Amazon Reviews Scraper

Scrape product reviews from Amazon with structured data output. Extract star ratings, review titles, body text, verified purchase status, helpful votes, reviewer info, images, and more.

Features

• Multi-domain support: Amazon US, UK, DE, FR, IT, ES, CA, AU, JP, IN
• Flexible input: Product URLs or ASIN codes
• Review filtering: By star rating (1-5, positive, critical)
• Sorting options: Most recent, most helpful, top reviews
• Sentiment analysis: Automatic positive/neutral/negative classification
• Summary statistics: Rating distribution, word frequency, country breakdown
• Pagination: Automatically fetches multiple pages up to your limit
• Anti-detection: Rotating user agents, random delays, retry logic
• Proxy support: Use Apify proxies for large-scale scraping

Input

Parameter	Type	Default	Description
productUrls	array	[]	Amazon product URLs
asins	array	[]	Amazon ASIN codes (10 characters)
maxReviews	integer	100	Max reviews per product
sortBy	string	"recent"	Sort order: recent, helpful, top_reviews
starFilter	string	"all"	Filter: all, 5_star, 4_star, 3_star, 2_star, 1_star, positive, critical
amazonDomain	string	"us"	Domain for ASIN lookups: us, uk, de, fr, it, es, ca, au, jp, in
generateSummary	boolean	true	Include summary statistics
proxyConfiguration	object	null	Proxy settings

Output

Each review includes:

{
    "product_title": "Product Name",
    "asin": "B08N5WRWNW",
    "review_id": "R1ABC2DEF3",
    "reviewer_name": "John D.",
    "rating": 5.0,
    "title": "Amazing product!",
    "text": "Full review text here...",
    "date": "2024-01-15",
    "country": "United States",
    "verified_purchase": true,
    "helpful_votes": 42,
    "images": ["https://..."],
    "sentiment": "positive",
    "review_number": 1
}

Summary statistics (when enabled):

{
    "_type": "summary",
    "product_title": "Product Name",
    "asin": "B08N5WRWNW",
    "total_reviews_scraped": 100,
    "average_rating_scraped": 4.32,
    "rating_distribution": {"1_star": 5, "2_star": 3, ...},
    "sentiment_distribution": {"positive": 75, "neutral": 12, "negative": 13},
    "verified_purchase_percent": 85.0,
    "top_words": [{"word": "quality", "total_count": 45, ...}],
    "country_distribution": {"United States": 78, "Canada": 12, ...}
}

Use Cases

• Market research: Analyze customer sentiment for competitive products
• Product development: Identify common complaints and feature requests
• Brand monitoring: Track review trends over time
• E-commerce analytics: Compare ratings across product categories
• Content generation: Find authentic customer quotes and testimonials
• Price tracking: Combine with product data for pricing analysis

Tips

• Use proxy rotation for scraping more than ~50 reviews to avoid detection
• Start with a small maxReviews (20-50) to test before scaling up
• Use starFilter: "critical" to focus on negative feedback analysis
• Sort by helpful to get the most informative reviews first