# Amazon Seller Reviews Scraper (`powerai/amazon-seller-reviews-scraper`) Actor

Export buyer feedback for an Amazon seller: ratings, text, dates, and whether the seller replied—one row per review with a collection timestamp.

- **URL**: https://apify.com/powerai/amazon-seller-reviews-scraper.md
- **Developed by:** [PowerAI](https://apify.com/powerai) (community)
- **Categories:** E-commerce, Integrations, Other
- **Stats:** 4 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Amazon Seller Reviews Scraper

Collect buyer reviews left for an Amazon seller: author, star rating, comment text, date, and whether the seller responded—saved as one row per review, with a timestamp on each row.

### Key Features

- Collect up to your chosen **maximum** number of reviews; continues across pages until that limit or until there are no more pages
- Each review typically includes **review\_author**, **review\_comment**, **review\_star\_rating**, **review\_date**, **has\_response**
- Choose **marketplace** (country), optional **star / sentiment filter**, **language**, and optional **fields** projection
- Each record includes **scrapedAt** so you know when it was collected

### Why Use It?

- **Practical**: See how buyers rate a merchant over time
- **Structured**: Clean JSON rows for spreadsheets or downstream tools
- **Steady**: Fetches page by page until your cap or the list ends

### Great For

- Seller reputation checks
- Competitive research on storefront feedback
- Monitoring feedback volume and tone

### Input Parameters

| Parameter | Required | Description |
|-----------|----------|-------------|
| `seller_id` | Yes | The seller ID on Amazon (merchant token). |
| `maxResults` | No | Maximum number of reviews to collect (default: 48). |
| `geo` | No | Which country’s Amazon site to use (default: `US`). Pick **UK** for the United Kingdom marketplace. |
| `star_rating` | No | Filter by star band or sentiment (`ALL`, `5_STARS` … `1_STARS`, `POSITIVE`, `CRITICAL`). Default: all. |
| `language` | No | Preferred language when supported (e.g. `en_US`). |
| `fields` | No | Optional comma-separated attributes if you want a narrower payload. |

### Output

Each dataset row is one review. The actor appends **scrapedAt** (ISO 8601) when the row was written.

| Field | Type | Description |
|-------|------|-------------|
| `review_author` | string | Display name of the buyer who left the review. |
| `review_comment` | string | The review body text (may be short or empty depending on the listing). |
| `review_star_rating` | number | Star rating for this review (e.g. 1–5). |
| `has_response` | boolean | Whether the seller has posted a public reply to this review. |
| `review_date` | string | Review date as returned by the site (e.g. `March 23, 2026`). |
| `scrapedAt` | string | When this row was collected (ISO 8601). |

#### Sample record

```json
{
  "review_author": "Marvonte Green",
  "review_comment": "Good",
  "review_star_rating": 5,
  "has_response": false,
  "review_date": "March 23, 2026",
  "scrapedAt": "2026-03-24T03:19:14.216Z"
}
```

### Notes

- Results depend on what the marketplace exposes for that seller and filters.
- Respect Amazon’s terms and applicable laws when using scraped data.

# Actor input Schema

## `seller_id` (type: `string`):

Amazon seller ID (merchant token) whose buyer reviews you want to collect.

## `maxResults` (type: `integer`):

Maximum number of reviews to collect across pages.

## `geo` (type: `string`):

Which Amazon country site to use. Choose UK for the United Kingdom marketplace.

## `star_rating` (type: `string`):

Optional filter: all ratings, a star band, or positive vs critical.

## `language` (type: `string`):

Optional result language (e.g. en\_US) when supported by the marketplace.

## `fields` (type: `string`):

Optional comma-separated list if you only want certain attributes in each row.

## Actor input object example

```json
{
  "seller_id": "A02211013Q5HP3OMSZC7W",
  "maxResults": 10,
  "geo": "US",
  "star_rating": "ALL",
  "language": "en_US"
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "seller_id": "A02211013Q5HP3OMSZC7W",
    "maxResults": 10,
    "geo": "US",
    "star_rating": "ALL",
    "language": "en_US"
};

// Run the Actor and wait for it to finish
const run = await client.actor("powerai/amazon-seller-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "seller_id": "A02211013Q5HP3OMSZC7W",
    "maxResults": 10,
    "geo": "US",
    "star_rating": "ALL",
    "language": "en_US",
}

# Run the Actor and wait for it to finish
run = client.actor("powerai/amazon-seller-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "seller_id": "A02211013Q5HP3OMSZC7W",
  "maxResults": 10,
  "geo": "US",
  "star_rating": "ALL",
  "language": "en_US"
}' |
apify call powerai/amazon-seller-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=powerai/amazon-seller-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/D4IhdErbIenLJ3bUR/builds/t8rTg0EN2OrFcwyMp/openapi.json