Sam's Club Customer Reviews Scraper

Reading Sam's Club reviews by hand stops working the moment you care about more than one item. The ratings live behind pagination, the star counts sit in a summary block, and copy-pasting hundreds of comments into a sheet is its own afternoon. Paste a review page URL here and the scraper walks every page for you, returning each review as a clean row: the star score, the headline, the full text, who wrote it, whether they actually bought the item, and how many shoppers found it helpful. Each row also carries the item's average score and total review count, so you have the headline numbers and the raw feedback side by side. Run one URL or a whole list.

What you get

Each review comes back as one row with a steady set of columns, so loading results into a spreadsheet or database stays predictable. Two layers of data per row:

• The review — feedbackId, starScore, headline, reviewText, authorName, submittedOn, verifiedBuyer, helpfulCount, feedbackTotal
• The item context — itemSku, reviewsPageUrl, averageScore, reviewsCount, scoreBreakdown, plus collectedAt and errorMessage

Quick start

1. Click Try for free and open the input form.
2. Paste one or more Sam's Club review page URLs into Review page URLs, one per line.
3. Set Reviews to pull per item to cap how many reviews you gather from each link.
4. Press Start, then export as JSON, CSV, Excel, or XML once the run finishes.

Use cases

• Product research — read what real buyers say before sourcing or reselling an item
• Sentiment tracking — group reviews by star score to see where a product wins or loses
• Competitor comparison — line up review counts and average scores across rival items
• Quality monitoring — watch for a drop in ratings or a spike in low-star complaints
• Voice-of-customer mining — pull review text in bulk to feed keyword or theme analysis
• Catalog enrichment — attach live rating data to your own product listings

Input

Field	Type	Required	Description
reviewPageUrls	array of strings	Yes	Sam's Club review page URLs to gather, one per line. Each link is handled on its own.
reviewsLimit	integer	No	How many reviews to pull from each URL. Default 50.
timeoutSeconds	integer	No	Seconds allowed per request before it is dropped. Default 90; raise it when deeper pages time out.

Example input

{
    "reviewPageUrls": [
        "https://www.samsclub.com/reviews/product/prod25430011?entryPoint=viewAllReviewsTop",
        "https://www.samsclub.com/reviews/product/990312885"
    ],
    "reviewsLimit": 50,
    "timeoutSeconds": 90
}

Output

Every review becomes one row, and each row repeats the item-level numbers so a single record stands on its own. Fields with no value come back as null so the dataset stays rectangular.

Example output

{
    "itemSku": "prod25430011",
    "reviewsPageUrl": "https://www.samsclub.com/reviews/product/prod25430011",
    "feedbackId": "rev_88421007",
    "starScore": 5,
    "headline": "Great value for a big family",
    "reviewText": "Bought this for our weekly grocery run and it has held up far better than the brand we used before. Will buy again.",
    "authorName": "Marisol G.",
    "submittedOn": "2026-05-18T14:22:00.000Z",
    "verifiedBuyer": true,
    "helpfulCount": 27,
    "feedbackTotal": 31,
    "averageScore": 4.6,
    "reviewsCount": 898,
    "scoreBreakdown": {
        "5": 612,
        "4": 143,
        "3": 71,
        "2": 34,
        "1": 38
    },
    "collectedAt": "2026-06-30T12:00:00.000000+00:00",
    "errorMessage": null
}

Output fields

Field	Type	Description
itemSku	string	Sam's Club item code pulled from the page link
reviewsPageUrl	string	Complete link to the Sam's Club reviews page
feedbackId	string	Identifier unique to this single review
starScore	number	Stars the shopper awarded, from 1 through 5
headline	string	Short title the shopper gave the review
reviewText	string	Body copy of the review
authorName	string	Public nickname of the reviewer
submittedOn	string	When the review was posted
verifiedBuyer	boolean	True when the reviewer is a confirmed buyer
helpfulCount	integer	How many shoppers tagged the review as helpful
feedbackTotal	integer	Up- and down-votes combined
averageScore	number	Mean star rating for the item across all reviews
reviewsCount	integer	Total number of reviews the item has
scoreBreakdown	object	Reviews tallied by star level
collectedAt	string	ISO 8601 timestamp of when the row was captured
errorMessage	string	Reason the request failed; null on success

Tips for best results

• Start with a couple of URLs. Run two or three links before a large batch so any URL-format issue shows up early.
• Set reviewsLimit to match your need. Pulling 50 reviews per item is plenty for a quick read; raise it when you want the full history.
• Raise timeoutSeconds for popular items. Items with thousands of reviews page deeper, so 90-120 seconds keeps later pages from dropping.
• Partial data still lands. If a later page fails, the reviews already gathered are kept and the run moves on rather than losing everything.
• Use the item-level numbers for a fast read. averageScore, reviewsCount, and scoreBreakdown give you the summary picture without reading every comment.

How can I use Sam's Club review data?

How can I use the Sam's Club Customer Reviews Scraper to research a product before buying or reselling? Paste the item's review page URL and the scraper returns every review with its star score, full text, and verified-buyer flag, plus the item's average score and total review count. Sort by starScore to read the harshest and happiest takes first, then use scoreBreakdown to see how the ratings actually split.

How can I export Sam's Club reviews to CSV or Excel for analysis? Run the scraper, let it gather the reviews, then export the dataset as CSV, Excel, JSON, or XML straight from the run page. Each review is one row with consistent columns, so it drops cleanly into a pivot table or a sentiment model without any reshaping.

How can I track Sam's Club ratings across several products at once? Add a separate line for each item's review page URL under reviewPageUrls and the scraper handles them in one run. Because every row repeats itemSku, averageScore, and reviewsCount, you can group by item to compare ratings side by side and watch how feedback shifts over time.

How can I pull review text in bulk for keyword or theme analysis? Set reviewsLimit high enough to capture the volume you want, then collect the reviewText and headline fields across all your items. The result is a tidy corpus of real shopper language you can feed into keyword counts, topic clustering, or any voice-of-customer workflow.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.