Walmart Reviews Scraper

Walmart Reviews Scraper

Walmart Reviews Scraper is a purpose-built Walmart review scraper tool that lets you scrape Walmart product reviews at scale and export clean, structured data for analysis. It solves the manual, time‑consuming process of collecting customer feedback by turning Walmart review pages into a consistent dataset for marketers, developers, data analysts, and researchers. With integrated sorting, keyword/search URL support, and robust proxy management, it enables high‑volume extraction workflows and powers everything from sentiment dashboards to a Walmart product reviews API pipeline.

What data / output can you get?

Below are the exact JSON fields this Walmart reviews extractor pushes to the Apify dataset. You can download Walmart product reviews in JSON, CSV, or Excel to feed BI tools, notebooks, or dashboards.

Data type	Description	Example value
itemType	Static label to identify the record type	"Review"
productUrl	Full Walmart product URL associated with the review	https://www.walmart.com/ip/Free-Assembly-Men-s-Everyday-Cotton-Tee-with-Short-Sleeves-Sizes-S-3XL/888475689
rating	Star rating value as an integer	5
title	Review headline text (may be null if not provided)	"Solid shirt"
text	Full review text content	"Good shirt, I bought it to run to the store or around town. Neckline is good."

Notes:

• Title may be null if the reviewer didn’t include a headline.
• Results are stored in an Apify dataset, enabling Walmart reviews data export to JSON, CSV, or Excel for downstream analysis.

Key features

• 🔒 Robust proxy management & anti‑blocking Automatically uses residential proxies with smart rotation and fallback logic to keep your Walmart product review crawler running reliably at scale.

• 🧭 Sorting controls for relevance and quality Choose how to extract Walmart ratings and reviews using the sortOrder parameter: relevancy, submission-desc, helpful, rating-desc, or rating-asc.

• 📄 Automatic pagination The Walmart ratings scraper walks through review pages automatically until your per‑product limit is reached, so you can download Walmart product reviews in bulk.

• 🔍 Multi‑source inputs (products, searches, keywords) Start from Walmart product URLs, search URLs, or plain keywords. Keywords are automatically converted into Walmart search URLs for flexible targeting.

• 📦 Multi‑product collection Control how many products to process per search URL with maxProductsPerStartUrl for efficient batching and dataset growth.

• 🏁 Review caps for predictable runs Limit the number of reviews per product with maxComments for fast prototyping or large‑scale collection.

• 🗂️ Structured, analysis‑ready output Clean JSON rows (itemType, productUrl, rating, title, text) are ideal for a Walmart reviews dataset, dashboards, and ML workflows.

• 💻 Developer‑friendly via Apify Access each run and dataset programmatically through the Apify API to build your own Walmart product reviews API integrations or Walmart reviews scraping Python scripts.

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 (containing /ip/…),
   • Paste Walmart search URLs (e.g., https://www.walmart.com/search?q=tshirt),
   • Or enter plain keywords (e.g., tshirt). Keywords are converted to search URLs automatically.
4. Configure sorting and limits:
   • sortOrder: Choose one of ["relevancy", "submission-desc", "helpful", "rating-desc", "rating-asc"].
   • maxComments: Set how many reviews to collect per product (1–1000).
   • maxProductsPerStartUrl: For search URLs, cap how many products to process (0 for unlimited).
   • skipProductsWithoutReviews: Enable to skip products with no reviews and speed up processing.
5. (Optional) Proxy settings:
   • proxyConfiguration is available; the actor automatically uses residential proxies for reliability.
6. Run the actor:
   • Click Start. The scraper navigates search or product pages, paginates reviews, and streams results into the dataset in real time.
7. Export your data:
   • Open the Run dataset and export to JSON, CSV, or Excel. Use the Apify API for programmatic access.

Pro tip: Automate recurring jobs and push the Walmart reviews dataset into your BI stack or CRM via the Apify API to build a production‑grade Walmart product reviews API workflow.

Use cases

Use case name	Description
Market research & benchmarking	Aggregate and compare ratings and review narratives across categories to quantify strengths and weaknesses vs. competitors.
Product optimization	Analyze recurring feedback to prioritize improvements and validate changes using fresh review batches.
SEO & content strategy	Mine review language to discover keywords, questions, and phrasing for high‑intent content and PDP optimization.
Customer sentiment tracking	Monitor shifts in ratings and comment themes over time to detect issues early and measure impact.
Data science & ML training	Build labeled text corpora of Walmart reviews to train or evaluate NLP models and sentiment classifiers.
Automation & pipelines	Use the Apify API to run jobs on schedules and deliver Walmart reviews data export to warehouses, notebooks, or dashboards.
Academic & social research	Study consumer behavior and product perception in large-scale, publicly available datasets.

Why choose Walmart Reviews Scraper?

This Walmart reviews extractor is built for precision, automation, and production reliability.

• ✅ Accurate, structured output: Clean, consistent fields ready for analysis and integration.
• 🚀 Scalable collection: Handle multiple products per query and paginate automatically.
• 🔐 Anti‑blocking ready: Residential proxies, rotation, and retries for dependable runs.
• 🧰 Sorting controls: Extract Walmart ratings and reviews in the order that best fits your analysis.
• 💻 Developer access: Connect via the Apify API for pipelines, scripts, and apps.
• 💸 Cost‑effective: Start fast, then scale as your Walmart reviews dataset grows.
• 🧩 Integration friendly: Export to JSON/CSV/Excel and wire up to BI tools and workflows.

Compared to browser extensions or one‑off scripts, this production‑ready Walmart product review crawler provides stability, automation, and repeatability for real‑world data operations.

Is it legal / ethical to use Walmart Reviews Scraper?

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

Guidelines to follow:

• Scrape only public, non‑authenticated content.
• Review and comply with Walmart’s Terms of Service.
• Adhere to data protection laws such as GDPR and CCPA.
• Use the data ethically and verify compliance with your legal team for edge cases.

Input parameters & output format

Example input JSON

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

Parameter reference:

• startUrls (array, required): List of Walmart product URLs, search URLs, or keywords. Supports bulk input. Default: none (UI prefill includes ["https://walmart.com/search?q=tshirt"]).
• sortOrder (string, optional): How to sort reviews. One of ["relevancy", "submission-desc", "helpful", "rating-desc", "rating-asc"]. Default: "relevancy".
• maxComments (integer, optional): Maximum reviews to extract per product. Range 1–1000. Set 0 for unlimited (not recommended). Default: 10.
• maxProductsPerStartUrl (integer, optional): Maximum number of products to process from each start URL (for search URLs). Range 0–1000 (0 = unlimited). Default: 20.
• skipProductsWithoutReviews (boolean, optional): If enabled, products with no reviews will be skipped to speed up processing. Default: true.
• proxyConfiguration (object, optional): Proxy settings. Editor type: proxy. UI prefill: {"useApifyProxy": false}.

Example output JSON

[
  {
    "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."
  }
]

Notes:

• Fields are exactly: itemType, productUrl, rating, title, text.
• title can be null when a reviewer omits a headline.
• Access results in the run’s Dataset to export your Walmart reviews data.

FAQ

Can this scrape both Walmart.com and Walmart.ca?

This actor targets Walmart.com. You can provide keywords or search URLs to cover categories and products on the US site.

Is Walmart Reviews Scraper free to use?

You can start on Apify’s free plan for smaller jobs and testing. As your needs grow, upgrade to handle larger Walmart reviews datasets.

Does it require login or cookies?

No. It scrapes publicly available product review pages without login.

Can I filter by rating or verified purchase?

Direct rating or verified‑purchase filters aren’t provided. However, you can choose sortOrder (relevancy, submission-desc, helpful, rating-desc, rating-asc) and then post‑process downloaded data to filter as needed.

How many reviews per product can I collect?

You control this with maxComments (1–1000, default 10). Set it higher to download more Walmart product reviews per item.

Can I start from keywords or search URLs?

Yes. Provide search URLs or plain keywords in startUrls. Keywords are automatically converted to Walmart search URLs, and the scraper will process multiple products using maxProductsPerStartUrl.

Is there an API to access results?

Yes. Every run and its dataset are accessible via the Apify API, making it easy to integrate with Python scripts, workflows, or a custom Walmart product reviews API.

How does it handle blocking?

The scraper uses residential proxies with rotation and fallback logic, plus retries and pacing, to reduce blocks and maintain stability during large‑scale Walmart customer reviews scraping.

Final thoughts

Walmart Reviews Scraper is built to extract Walmart ratings and reviews into clean, analysis‑ready data. With flexible inputs (products, searches, keywords), sorting, automatic pagination, and robust proxying, it helps marketers, developers, analysts, and researchers turn raw feedback into insights fast. Use the Apify API to automate end‑to‑end pipelines, power dashboards, and keep your Walmart reviews dataset fresh—start extracting smarter today.