Amazon Review Scraper

Read Amazon reviews as a source-linked corpus. Keep rating, title, text, author, date, helpful votes, review identity, and source link together.

What it returns

Each row keeps the Amazon source record beside the fields needed to use it. The opening set is text, url, author, rating, publishedAt, title, businessId, reviewUrl, message, language, reactions, and photos. The complete schema is declared before the run, and dataset views keep related fields together without changing the underlying row.

Input

Amazon Review Scraper accepts source URLs. Run controls stay in the same form.

Field	What it controls	Starting value
startUrls	Paste exact Amazon URLs, one per line.	["https://www.amazon.com/dp/B09LK1P1RD"]
maxItems	Stop after this many dataset rows.	100
maxSeconds	Stop after this many seconds and keep completed rows.	240
includeEmpty	Keep empty-result records in the returned record.	false

Example input

{
  "startUrls": [
    "https://www.amazon.com/dp/B09LK1P1RD"
  ],
  "maxItems": 3,
  "maxSeconds": 240,
  "includeEmpty": false
}

No field is required. Start with the filled example, then replace only the target values needed for the job. Run controls can stay at their starting values for the first collection.

Dataset fields

Field	Type
text	`string
url	`string
author	`string
rating	`string
publishedAt	`string
title	`string
businessId	`string
reviewUrl	`string
message	`string
language	`string
reactions	`string
photos	`string
scrapedAt	`string

Dataset views

Views are working surfaces for review and export. They select and order fields while leaving the stored row unchanged.

View	Opening fields
overview	text, rating, reviewUrl, author, title, businessId, publishedAt, and scrapedAt
content	author, title, url, and text
engagement	author, title, url, rating, reviewUrl, and reactions
identity	author, title, and businessId
timing	author, title, url, publishedAt, and scrapedAt
provenance	url

Output and exports

Output	Type	Destination
results	string	{{links.apiDefaultDatasetUrl}}/items
json	string	{{links.apiDefaultDatasetUrl}}/items?clean=true&format=json
csv	string	{{links.apiDefaultDatasetUrl}}/items?clean=true&format=csv
excel	string	{{links.apiDefaultDatasetUrl}}/items?clean=true&format=xlsx
jsonl	string	{{links.apiDefaultDatasetUrl}}/items?clean=true&format=jsonl

Completed rows are available in the Apify dataset as JSON, CSV, Excel, and JSONL exports. The run output also carries the declared links above for API clients and automations.

Pricing

$5 per 1,000 dataset items on the Free plan. Other Apify plans use the rates shown in the Pricing tab.

Console, API, schedules, and MCP

Runs can begin in Apify Console, from a saved task, or through the Actor API. A schedule can reuse the same input, and a run-finished webhook can pass the dataset or run ID to the next system.

POST https://api.apify.com/v2/acts/YJn51LUD2cOFgSOL4/runs
GET  https://api.apify.com/v2/datasets/{datasetId}/items

For MCP selection, use Amazon Review Scraper. Its machine entry carries the same description, input field names, no-required-field contract, output types, dataset fields, views, and pricing facts as this document.

Saved tasks

Twenty saved-task products cover distinct lookup, comparison, research, operations, automation, and export jobs:

• Amazon Review core language status filter: buyer-job; opens overview.
• Amazon Review titles and text file: buyer-job; opens content.
• Amazon Review ratings review URL response: buyer-job; opens engagement.
• Amazon Review authors and titles lookup: buyer-job; opens identity.
• Amazon Review timing publication dates date order: buyer-job; opens timing.
• Amazon Review links authors source: buyer-job; opens provenance.
• Amazon Review titles core copy review: buyer-job; opens overview.
• Amazon Review content text copy review: buyer-job; opens content.
• Amazon Review response signal ranking: buyer-job; opens engagement.
• Amazon Review identity authors match file: buyer-job; opens identity.
• Amazon Review collection times timing timeline: buyer-job; opens timing.
• Amazon Review links source map: buyer-job; opens provenance.
• Amazon Review ratings review URL core: buyer-job; opens overview.
• Amazon Review titles content brief: buyer-job; opens content.
• Amazon Review ratings audience sizing: buyer-job; opens engagement.
• Amazon Review authors identity roster: buyer-job; opens identity.
• Amazon Review publication dates collection times timing: buyer-job; opens timing.
• Amazon Review links and reactions trace file: buyer-job; opens provenance.
• Amazon Review authors handoff: buyer-job; opens overview.
• Amazon Review text titles content: buyer-job; opens content.

Integrations

Use the dataset API from any HTTP client, export rows to a spreadsheet, or send the run ID through an Apify webhook. Saved tasks give schedules and automation tools a stable input without changing the Actor contract.

Related products

• Amazon Rating Scraper
• Amazon Product Scraper
• Amazon Search Scraper
• Shopify Rating Scraper
• AliExpress Rating Scraper

When a run needs attention

• No rows: Open the target in a browser, check spelling and source visibility, then retry the saved example before widening the input.
• A field is empty: Check the field beside its source URL. A missing source value stays empty instead of being replaced with a guess.
• A target fails: Keep successful targets in the dataset, then retry only the affected input.
• An automation cannot find results: Read the dataset ID from the run and request its items endpoint directly.

FAQ

What do I get back from one run?

One row per review with 13 declared fields, opening on text, url, author and rating. The schema is published before the run, so you know the shape before you spend anything.

Do I need a amazon account or login?

No. The run works from the amazon sources you supply in the input. Nothing is posted, changed or accessed on your behalf.

What does a run cost?

The current rate is shown on the Pricing tab and is charged per row you receive, so a run that finds nothing costs close to nothing. Cap the run with the item limit when you want a predictable ceiling.

Can I try it before committing budget?

Yes. Cap the run with the item limit in the input and inspect the first rows. The cap is enforced before charging, so a trial run stays a trial.

What do I put in the input?

The staged input is already usable: startUrls, maxItems and maxSeconds. Replace the staged target with your own list when you are ready to run for real.

Are any fields required?

No field is required. Every input carries a working default, so the Actor can be started as-is and refined afterwards.

Can I schedule this to run on its own?

Yes. Save the input as an Apify task and attach a schedule. Keep separate tasks when different teams need different targets or delivery paths.

Do I need to configure proxies?

No. Network access is handled inside the Actor and needs no proxy configuration from you.

How fresh is the data?

Every row is collected during the run you start, not served from a cache. Re-run the same input whenever you need the current state of a amazon review.

Can I use the results commercially?

The Actor collects publicly accessible amazon information. You remain responsible for how you use it, including any privacy or contractual obligations that apply to your business.

How do I compare two runs?

Keep text and url as your join key and diff the exports. The identity fields stay stable across runs, which is what makes a comparison meaningful.

What happens if a source fails mid-run?

The run continues through the remaining sources and finishes with what it collected. Partial results are still written to the dataset rather than discarded.

Can I limit how long a run takes?

Yes. The maxItems input caps the run. Use it when you need a predictable cost and a predictable finish time.

How do I report a problem?

Open an issue on the Actor with the run ID, the input you used and the field or row that needs attention. The run ID lets the exact execution be inspected.

How is this different from Amazon Rating Scraper?

Amazon Review Scraper answers one job: Read Amazon reviews as a source-linked corpus.. Amazon Rating Scraper covers a different question on the same platform. Run both when you need both sides.

How do I read the output without scrolling through JSON?

Open the overview view on the Output tab. 6 views ship with the Actor (overview, content, engagement, identity, timing and provenance), each grouping the fields that belong to one question.

How do I get the data into my own tools?

Export the dataset as JSON, CSV, Excel or XML, call the dataset API directly, or attach a run-finished webhook and collect the dataset reference as soon as the run ends.

Can an agent or LLM call this?

Yes. Amazon Review Scraper is exposed over MCP with the same description, no-required-field input contract and output types shown here, so an agent can select and call it without a human in the loop.

Why is a value empty on some rows?

amazon does not expose every field on every review. An absent value stays empty rather than being filled with a guess, so a row never invents a fact it did not receive.

A run returned fewer rows than I expected. Why?

The usual causes are a narrow source list, an item cap still set low, or a source that genuinely holds less than expected. Widen the input or raise the cap and run again.

Support

Use the Actor issue form for product questions, broken source routes, schema mismatches, and feedback. Include the smallest input that reproduces the problem. That is enough to locate the run and its dataset without sharing an entire working list.

Use this Actor only for data you are allowed to collect. Follow source terms, privacy law, and your own retention policy.