limit products discovered per search URL (default 20)
   • skipProductsWithoutReviews: skip products with no reviews (default true)
   • proxyConfiguration: proxy settings (Apify editor-supported)
5. Start the run. The actor will normalize inputs (keywords → search URLs), discover product pages (for search/keywords), fetch review pages, and handle pagination.
6. Monitor progress in logs; reviews are pushed continuously to the dataset with itemType, productUrl, rating, title, and text.
7. Download results from the run’s dataset in JSON, CSV, or Excel, or access them programmatically via the Apify API.

Pro tip: Seed the actor with multiple search URLs or keywords to build a larger Walmart review dataset quickly using this Walmart reviews scraping tool.

Use cases

Use case name	Description
Market research & benchmarking	Aggregate ratings and verbatim feedback to compare products and detect shifts in customer sentiment over time.
SEO & content insights	Mine review text for real customer language to inform keyword targets and messaging. Export data to CSV for easy analysis.
Product improvement feedback loop	Pull consistent, structured review data to prioritize fixes and enhancements based on volume and rating trends.
Competitive intelligence	Track competing products’ ratings and review narratives to identify strengths, weaknesses, and positioning gaps.
Data science & NLP	Build labeled corpora of rating + text for sentiment models or topic extraction at scale.
Dashboarding & BI	Pipe dataset outputs into BI tools for continuous monitoring and alerting via the Apify API.
Automation & ETL	Use the Apify API to integrate this Walmart review data scraper into ETL pipelines and analytics stacks.

Why choose Walmart Reviews Scraper?

This Walmart ratings and reviews scraper prioritizes reliability, structure, and developer access.

• ✅ Accurate, structured output (rating, title, text, productUrl) for clean analytics
• 🔁 Built-in residential proxy and retry logic for resilient runs at scale
• 📈 Scales from a few products to large keyword-driven collections with pagination controls
• 🧰 Python-based and API-accessible for developers integrating with automation stacks
• 🛡️ Safe: focuses on publicly available product review pages
• 💸 Efficient: fine-tune per-product and per-start URL limits to control spend
• 🧩 More reliable than browser extensions or unstable one-off scripts, ideal for ongoing workflows

Bottom line: a production-ready Walmart reviews scraper without API dependencies on Walmart that’s built for automation and repeatability.

Is it legal / ethical to use Walmart Reviews Scraper?

Yes—when used responsibly. This actor targets publicly available product review pages and does not access private or authenticated content.

Guidelines for compliant use:

• Scrape only public, non-login-protected pages
• Review and honor Walmart’s Terms of Service
• Comply with data protection laws (e.g., GDPR, CCPA)
• Avoid collecting or using personal data in ways that violate applicable policies or laws
• Consult your legal team for edge cases or jurisdiction-specific requirements

This tool is not affiliated with Walmart. You are responsible for ensuring compliance.

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

Field	Type	Required	Default	Description
startUrls	array	Yes	—	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.
sortOrder	string	No	relevancy	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).
maxComments	integer	No	10	Maximum number of reviews to extract per product. Set to 0 for unlimited (not recommended).
maxProductsPerStartUrl	integer	No	20	Maximum number of products to process from each start URL (for search URLs). Set to 0 for unlimited.
skipProductsWithoutReviews	boolean	No	true	If enabled, products with no reviews will be skipped to speed up processing.
proxyConfiguration	object	No	{"useApifyProxy": false}	Proxy settings. By default, starts with no proxy. If Walmart blocks requests, automatically falls back to datacenter proxy, then residential proxy with retries.

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": 5,
    "title": null,
    "text": "these are high quality t-shirts. My husband loves them and they are 100% cotton which My husband needs. these laundry really well with minimal shrinkage. in other words, it does not change the size of the t-shirt."
  },
  {
    "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 bc the women's white tee was sold out. Ended up liking the cut of the men's better."
  }
]

Notes:

• title can be null when the reviewer didn’t provide a headline.
• Fields are pushed individually per review as they’re discovered.

FAQ

Can I scrape both product URLs and search results?

Yes. You can input direct product URLs, Walmart search URLs, or plain keywords in startUrls. The scraper will normalize keywords to search URLs and then discover product pages automatically.

Does this Walmart reviews scraper support sorting by rating or date?

Yes. Use the sortOrder parameter to pick relevancy, submission-desc (newest first), helpful, rating-desc (highest first), or rating-asc (lowest first).

How many Walmart reviews can I scrape per product?

Use maxComments to control how many reviews are collected per product. The default is 10. You can increase it up to 1000 as needed.

Can I export Walmart reviews to CSV?

Yes. All results are stored in the Apify dataset for the run. You can download them as JSON, CSV, or Excel from the dataset UI or via the Apify API.

Does this Walmart review extractor require login or cookies?

No. It targets public product review pages on Walmart.com and does not require login.

Is there an API to access the results?

Yes. Every run’s dataset and logs are accessible via the Apify API, making this a developer-friendly Walmart reviews scraper for Python and automation workflows.

Which Walmart domains are supported?

This actor is designed for Walmart.com. It normalizes inputs to use www.walmart.com and builds review URLs from product IDs on that domain.

Does it scrape reviewer names, dates, or images?

No. The current output focuses on itemType, productUrl, rating, title, and text for reliability and simplicity.

Closing CTA / Final thoughts

Walmart Reviews Scraper is built to turn Walmart.com customer feedback into clean, structured data you can trust. With keyword/search URL support, automatic pagination, robust proxy handling, and a compact JSON schema, it helps marketers, analysts, and developers move from raw reviews to actionable insights quickly. Access results via the Apify API, export Walmart reviews to CSV, and plug them into your dashboards or NLP pipelines. Start scraping smarter and transform Walmart review data into an engine for research, optimization, and growth.