Amazon Reviews Scraper & Extractor

Extract Amazon customer reviews — full review text, star rating, Verified Purchase badge, author, date and variant — from any Amazon marketplace. Clean, flat JSON/CSV for sentiment analysis, competitor research, and automation in n8n, Zapier, Make.com or your own LLM pipeline.

What you get

One flat row per review, ready for analysis:

{
  "productAsin": "B0D3ZBFMW6",
  "marketplace": "amazon.com",
  "reviewId": "R2XKLPV8QN3ZTY",
  "rating": 5,
  "title": "Works great - the bags are well made!",
  "text": "So far, so good! I just got this home and used it to seal and freeze a couple of ribeye steaks. The seal was tight and the bags feel much sturdier than the ones I used before.",
  "verifiedPurchase": true,
  "authorName": "Dawn",
  "reviewDate": "2026-07-09T00:00:00.000Z",
  "reviewCountry": "United States",
  "helpfulVotes": 5,
  "variant": "Size: Vacuum Sealer + 30 Bags"
}

Any field that could not be read from the page is null. It is never filled with a placeholder such as "N/A", "Unknown", 0 or today's date.

How many reviews per product — read this first

Amazon publishes roughly 8-16 reviews per product to logged-out visitors, and this Actor returns those.

That is the whole set Amazon serves without a signed-in session: the reviews inlined on the product page, including its "top reviews from other countries" block. The dedicated /product-reviews/ list now redirects to a sign-in page, so the complete review history is not reachable by any logged-out scraper — including this one.

maxReviewsPerProduct is therefore a cap, not a promise. Setting it to 1000 does not produce 1000 reviews; the run tells you in the log and in the OUTPUT record exactly how many Amazon exposed for each URL.

If you need the full review history of a product, this Actor is not the right tool and you should not buy it expecting that.

Supported marketplaces

The marketplace in the URL you submit is the marketplace that gets scraped:

amazon.com · amazon.co.uk · amazon.de · amazon.fr · amazon.it · amazon.es · amazon.nl · amazon.se · amazon.pl · amazon.com.be · amazon.ca · amazon.com.mx · amazon.com.br · amazon.in · amazon.co.jp · amazon.com.au · amazon.sg · amazon.ae · amazon.sa · amazon.eg · amazon.com.tr · amazon.ie · amazon.cl · amazon.co.za · amazon.com.ng

Always paste the full product URL — a bare ASIN such as B0D3ZBFMW6 is not a valid URL and is rejected before the run starts.

Input

{
  "productUrls": [
    { "url": "https://www.amazon.com/dp/B0D3ZBFMW6" },
    { "url": "https://www.amazon.in/dp/B07PHQ1YP5" }
  ],
  "maxReviewsPerProduct": 20,
  "starRatings": ["1", "2", "3", "4", "5"],
  "verifiedOnly": false,
  "sortBy": "all"
}

Field	Type	Default	Description
productUrls	Array	one example URL	Amazon product URLs. The marketplace in each URL is respected.
maxReviewsPerProduct	Integer	20	Upper cap per product. Amazon exposes about 8-16, so a larger number does not return more.
starRatings	Array	["1","2","3","4","5"]	Keep only these star ratings, e.g. ["1","2"] for negative reviews.
verifiedOnly	Boolean	false	Keep only reviews with Amazon's Verified Purchase badge.
sortBy	String	"all"	recent, helpful, or all (Amazon's own order). Applied after collection.
proxyConfiguration	Object	Apify Residential	Amazon serves a captcha wall to a large share of datacenter requests, so residential is the default.

Because the filters are applied to the ~8-16 reviews Amazon publishes, a narrow filter (for example verifiedOnly: true combined with starRatings: ["1"]) can legitimately return very few rows or none. The run says so explicitly rather than returning a silent empty dataset.

Output fields

Field	Type	Description
productAsin	string	ASIN of the reviewed product
marketplace	string	Marketplace the review was collected from, e.g. amazon.in
reviewId	string | null	Amazon's own review id — stable across runs, usable as a dedupe key
rating	integer | null	Star rating 1-5
title	string | null	Review headline
text	string | null	Full review body as plain text
verifiedPurchase	boolean	Verified Purchase badge present
authorName	string | null	Reviewer's public display name
reviewDate	string | null	ISO 8601 date at UTC midnight
reviewCountry	string | null	Country the review was written in (differs from marketplace for cross-country reviews)
helpfulVotes	integer	Helpful-vote count. Amazon omits the line entirely at zero, so 0 means "no statement shown".
variant	string | null	Variant the reviewer bought

Honest run reporting

Every run writes an OUTPUT record to its key-value store with one entry per submitted URL, so you always know what happened to each one:

Status	Meaning
ok	Reviews were delivered
no-reviews	Amazon itself states this product has no customer reviews yet
all-filtered-out	Reviews existed, your filters removed all of them
not-found	That ASIN is not sold on that marketplace
blocked	Amazon served its anti-bot page on every attempt
login-gated	Amazon redirected to a sign-in page
invalid-url	The URL contained no usable ASIN
charge-limit	The run's maximum cost was reached before these reviews could be stored

Rules this Actor follows:

• If nothing could be delivered because of a problem on our side, the run fails loudly instead of reporting success with an empty dataset.
• If nothing could be delivered because the products genuinely have no reviews or your filters removed them all, the run succeeds and says exactly that.
• No number printed in the log is ever larger than what actually landed in the dataset.

Use cases

• Sentiment analysis — feed text + rating straight into an LLM or classifier
• Competitor research — track what buyers praise and complain about across rival ASINs
• Product development — mine recurring pain points and feature requests
• Support monitoring — filter starRatings: ["1","2"] and alert on new negatives
• Cross-market comparison — same product, amazon.com vs amazon.de vs amazon.in

Automation

Works as a normal Apify Actor in n8n, Zapier, Make.com and the Apify API. A typical monitoring setup:

1. Schedule the Actor daily with your ASIN list
2. Filter rows to rating <= 2
3. Deduplicate on reviewId
4. Post new negatives to Slack or a Notion database

Pricing

Pay-per-event: you are charged per review that is actually stored in the dataset, plus Amazon's standard Actor-start event. Reviews that are not delivered are not charged. Current per-event prices are shown in the Apify Console before you start a run.

If a run hits the "Maximum cost per run" you set, it stops storing and charging, and reports the shortfall explicitly rather than pretending it delivered everything.

Limitations

1. About 8-16 reviews per product. Amazon login-gates the full list; see above. This is a hard ceiling, not a configuration issue.
2. Amazon occasionally serves an anti-bot page. The Actor rotates to a fresh residential IP and retries, then reports blocked if it still cannot get through.
3. Sorting is applied after collection, because Amazon does not let logged-out clients re-sort the product page.
4. A product not sold on the marketplace in the URL returns not-found — check you are using the right storefront domain.

Legal & compliance

• Collects publicly accessible review data only — no login, no authentication bypass
• No customer account credentials or session cookies are used or requested

This Actor is a general-purpose tool for analyzing publicly accessible web data. The user bears sole responsibility for ensuring their specific use complies with applicable laws (GDPR/DSGVO, copyright law), the target website's Terms of Service, and Apify's Terms of Service. The provider (webdatalabs) expressly disclaims liability for any unauthorized or unlawful use. By using this Actor, the user agrees to indemnify the provider against any third-party claims arising from their use of the data.

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Custom solutions & enterprise

Need a custom data feed, modified output format, or enterprise integration?

Contact: Furkanc58@gmail.com

• Daily/weekly data feeds (Snowflake, S3, BigQuery, Google Sheets)
• Custom scrapers for platforms not yet covered
• White-label solutions for agencies
• Priority support and SLAs

Response within 24-48 hours.

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