Walmart Review Scraper: Collect Product Reviews from Walmart

Walmart Review Scraper pulls customer reviews from walmart.com product pages. Give it a product URL or item ID and it returns review data you can analyze, export, or feed into other pipelines. It pages through results automatically, so you get everything available, not just the first screen.

What data does this actor extract?

Each review record includes:

• Review text and headline
• Star rating (1 to 5)
• Reviewer display name and submission date
• Verified purchase status
• Helpful vote count
• Product name, item ID, and overall average rating
• Total review count for the product

Use cases

• Brand monitoring: track what buyers say about your products or competitors on Walmart without checking pages manually
• Sentiment analysis: feed review text into NLP pipelines to measure satisfaction trends over time
• Competitor research: collect reviews for rival products to find gaps your own product can fill
• Dataset building: create training data for e-commerce models using real customer language from Walmart
• Rating analysis: compare star distributions across product variants to see which ones buyers actually prefer

Input

Parameter	Type	Default	Description
productUrl	string	—	Walmart product URL or numeric item ID
productUrls	array	—	List of Walmart product URLs or item IDs
starRating	string	all	Filter to a specific star rating
sort	string	relevancy	Order in which reviews are returned
maxItems	integer	100	Max reviews to collect per product (up to 1000)
requestTimeoutSecs	integer	30	Per-request timeout in seconds

Example input

{
    "productUrl": "https://www.walmart.com/ip/Apple-AirPods-with-Charging-Case-2nd-Generation/604342441",
    "starRating": "5",
    "sort": "submission_desc",
    "maxItems": 200
}

Star rating filter

Value	Meaning
all	All star ratings (default)
5	5-star reviews only
4	4-star reviews only
3	3-star reviews only
2	2-star reviews only
1	1-star reviews only

Sort options

Value	Meaning
relevancy	Most relevant (default)
submission_desc	Newest reviews first
submission_asc	Oldest reviews first
helpfulness	Most helpful first
rating_desc	Highest rated first
rating_asc	Lowest rated first

Output

Results are stored in the Apify dataset. Each entry looks like this:

{
    "reviewId": "89f24a1c-1234-5678-abcd-ef0123456789",
    "reviewTitle": "Great product, fast delivery",
    "reviewText": "I ordered this last week and it arrived two days early. Works exactly as described and the sound quality is solid.",
    "rating": 5,
    "reviewerName": "JohnDoe123",
    "reviewDate": "2024-11-15T00:00:00.000Z",
    "helpfulCount": 12,
    "isVerifiedPurchase": true,
    "productId": "604342441",
    "productName": "Apple AirPods with Charging Case (2nd Generation)",
    "productUrl": "https://www.walmart.com/reviews/product/604342441",
    "overallRating": 4.5,
    "totalReviewCount": 1247,
    "scrapedAt": "2024-12-01T09:32:11.423Z",
    "error": null
}

Field	Type	Description
reviewId	string	Unique review identifier
reviewTitle	string	Review headline
reviewText	string	Full review body
rating	number	Star rating (1 to 5)
reviewerName	string	Display name of the reviewer
reviewDate	string	Date review was submitted
helpfulCount	integer	Number of helpful votes
isVerifiedPurchase	boolean	True if reviewer made a verified purchase
productId	string	Walmart numeric item ID
productName	string	Product display name
productUrl	string	URL to the Walmart review page
overallRating	number	Product average star rating
totalReviewCount	integer	Total reviews on the product
scrapedAt	string	ISO 8601 timestamp of when the record was collected
error	string	Error message if extraction failed, null otherwise

How it works

1. Parse the Walmart item ID from the URL you provide (or use the numeric ID directly)
2. Fetch product review pages through built-in bypass infrastructure
3. Extract review data from the embedded page JSON
4. Paginate until your review limit is reached or all reviews are collected
5. Push each review as a structured record to the Apify dataset

Integrations

Connect Walmart Review Scraper with other apps using Apify integrations. Export results to Google Sheets, trigger workflows in Make or Zapier, or push data to Slack. You can also use webhooks to kick off downstream processes as soon as scraping finishes.

FAQ

What Walmart URLs does this accept? Any walmart.com product URL works, including /ip/ product pages and /reviews/product/ review pages. You can also pass a bare numeric item ID.

How many reviews can I collect per run? Up to 1000 reviews per run. Set maxItems to control the exact count.

What does "verified purchase" mean? Walmart marks reviews from shoppers who bought the product through walmart.com. The isVerifiedPurchase field reflects that badge.

Can I get the newest reviews first? Yes. Set sort to submission_desc and the actor returns the most recent reviews first. Combine it with starRating to get, say, the newest 1-star reviews.

What if a product has no reviews? The actor finishes cleanly and returns an empty dataset. The run log will note that no reviews were found on the first page.