# Amazon Review Aspect & Sentiment Analysis

**Use case:** 

Turn raw reviews into structured sentiment. This task returns Amazon's AI-generated 'Customers say' summary and ReviewAspects (quality, value, ease of use and more) alongside full review text for any ASIN. All star ratings included, up to 100 reviews. Feed the CustomersSay and ReviewAspects fields straight into LLM or sentiment-analysis pipelines for product and brand insight.

## Input

```json
{
  "ASIN_or_URL": [
    "B0DMT42TFS"
  ],
  "country": "United States",
  "End_date": "1990-01-01",
  "recent_days": 0,
  "unique_only": false,
  "get_customers_say": true,
  "max_reviews": 100,
  "sort_reviews_by": [
    "helpful",
    "recent"
  ],
  "filter_by_verified_purchase_only": [
    "all_reviews",
    "avp_only_reviews"
  ],
  "filter_by_ratings": [
    "all_stars"
  ],
  "filter_by_mediaType": [
    "all_contents",
    "media_reviews_only"
  ],
  "variant_scope": "all_variants",
  "filter_by_keywords": [
    "good",
    "perfect",
    "cheap"
  ]
}
```

## Output

```json
{
  "PageUrl": {
    "label": "Page URL",
    "format": "link"
  },
  "ProductLink": {
    "label": "Product Link",
    "format": "link"
  },
  "ASIN": {
    "label": "ASIN",
    "format": "text"
  },
  "Brand": {
    "label": "Brand",
    "format": "text"
  },
  "ProductTitle": {
    "label": "Product Title",
    "format": "text"
  },
  "CustomersSay": {
    "label": "CustomersSay",
    "format": "text"
  },
  "ReviewAspects": {
    "label": "ReviewAspects",
    "format": "array"
  },
  "ReviewId": {
    "label": "Review ID",
    "format": "text"
  },
  "ReviewDate": {
    "label": "Review Date",
    "format": "text"
  },
  "Images": {
    "label": "Images",
    "format": "array"
  },
  "ReviewScore": {
    "label": "Review Score",
    "format": "text"
  },
  "RatingTypeTotalReviews": {
    "label": "Rating Type TotalReviews",
    "format": "text"
  },
  "Reviewer": {
    "label": "Reviewer",
    "format": "text"
  },
  "ReviewerProfileUrl": {
    "label": "Reviewer Profile Url",
    "format": "link"
  },
  "ReviewerId": {
    "label": "Reviewer Id",
    "format": "text"
  },
  "ReviewUrl": {
    "label": "Review Url",
    "format": "link"
  },
  "ReviewTitle": {
    "label": "Review Title",
    "format": "text"
  },
  "ReviewContent": {
    "label": "Review Content",
    "format": "text"
  },
  "Verified": {
    "label": "Verified Purchase",
    "format": "text"
  },
  "Variant": {
    "label": "Variant Details",
    "format": "array"
  },
  "VariantASIN": {
    "label": "Variant ASIN",
    "format": "text"
  },
  "HelpfulCounts": {
    "label": "Helpful Counts",
    "format": "text"
  }
}
```

## About this Actor

This example demonstrates how to use [Amazon Reviews Scraper with Advanced Filters](https://apify.com/delicious_zebu/amazon-reviews-scraper-with-advanced-filters.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/delicious_zebu/amazon-reviews-scraper-with-advanced-filters.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/delicious_zebu/amazon-reviews-scraper-with-advanced-filters.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).