Walmart Reviews Scraper

Collect Walmart.com customer reviews for any product: star rating, title, full text, date, reviewer nickname, verified-purchase flag, helpful votes, photos and the seller's or brand's reply. Give it product URLs, item ids, or just a keyword. It can pick the top products for that keyword and collect reviews for each one.

Filters let you keep only the reviews you care about: specific star ratings such as 1 and 2 stars for complaints, verified buyers only, or only reviews posted since a date. That last one turns a daily schedule into a new-reviews feed.

The actor reads Walmart's mobile-app data feed and fetches 50 reviews per request. It needs no browser, no proxy and no Walmart account.

Who it's for: brands and agencies monitoring product reputation, product teams researching competitors, and anyone building sentiment or AI pipelines on real customer feedback.

What data you get

Field	Example	Notes
review_id	441841979
rating	5	1–5 stars
title	Definitely a great option	often empty on Walmart
text	I love my laptop it came with lots of perks…
date	2026-09-25	ISO date
author	Jennifer	reviewer nickname
verified_purchase	true
recommended	true	when the reviewer answered
helpful_votes, unhelpful_votes	12, 1
photos	["https://i5.walmartimages.com/…"]	photos attached to the review
seller_name, fulfilled_by	Walmart.com, Walmart	who the reviewer bought from
seller_response	Hello Linda, thank you for your feedback…	brand or seller reply, when present
syndication_source	influenster.com	set when the review was syndicated from another site
badges	["VerifiedPurchaser"]
language	English
us_item_id, product_name, product_url		the product reviewed
product_average_rating, product_total_reviews	4.6, 7095	product-level context on every row
scraped_at	2026-09-28T02:41:48Z

Use cases

• Reputation monitoring. Schedule a daily run with sinceDate set to yesterday and ratings: ["1","2"] to get every new negative review for your products.
• Competitor research. Use searchQueries: ["air fryer"] with maxProductsPerQuery: 10 to compare what buyers praise and complain about across the top products in a category.
• Seller and brand response tracking. See which reviews got a reply in seller_response, and how fast.
• Sentiment and AI analysis. Feed dated, rated review text into a sentiment model, topic clustering or an LLM summary.
• Product development. Mine 1- and 2-star reviews for recurring defects and missing features.

Input

Parameter	Description
productUrls / itemIds	Product pages (/ip/... or /reviews/product/...) or Walmart item ids
searchQueries	Optional keywords; the top products with reviews are used
maxProductsPerQuery	Products to take per keyword (default 5)
sort	Newest first (default), oldest first, most relevant, most helpful, highest or lowest rating
ratings	Keep only these star ratings, e.g. ["1", "2"]
verifiedOnly	Keep only verified purchases
sinceDate	YYYY-MM-DD; stop at the first older review (needs newest-first sort)
maxReviewsPerProduct	Cap per product (default 100)
maxItems	Total review rows (default 1000)

Example input

{
    "productUrls": [{ "url": "https://www.walmart.com/ip/5144605607" }],
    "searchQueries": ["coffee maker"],
    "maxProductsPerQuery": 3,
    "sort": "submission-desc",
    "ratings": ["1", "2"],
    "verifiedOnly": true,
    "maxReviewsPerProduct": 200,
    "maxItems": 1000
}

Example output

{
    "review_id": "439905127",
    "rating": 1,
    "title": null,
    "text": "Very slow laptop. Very disappointing.",
    "date": "2026-09-09",
    "author": "E",
    "author_location": null,
    "verified_purchase": true,
    "recommended": null,
    "helpful_votes": 0,
    "unhelpful_votes": 0,
    "photos": [],
    "seller_name": "Best Electronics",
    "fulfilled_by": "Seller",
    "seller_response": null,
    "syndication_source": null,
    "badges": [
        "VerifiedPurchaser"
    ],
    "language": "English",
    "us_item_id": "443153637",
    "product_name": "HP 14 Touchscreen Laptop Intel Processor 4GB RAM 64GB eMMC WiFi 6 Bluetooth Windows 11 Home S 1 Year Office Pale Gold Type C Hub",
    "product_url": "https://www.walmart.com/ip/443153637",
    "product_average_rating": 4.1,
    "product_total_reviews": 20504,
    "scraped_at": "2026-09-28T02:45:10Z"
}

Scheduling and integrations

• New-review alerts. Schedule a daily run with sinceDate and sort: submission-desc, and connect a webhook or Slack integration to post the results.
• Exports. Download results as JSON, CSV or Excel, or read them through the Apify API.
• Integrations. Works with Google Sheets, Make, Zapier, n8n and Airbyte.

Use with AI assistants (MCP)

Add the actor through the Apify MCP server in Claude, Cursor or another MCP client. Ask "Summarize the most common complaints in 1-star Walmart reviews of the Ninja AF140 air fryer", and the assistant runs the actor and reads the reviews.

FAQ

Why do I get fewer reviews than the product's review count? Walmart's review count includes star-only ratings with no text. Only reviews with text can be listed. For a popular laptop that's about 7,000 of 20,500 ratings, and some small products have ratings but no written reviews at all. product_total_reviews still shows the full count.

How far back can I go? Every review with text, back to the oldest one. The actor pages through them 50 at a time.

How do the rating and verified filters affect cost? You only pay for rows that pass the filters. The actor still reads the non-matching reviews, so rare filters on large products take longer.

Do I need a proxy or an account? No. The actor collects public reviews without logging in.

Is this legal? Reviews are public. Reviewer nicknames are included as Walmart shows them. Use the data in line with Walmart's terms and privacy laws that apply to you, such as GDPR and CCPA.

Found a problem? Open an issue on the actor's Issues tab and include the run link.