Walmart Reviews Scraper: Verified, Helpful Votes, Photos

From The Mine Works, makers of Threads Scraper and B2B Leads Finder, with over 140,000 runs across 170+ public actors.

Why choose this actor?

• Hundreds of reviews per product in one run, not the first page. The actor walks Walmart's own review pages, 10 reviews at a time, until it reaches your number or the last review. Our proof run collected 600 reviews from 4 coffee makers in 131 seconds (150 each, newest first, back to July 2026 for the slowest seller). No Walmart account, no API key, no cookies of yours.
• The filters Walmart's page has, on every run. Sort by most recent, most helpful, most relevant, highest or lowest rating, keep only some star levels, and keep only verified purchases. In our filter test every one of 180 rows was a 1 or 2 star review and every one carried the verified purchase flag.
• You pay only for reviews you receive. One charge per review row saved to your dataset, plus a flat start fee per run. Item ids that do not exist, products with no written reviews, reviews Walmart repeats across its pages (12 skipped for one product in the proof run) and reviews an earlier run already gave you (when you switch that on) are never charged.

Part of The Mine Works Marketing, SEO and reviews family: Facebook Ad Library Scraper, Google Ads Transparency Scraper, Similarweb Scraper, Google News Scraper, Trustpilot Reviews Scraper, Google Trends Scraper.

Try it in one minute

Paste this input and press Start. It returns the 20 newest one star reviews of a Keurig coffee maker in a few seconds:

{
  "products": ["https://www.walmart.com/ip/12516374178"],
  "maxReviewsPerProduct": 20,
  "sort": "most_recent",
  "stars": ["1"]
}

You can name a product in three ways, and mix them in one list:

• Product link: https://www.walmart.com/ip/12516374178 or the long form with the product name, https://www.walmart.com/ip/KEE-BLACK-GEN-2/12516374178, with or without extra parameters.
• Reviews link: https://www.walmart.com/reviews/product/12516374178, the page behind "See all reviews".
• Item id: 12516374178, the number at the end of the product link.

On Apify's free plan every run returns the first 10 results as a preview, so you can check the data and the fields before you pay. A paid Apify plan returns every result: https://apify.com/pricing?fpr=ymnoit

Copy to your AI assistant

themineworks/walmart-reviews-scraper on Apify. Returns Walmart.com product reviews, one row per review with stars, title, text, reviewer nickname, date, verified purchase flag, helpful and unhelpful votes, photos, videos, syndication source and the brand's reply, plus the product title, price, category, average rating and review counts on every row. Call ApifyClient("TOKEN").actor("themineworks/walmart-reviews-scraper").call(run_input={"products": ["https://www.walmart.com/ip/12516374178"], "maxReviewsPerProduct": 200, "sort": "most_recent"}), then client.dataset(run["defaultDatasetId"]).list_items().items. Required: products (Walmart.com product links, reviews links or item ids). Optional: maxReviewsPerProduct (default 100, 20 to 10,000), sort (most_recent, most_helpful, most_relevant, highest_rating or lowest_rating; default most_recent), stars (list of "1" to "5"; default all), verifiedPurchaseOnly (default false), onlyNewReviews (default false). Skip rows that have "_type": "info". Full spec: GET https://api.apify.com/v2/acts/themineworks~walmart-reviews-scraper/builds/default (Bearer TOKEN), which returns inputSchema and readme. Token: https://console.apify.com/account/integrations?fpr=ymnoit&utm_source=apify-readme&utm_medium=referral

Key features

• 41 fields per review: review id, stars, title, text, nickname, date, verified purchase, incentivized, Walmart associate and Top Reviewer flags, helpful and unhelpful votes, photos, videos, syndication source, the brand's reply and who wrote it, the variant bought, seller and fulfiller, then the product's title, link, price, category path, average rating, total ratings, written reviews and recommend share.
• Up to 10,000 reviews per product. Walmart shows 10 written reviews a page; the actor reads page after page until your cap or the last page Walmart offers for your filters.
• Five sort orders: most recent, most helpful, most relevant (Walmart's default), highest rating and lowest rating.
• Star filter and verified only: pick any mix of 1 to 5 stars and switch on verified purchases only. Walmart applies both before paging, so the cap counts only matching reviews.
• Up to 1,000 products per run, three read side by side, each with its own status in the run summary.
• Only new reviews on repeat runs: switch it on for a schedule and each run returns, and charges, only reviews no earlier run in your account delivered.

How to use it

Basic: the newest reviews of one product

{
  "products": ["https://www.walmart.com/ip/Ninja-Fresh-Brew-CE451/18210159416"],
  "maxReviewsPerProduct": 300
}

You get up to 300 rows, newest first, each with the product's title, price, category and rating counts copied on.

Several products at once

{
  "products": [
    "https://www.walmart.com/ip/12516374178",
    "https://www.walmart.com/reviews/product/18210159416",
    "985675140",
    "2860977484"
  ],
  "maxReviewsPerProduct": 150,
  "sort": "most_recent"
}

This is the input of our proof run: 600 reviews, 150 per product, in 131 seconds. Each product has its own line in the run summary (status, pages read, why it stopped).

Daily complaint watch on your own products

{
  "products": ["12516374178", "18210159416"],
  "maxReviewsPerProduct": 50,
  "sort": "most_recent",
  "stars": ["1", "2"],
  "onlyNewReviews": true
}

Schedule it daily (Console, Schedules, Add schedule). Each run returns only one and two star reviews that no earlier run delivered, so the dataset is your queue of new complaints. In our two run test the second run found nothing new on the first page, stopped there and charged no reviews.

Competitor teardown: the reviews shoppers found most useful

{
  "products": ["5517246458", "15712861535"],
  "maxReviewsPerProduct": 500,
  "sort": "most_helpful",
  "verifiedPurchaseOnly": true
}

Most helpful first, verified buyers only. Group by rating and read title and text for what buyers praise and what makes them return the product; helpful_votes tells you which complaints other shoppers agree with.

Brand reply audit

{
  "products": ["12516374178"],
  "maxReviewsPerProduct": 1000,
  "sort": "lowest_rating"
}

Lowest rated first. Filter the rows where response_text is filled to see how the brand answers bad reviews, and where it is empty to find the ones nobody answered. In our proof run 57 of 600 rows carried a reply, all from the brands' own care teams.

Syndicated review check

Walmart shows reviews collected on other sites (for example influenster.com) next to its own. Run your usual input and split the rows on syndication_source: empty means the review was written on Walmart.com, a site name means it came from that site. Nine of the 600 proof rows were syndicated.

Input parameters

Parameter	Type	Default	What it does
products	array of strings	two example products	Walmart.com product links, reviews links or item ids, one per line. Up to 1,000 per run; repeats are read once. Required.
maxReviewsPerProduct	integer	100	Reviews to collect per product, 20 to 10,000. With a star filter the cap counts the combined matching list.
sort	string	most_recent	most_recent, most_helpful, most_relevant (Walmart's default), highest_rating or lowest_rating.
stars	array of strings	empty (every rating)	Star levels to keep, any of "1" to "5". Picking all five is the same as no filter.
verifiedPurchaseOnly	boolean	false	Keep only reviews Walmart marks as a verified purchase.
onlyNewReviews	boolean	false	Skip reviews an earlier run of yours already delivered, for schedules. Use with most_recent.

What data do you get?

One row per review. The fields come in six groups.

The review: review_id, rating (1 to 5), title, text, reviewed_at (ISO date, for example 2026-10-03), language, recommended (when Walmart asked the reviewer).

The reviewer and trust signals: reviewer_nickname as Walmart shows it, verified_purchase, incentivized (sweepstakes or free product), walmart_associate, top_reviewer, helpful_votes, unhelpful_votes.

Media and replies: photos and videos (lists of links, empty when none), syndication_source (the site a review came from, empty for reviews written on Walmart.com), response_text and response_from (the brand's or seller's public reply).

What was bought: variant (for example "Color: Seafoam"), reviewed_item_id and reviewed_item_name (Walmart pools reviews across the variants of a product, so these can differ from the product you asked for), sold_by, fulfilled_by.

The product, on every row: item_id, product_title, product_url, product_price, product_category, product_rating, product_review_count (every rating, star only ones included), product_reviews_with_text (written reviews, the ones that can be returned), product_recommended_percent.

Run context: sort, star_filter, verified_only, page, position, reviews_url, input, scraped_at.

Empty values are left out of the row rather than sent as null, so a review without a title simply has no title field.

Stable fields for automations

These fields were present in every one of the 600 rows of our proof run, and their names will not change:

Field	What it holds
item_id	Walmart item id of the product you asked for
product_title	Product title on Walmart.com
review_id	Walmart's own review id, stable across runs (use it to dedupe)
rating	Stars, 1 to 5
reviewed_at	Date the review was posted, YYYY-MM-DD
verified_purchase	true or false
helpful_votes	Shoppers who marked the review helpful
unhelpful_votes	Shoppers who marked it not helpful
photos	List of photo links, empty list when none
product_url	Link to the product
product_rating	Product's average rating
product_review_count	All ratings behind the average
product_reviews_with_text	Written reviews the product has
position	Place of the review in Walmart's list for your sort and filters
scraped_at	When the row was read, ISO 8601 UTC

Output examples

Real rows from our proof run of 5 October 2026, trimmed for length (long text shortened with "...", reviewer nicknames masked).

A one star review with a photo and the brand's reply:

{
  "item_id": "18210159416",
  "product_title": "Ninja Fresh Brew 14-Cup Drip Coffee Maker, Classic & Rich Brew Styles, Delay Brew, CE451, Stainless Steel",
  "review_id": "440420756",
  "rating": 1,
  "title": "Failed in 9 Months cutting the cord with all Ninja",
  "text": "Failed after only about 9 months of normal use. The disappointing part wasn't just the product failure...",
  "reviewer_nickname": "J****",
  "reviewed_at": "2026-09-13",
  "verified_purchase": true,
  "helpful_votes": 0,
  "unhelpful_votes": 0,
  "photos": ["https://i5.walmartimages.com/dfw/6e29e393-9ca2/k2-_240f65bb-4b1d-42f2-a30d-e0dd4d3afd77.v1.jpg"],
  "response_text": "Hi J****, thank you for taking the time to share your experience with the Ninja 12-Cup Programmable Drip Coffee Maker...",
  "response_from": "SharkNinja Product Expert",
  "reviewed_item_id": "997508948",
  "sold_by": "Walmart.com",
  "fulfilled_by": "Walmart",
  "product_price": 99.99,
  "product_category": "Home > Appliances > Kitchen Appliances > Coffee Shop > Ninja Coffee Makers",
  "product_rating": 4.6,
  "product_review_count": 9144,
  "product_reviews_with_text": 2806,
  "sort": "most_recent",
  "page": 8,
  "position": 72
}

A review syndicated from another site (no verified purchase flag, as Walmart shows it):

{
  "item_id": "18210159416",
  "review_id": "407118691",
  "rating": 4,
  "title": "Easy clean, easy to use and quiet.",
  "text": "Brews faster then my old mr.coffee maker, it doesn't make the really loud gargling sound that most do...",
  "reviewer_nickname": "H*******",
  "reviewed_at": "2026-09-30",
  "verified_purchase": false,
  "syndication_source": "influenster.com",
  "photos": [],
  "product_rating": 4.6,
  "product_review_count": 9144,
  "page": 2,
  "position": 16
}

A short verified review of a different variant than the one asked for (Walmart pools reviews across colors):

{
  "item_id": "12516374178",
  "product_title": "Keurig K-Express Essentials Black Single-Serve K-Cup Pod Coffee Maker",
  "review_id": "442829804",
  "rating": 1,
  "text": "It was not the color I ordered. I ordered RED not white",
  "reviewer_nickname": "B**",
  "reviewed_at": "2026-10-03",
  "verified_purchase": true,
  "variant": "Color: Red",
  "reviewed_item_id": "17400009688",
  "sold_by": "Walmart.com",
  "fulfilled_by": "Walmart",
  "product_rating": 4.4,
  "product_review_count": 13039,
  "page": 1,
  "position": 2,
  "reviews_url": "https://www.walmart.com/reviews/product/12516374178"
}

Pricing

Pay per event: you pay for each review delivered to your dataset, plus a flat $0.005 per run, whatever memory you choose. Prices per review by Apify plan:

Event	Free plan	Bronze (Starter)	Silver (Scale)	Gold and above (Business)
Review delivered (review-scraped), per 1,000	$0.25	$0.25	$0.25	$0.25
Run start (run-start), once per run	$0.005	$0.005	$0.005	$0.005

Free plan runs return up to 10 results each; paid plans have no cap.

What is never charged:

• Item ids Walmart has no product for, and products with no written reviews.
• Pages Walmart refused, even after retries.
• A review Walmart shows twice across its pages: the second copy is skipped.
• Reviews an earlier run already delivered, when Only new reviews is on.
• The information row at the end of the dataset (it has "_type": "info").

Proxy traffic goes through Apify's datacenter proxy, which is included in the price; there is no separate proxy fee.

FAQ

What do I get on the free plan? On Apify's free plan every run returns the first 10 results as a preview, so you can check the data and the fields before you pay. A paid Apify plan returns every result with no cap: https://apify.com/pricing?fpr=ymnoit

What does this actor read? The public review pages of Walmart.com (the "See all reviews" page of each product), logged out, the way any shopper sees them. It does not use a Walmart account, an API key or your cookies.

How many reviews can I get for one product? Up to 10,000 per product per run, limited by how many written reviews the product has. Walmart lists only reviews with text; star only ratings count toward product_review_count but never appear as rows. For the Keurig in our proof run that is 2,467 written reviews out of 13,039 ratings, and its last page (page 247, reviews 2,461 to 2,467, back to March 2025) answered like the first, so the whole written list is reachable.

How fresh is the data? Live. Every run reads Walmart at that moment. With Most recent sort, the first rows are the reviews posted in the last day or two on a busy product.

Do I need a Walmart account, cookies or a proxy of my own? No. Nothing to log in to and nothing to configure. The actor uses Apify's datacenter proxy, which the run includes.

Does it work for walmart.ca or other countries? No, Walmart.com (United States) only. Links to other Walmart sites are skipped with a note in the log.

Why does a review show a different item than the one I asked for? Walmart pools reviews across the variants of a product (colors, sizes, pack counts). item_id is always the product you gave; reviewed_item_id, reviewed_item_name and variant say which exact variant the reviewer bought.

What happens with a wrong item id or a removed product? It gets status not_found in the run summary (the OUTPUT record), with the reason, and costs nothing. The other products in the run go on as normal.

Why can the most helpful order return fewer new reviews per page? Walmart's own pages overlap a little for some sorts: the same review can appear on two pages. The actor keeps the first copy, skips the second and keeps paging, so you still reach your number, and repeats are never charged.

Can I run it on a schedule and get only new reviews? Yes. Turn on onlyNewReviews, keep sort on most_recent, and add a schedule in Console (Schedules, Add schedule, daily or weekly). Each run delivers and charges only reviews no earlier run in your account delivered, and stops as soon as it reaches ones it has seen.

What formats can I export? JSON, CSV, Excel, XML, RSS and HTML from the dataset tab, or through the API. In CSV and Excel a list such as photos is spread over numbered columns (photos/0, photos/1).

Can I use it from Claude, ChatGPT or Cursor (MCP)? Yes, through Apify's MCP server.

• Connector URL: https://mcp.apify.com/?tools=themineworks/walmart-reviews-scraper
• Claude: Settings > Connectors > Add custom connector, paste the URL, sign in with Apify.
• ChatGPT: developer mode, add an MCP connector with the URL, sign in with Apify.
• Cursor or VS Code: add it as an HTTP MCP server with that URL.
• Claude Code: claude mcp add -t http walmart-reviews-scraper "https://mcp.apify.com/?tools=themineworks/walmart-reviews-scraper"

I also need prices, stock and sellers. Use our Walmart Product & Price Scraper on the same products or on whole categories, and join the two datasets on the item id.

Is it legal to scrape Walmart reviews? The actor reads only public pages and returns what any visitor can see. Reviewer nicknames are the names reviewers chose to show. You are responsible for how you use the data, including Walmart's terms and data protection law such as GDPR and CCPA.

Integrations

• Google Sheets: add the Google Sheets integration to the actor or a schedule, and new rows land in a sheet after each run.
• Make, Zapier and n8n: use the Apify app to start a run and read the dataset, for example to post new one star reviews to Slack.
• Webhooks: call your own endpoint when a run finishes.
• API: start runs and read results from any language; the Python and JavaScript clients are a few lines each.
• MCP clients: Claude, ChatGPT, Cursor, VS Code and Claude Code, as in the FAQ above.

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Support

Found a product that does not come through, or a field you need? Open an issue on the Issues tab and include the product link; we answer there. For a new site or source, email dmineworks@gmail.com.

Walmart Reviews Scraper turns any list of Walmart.com products into a clean table of reviews, with the filters Walmart's own page offers and a charge only for the reviews you get.