Walmart Review Scraper with Reviewer and Date Details

Extract Walmart product reviews with full reviewer identity, submission date, and review-authenticity signals — reviewer nickname, author ID, verified-purchase badge, syndicated-review detection, helpful/unhelpful votes, review media, item variant, and Walmart's own star-rating histogram. Give it a Walmart product URL, search URL, or a plain keyword and get a clean, structured Walmart reviews dataset in JSON, CSV, Excel, or via API — no login, no browser, no Walmart account required.

What does this Walmart review scraper do?

Most Walmart review scrapers return only a rating, a title, and a text snippet. This one adds the data you actually need to judge whether a product's reviews are trustworthy:

• Who wrote it — reviewer nickname, a stable pseudonymous author ID, and any reviewer badge (e.g. Top Reviewer / review-count tier) Walmart has assigned.
• When it was submitted — the real submission date on every row.
• Whether it's a genuine Walmart purchase — Walmart's own "Verified Purchase" badge, surfaced as a boolean plus the raw badge text.
• Whether it was syndicated in from another site — a syndicationSource flag Walmart attaches when a review was originally written on a brand's own storefront (e.g. via the Bazaarvoice network) and piped into the Walmart listing rather than written by a Walmart shopper. This is the scraper's core differentiator — checked against the top Walmart-titled actors on Apify, none currently expose it.
• Supporting signals — helpful/unhelpful vote counts, recommended (thumbs up/down), seller name and fulfillment type, which item variant (color/size) was reviewed, review photo/video URLs, and the product's own star-count histogram (productRatingSummary).

Who is this for?

• Brand and category managers auditing whether a product's rating is propped up by borrowed (syndicated) or unverified reviews.
• E-commerce and market researchers who need dated, attributable Walmart review data instead of an undated text blob.
• Review-monitoring and reputation teams tracking new reviews over time with a real submission-date filter.
• Data teams / analysts building a Walmart customer-review dataset for sentiment, trend, or competitor benchmarking work downstream.

Key features

• 🔗 Accepts a Walmart product URL, a search URL, or a plain keyword — bulk input supported, one entry per line.
• 🔀 Five review sort orders: relevancy, newest first, most helpful, highest rating, lowest rating.
• ✅ Verified Purchase filter — keep only reviews carrying Walmart's own verified-purchase badge.
• 🚫 Syndicated review filter — drop reviews copied in from an external brand site instead of written on Walmart.
• 📅 Date filter (reviewsNewerThan) — absolute (YYYY-MM-DD) or relative ("30 days", "6 months", "2 years"); combine with newest-first sort and the scraper stops paging early once it passes your cutoff, saving requests.
• ⭐ Star-rating filter — keep only the 1–5 star reviews you select.
• 🌐 Built-in residential-proxy handling with automatic retry on a fresh IP when Walmart's anti-bot (PerimeterX) blocks a request.
• 📊 Includes Walmart's own rating summary (average rating, per-star counts and percentages, recommended %, total media count) alongside every review row.

What data can you extract? (output fields)

Every row is one Walmart review. Coverage figures below are measured against a live sample (30 reviews across 2 products, 3 sort orders) — they tell you honestly how often a field is populated, not a guarantee for every product.

Field	Description	Coverage / notes
itemType	Constant "Review"	Always present
reviewId	Walmart's internal review ID	Always present, all distinct
rating	Star rating (1–5)	Always present
reviewSubmissionTime	Submission date, M/D/YYYY (date only — Walmart does not provide time-of-day)	Always present
title	Review title	Present when the reviewer wrote one
text	Review body text	Present when the reviewer wrote one (roughly 62% of a product's total reviews are ratings-only with no text at all — see Limitations)
userNickname	Reviewer display name	Almost always present; can legitimately be "anonymous" when the reviewer chose to hide their name
authorId	Stable pseudonymous reviewer key (hashed token, not a real name/account)	Always present
isVerifiedPurchase	true if Walmart's "Verified Purchase" badge is on the review	~70% true in the sample. Reviews from before Walmart introduced the badge (roughly pre-2018) carry no badge at all — false there does not mean "not purchased"
reviewBadges	Raw badge text(s) attached to the review (e.g. "Verified Purchase")	Same coverage as isVerifiedPurchase
reviewerBadges	Reviewer-level badges (e.g. Top Reviewer / review-count tier) with badge ID + value	Low coverage (roughly 1 in 6 reviews) — most reviewers have none, this is expected, not a bug
isSyndicated	true if the review was copied in from an outside brand's own site rather than written on Walmart	Roughly 1 in 6 reviews in the sample — the scraper's core differentiator
syndicationSourceName	Name of the originating brand/platform when isSyndicated is true	Present only when isSyndicated is true
externalSource	Review platform backend (observed constant "bazaarvoice")	Always present, informational
recommended	true/false if the reviewer answered "would you recommend this?"	~63% populated; null when the reviewer didn't answer — never a faked false
positiveFeedback / negativeFeedback	Helpful / unhelpful vote counts on the review	Always present; genuinely 0 on newest-first sort for reviews with no votes yet
status	Walmart's internal review status (e.g. APPROVED)	Present on most reviews, null on some
sellerName / fulfilledBy	Seller name and fulfillment type for the reviewed item	~63% populated; more often null on syndicated/older rows
itemId / itemName	The specific item variant the review is attached to (multi-variant listings roll several items into one review page)	itemName always present; itemId on roughly two-thirds of rows
reviewedVariant	Which product options (e.g. Color, Size) the reviewer's unit had	Roughly two-thirds populated — depends on the category having variant options at all
reviewMediaUrls	Direct URLs to photos/videos the reviewer attached	Only a minority of reviews include media (roughly 1 in 5 in the sample)
originalLanguage	Review language (observed constant "English" on English-market listings)	Always present
productRatingSummary	Walmart's own aggregate block for the product: average rating, total review count, text-review count, per-star counts and percentages, recommended %, total media count	Present on every fetched page (repeats per row, since it describes the product, not the individual review)
productUrl	The product page URL the review belongs to	Always present
scrapedAt	UTC timestamp of when the row was scraped	Always present

Input parameters

Field	Type	Default	Description
startUrls	array (required)	—	One entry per line: a Walmart product URL, a search URL, or a plain keyword.
sortOrder	string (enum)	relevancy	relevancy, submission-desc (newest first), helpful, rating-desc, rating-asc.
maxComments	integer	5	Max reviews to keep per product, counted after all filters below are applied — e.g. maxComments:5 + verifiedPurchasesOnly:true keeps fetching until 5 verified reviews are found (or reviews run out), never more.
maxProductsPerStartUrl	integer	10	For search URLs/keywords, how many products to process per start URL.
skipProductsWithoutReviews	boolean	true	Skip a product entirely if it has no reviews, to save time.
verifiedPurchasesOnly	boolean	false	Keep only reviews carrying Walmart's Verified Purchase badge. Off by default because it can silently remove a product's entire pre-badge (roughly pre-2018) review history.
excludeSyndicatedReviews	boolean	false	Drop reviews copied in from an outside brand's own site.
reviewsNewerThan	string (date)	empty	Absolute date (YYYY-MM-DD) or relative window ("30 days", "6 months", "2 years"). Leave empty for no cutoff. Precision is to the day (Walmart's own timestamp has no clock time).
ratings	array (multi-select)	[]	Keep only the star ratings you select (1–5). Empty = keep all.
proxyConfiguration	object	Apify residential proxy	Proxy strategy. Walmart's PerimeterX protection blocks nearly all datacenter/no-proxy traffic on product and review pages, so a residential proxy is used by default with automatic escalation/retry on a fresh IP when a block is detected.

Example input

{
  "startUrls": ["https://www.walmart.com/search?q=tshirt"],
  "sortOrder": "submission-desc",
  "maxComments": 20,
  "maxProductsPerStartUrl": 5,
  "skipProductsWithoutReviews": true,
  "verifiedPurchasesOnly": true,
  "excludeSyndicatedReviews": false,
  "reviewsNewerThan": "6 months",
  "ratings": ["1", "2"]
}

Output example

{
  "itemType": "Review",
  "productUrl": "https://www.walmart.com/ip/product-name/123456",
  "rating": 5,
  "title": "Great quality for the price",
  "text": "Fits true to size and the material feels durable after a few washes.",
  "reviewId": "abcd1234-ef56-7890-ab12-cd34ef567890",
  "authorId": "9f8e7d6c5b4a3210",
  "userNickname": "JaneD",
  "reviewSubmissionTime": "3/14/2026",
  "isVerifiedPurchase": true,
  "reviewBadges": ["Verified Purchase"],
  "reviewerBadges": [{ "badgeId": "TOP_REVIEWER", "badgeValue": "1,700" }],
  "isSyndicated": false,
  "syndicationSourceName": null,
  "externalSource": "bazaarvoice",
  "recommended": true,
  "positiveFeedback": 4,
  "negativeFeedback": 0,
  "status": "APPROVED",
  "sellerName": "Walmart.com",
  "fulfilledBy": "Walmart",
  "itemId": "123456",
  "itemName": "Men's Classic T-Shirt",
  "reviewedVariant": [{ "name": "Color", "value": "Navy" }],
  "reviewMediaUrls": [],
  "originalLanguage": "English",
  "productRatingSummary": {
    "averageOverallRating": 4.4,
    "totalReviewCount": 17204,
    "reviewsWithTextCount": 6533,
    "recommendedPercentage": 91
  },
  "scrapedAt": "2026-07-30T12:00:00Z"
}

How to use it

1. Open the actor and paste one or more Walmart product URLs, search URLs, or keywords into startUrls.
2. Set maxComments for how many reviews you want per product, and pick a sortOrder (use submission-desc if you're also using the date filter — it lets the run stop early once it passes your cutoff).
3. Turn on any of the four authenticity filters (verifiedPurchasesOnly, excludeSyndicatedReviews, reviewsNewerThan, ratings) you need.
4. Run the actor. Reviews stream into the dataset as they're found — export as JSON, CSV, Excel, or pull them via the Apify API.

Pricing — how billing works

This actor is pay-per-event: you are billed per review row written to your dataset, not per page fetched. If you enable filters, the run may still need to read through several pages of raw reviews to find enough matches, but you are only charged for the rows that pass your filters and are actually saved — filtered-out reviews are never counted or billed.

Filtering — how it works under the hood

Walmart's own review endpoint does not support server-side filtering by rating, verified status, or date — all four filters in this actor (verifiedPurchasesOnly, excludeSyndicatedReviews, reviewsNewerThan, ratings) are applied client-side, after each page of reviews is fetched. The one exception is the newest-first + date-cutoff combination: sorting by submission-desc while using reviewsNewerThan lets the run stop paging as soon as an entire page is older than your cutoff, which does reduce the number of pages fetched.

Limitations & honest caveats

• Roughly 62% of a product's total reviews are ratings-only, with no text, and are not retrievable through Walmart's review pagination at any depth — this is a platform ceiling (confirmed on products with 17,000+ total reviews but only a few thousand ever surfacing in the paginated review feed), not a bug in this actor.
• reviewerBadges and reviewMediaUrls are genuinely low-coverage fields on Walmart (most reviewers have no badge and don't attach photos/video) — expect them populated on a minority of rows.
• authorId is a hashed, pseudonymous token for deduplication/analysis purposes — it is not a real name, email, or account identifier.
• verifiedPurchasesOnly can remove a product's entire pre-2018 review history, since the Verified Purchase badge did not exist before then. It defaults to false so you see the full verified/unverified mix first.
• reviewSubmissionTime is date-only — Walmart does not expose a submission time-of-day.
• Product-level metadata beyond the rating histogram (price, category, full seller catalog data) is out of scope for this actor, which focuses on review content and authenticity — not full product-listing data.

FAQ

Does this scraper require a Walmart login or API key? No. It reads Walmart's own public review pages; no account, cookie, or login is used or required.

Why did I get fewer reviews than my maxComments value? maxComments is a ceiling, not a guarantee — a product may simply have fewer reviews than requested, especially once filters like verifiedPurchasesOnly or ratings are applied.

Can I filter reviews by both star rating and verified-purchase status at the same time? Yes — all four filters (verifiedPurchasesOnly, excludeSyndicatedReviews, reviewsNewerThan, ratings) can be combined; a review must pass every filter you enable to be kept.

What does "syndicated review" mean and why does it matter? It's a review Walmart displays that was originally written on a different brand-owned storefront and then piped into the Walmart product listing, rather than written by a Walmart customer. Some products' ratings lean heavily on syndicated reviews rather than genuine Walmart purchases — this actor is built to surface that distinction.

Is userNickname sometimes just "anonymous"? Yes — some reviewers choose to hide their name on Walmart, and the review itself is still real. It's passed through as-is rather than dropped or faked.

Does it work on search-result pages, not just single products? Yes — give it a Walmart search URL or a plain keyword and it discovers products from the results, up to maxProductsPerStartUrl per start URL, then scrapes reviews for each.

Compliance

This actor only collects publicly visible review data from Walmart's own product and review pages — no login, private data, or personal account information is accessed.