Access structured, high-quality customer reviews and ratings data from the world's leading platforms — Amazon, Google Play, Trustpilot, App Store, and more — covering reviewers across the US, Europe, and Australia.
Get Reviews Data Browse Datasets
Customer reviews are one of the most valuable sources of unstructured consumer intelligence available online. Our reviews datasets give you ready-to-use, clean, structured data so you can focus on insights — not scraping.
Our source platforms operate internationally, so review data already spans multiple markets. Need a market-specific extract? We can build a custom scrape targeted at your region.
Amazon.com, Yelp, G2, Capterra, and App Store/Google Play reviews from US users — the deepest coverage in our catalog, with the largest review volumes and category breadth.
Trustpilot is UK/EU-founded with strong regional coverage, and Amazon's EU marketplaces (UK, DE, FR, ES, IT) contribute reviewer data. All datasets contain only public review text and metadata, keeping them usable for GDPR-conscious projects.
Global platforms like Amazon, Google Play, and the App Store include Australian reviewers today. For an AU-specific site (e.g. ProductReview.com.au), we can scope a custom scraper on request.
Platform-specific datasets with consistent structure and high coverage
Millions of product reviews from Amazon including ratings, verified purchase status, helpful votes, reviewer profiles, and review dates across all major categories.
App store reviews from Google Play including app ratings, user reviews, developer replies, thumbs up counts, and review timestamps for any app.
Reviews and ratings from Apple's App Store with review text, star ratings, app version, device type, and user display names.
Business reviews from Trustpilot including company reviews, TrustScore, review count, categories, verified reviews, and business replies — strong UK/EU coverage.
In-depth reviews for electronics and tech products from major retailers — laptops, phones, cameras, audio equipment, and smart home devices.
Product reviews from beauty platforms and retailers including Sephora, Ulta, and major brands — with skin type, age range, and usage details.
Hospitality reviews from travel platforms covering hotels, resorts, and vacation rentals with location, price tier, amenities ratings, and traveler type.
Recipe ratings and reviews from major food sites including ingredients used, cooking difficulty, dietary tags, and user substitutions.
Most review scrapes hand you raw HTML or loose text. CrawlFeeds delivers machine-ready structured data — every field typed and normalised so you can load it directly into your app or model without preprocessing.
Every review record carries the rating, full text, and verification status as typed fields — no regex required to pull a star count out of markup.
| Field | Type | Example |
|---|---|---|
rating | Integer (1-5) | 4 |
review_title | String | "Great value for money" |
review_body | Text | Full review text |
verified_purchase | Boolean | true |
helpful_votes | Integer | 12 |
// JSON — review record example
{
"review_id": "R2X8K...",
"rating": 4,
"review_title": "Great value for money",
"review_body": "Works exactly as described...",
"verified_purchase": true,
"helpful_votes": 12,
"review_date": "2026-02-14",
"reviewer_name": "J. Carter",
"language": "en"
}
Reviews are linked back to the product or business they belong to, with the source platform and category attached — so you can segment by market or vertical without a join against another dataset.
// JSON — product & platform context
{
"platform_source": "amazon.com",
"product_id": "B0CX...",
"product_name": "Wireless Headphones",
"category": "Electronics",
"seller_response": null,
"sentiment_score": 0.82
}
Train NLP models on millions of real consumer reviews to classify sentiment, detect topics, and extract opinions at scale.
Monitor competitor product ratings, review volume, and common complaints to benchmark your product against alternatives.
Identify unmet customer needs, common pain points, and feature requests from authentic review data before building.
Use real-world review text as fine-tuning data for language models, recommendation systems, and review summarization tools.
Track brand mentions, rating trends, and customer satisfaction metrics over time across multiple platforms and regions.
Build classifiers to identify suspicious review patterns, review bombing, and inauthentic reviewer behavior.
Compare rating patterns and common complaints between US, European, and Australian customers before launching in a new market.
Beyond the datasets on this page, our Data Catalog lets you filter and download over 150M+ reviews spanning hotels, apps, and products — from Booking.com and TripAdvisor to Google Play and major e-commerce marketplaces. Filter by site or category and download exactly the slice you need.
Ready-to-download datasets available now
Get clean, structured customer reviews data from Amazon, Trustpilot, Google Play, and more — covering US, European, and Australian markets. Start your sentiment analysis, competitive monitoring, or AI training project today.
Get a Custom Quote Browse Datasets