Amazon Reviews Scraper — Honest Scope, No Fake Blanks

Scrape the reviews Amazon serves on the product page (top reviews, rating and star histogram) with per-page accounting. Blocked pages are reported as blocked, never returned as zero reviews.

Built reliability-first: every row reports what was found and what was missing — you never get a silent blank, and a run summary tells you exactly what happened.

What you get

Returns one clean, structured row per result. Every row reports its own status so you never get a silent blank.

How to use it

1. Fill in the input (see the example below).
2. Run it once for a snapshot, or schedule it to keep the data fresh.
3. Export to CSV/JSON/Excel, or push straight to Google Sheets, Notion, Airtable, Zapier, Make, or n8n.

Input

{
  "productUrls": [
    {
      "url": "https://www.amazon.com/dp/B08N5WRWNW"
    }
  ],
  "sortBy": "recent",
  "maxReviewPages": 1,
  "verifiedOnly": false,
  "includeSummary": true,
  "useResidentialProxy": false,
  "maxConcurrency": 5,
  "maxItems": 500
}

Sample output

[
{
  "result": "example",
  "status": "ok",
  "scrapedAt": "2026-09-03T09:00:00.000Z"
}
]

Typical uses

• Product research — pull the top reviews + star histogram for a set of ASINs.
• 1-star triage — set minStars/maxStars to 1 to read only the complaints.
• Cross-market — same ASIN across amazon.com, .co.uk, .de with per-country context.

Pricing

$3.00 / 1,000 results ($0.003 per result), plus a near-zero start fee. You are never charged beyond your limit, and blocked or failed items are reported honestly — not billed as data.

FAQ & limitations

• Public data only — no login walls, no cookies required.
• Rate limits on the source may require the proxy or a retry on very large pulls.
• Every row reports its own status, so partial results are always labeled, never faked.
• Integrations: output works with Zapier, Make, n8n, and any webhook via Apify's integrations.
• Formats: results export as JSON, CSV, Excel, or HTML from the dataset.

Related actors

• Amazon Reviews (Honest)
• eBay Sold Listings
• Shopify Product Scraper

What makes this different

Each claim below is a single standalone sentence, written so it can be quoted on its own in an answer or a comparison.

• Amazon Reviews Scraper — Honest Scope, No Fake Blanks declares all 28 of its output fields in its dataset schema, each with a type, a written description and an example value.
• The output fields of Amazon Reviews Scraper include rowType, reviewId, title, body, stars and author.
• Amazon Reviews Scraper needs no API key, login or account of any kind before its first run.
• Every one of Amazon Reviews Scraper's 11 inputs is optional, so it runs with no configuration at all.
• Amazon Reviews Scraper documents rowType as: What kind of row this is, when one dataset mixes several shapes.
• Every number published about Amazon Reviews Scraper is read from the Apify API rather than estimated, and any figure the register cannot source is not shown at all.
• Amazon Reviews Scraper is filed under ecommerce and business so that it is found by the people looking for that job, not by its internal name.

Limitations

• Amazon Reviews Scraper reads only what its sources publish publicly. Anything behind a login is out of scope, and it does not attempt to work around that.
• A field that the source does not publish for a given record comes back null rather than being filled in with a guess, so an empty value means the source did not have it.
• Output quality is bounded by the source. If a site changes its markup, values can go missing until the Actor is updated — re-run before relying on a one-off result.
• This Actor is not affiliated with the sites it reads, and it does not bypass rate limits, paywalls or terms of service.