Trustpilot Reviews Scraper — Ratings, Text, Author & Date

Export every Trustpilot review for any company as clean, structured data: star rating, title, full text, author, verified status, language, date, and company replies. The cheapest Trustpilot scraper on the market.

Monitor your reputation, analyze competitor reviews, or build a sentiment dataset — by domain, in bulk, no proxies or scraping to maintain.

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What you get per review

• ⭐ Star rating — 1–5 score.
• 📝 Title & full text — the complete review.
• 👤 Author — reviewer name, profile link, country, and total reviews written.
• ✅ Verified status — genuine-purchase flag.
• 🌐 Language & date — for filtering and trend analysis.
• 💬 Company reply — whether the business responded.

Company summary (per domain)

A summary record per company: name, location, overall TrustScore, total review count, and a star distribution (1–5) computed from the fetched reviews.

Filters

• Minimum rating — keep only reviews at or above N stars.
• Verified only — drop unverified reviews.
• Language — keep one ISO language (e.g. en).
• Date range — dateFrom / dateTo (YYYY-MM-DD).

Perfect for

• Reputation monitoring — track your Trustpilot reviews automatically.
• Competitor analysis — see what customers say about rivals.
• Sentiment analysis & AI — build training/analysis datasets at scale.
• Voice-of-customer research — surface common complaints and praise.
• AI agents — feed structured review data into automated pipelines and MCP tools.

How to use it

1. Enter one or more company domains (e.g. nike.com).
2. Set how many reviews per company and the sort order.
3. Run it — export JSON/CSV or pull via the API.

Example input

{ "domains": ["nike.com"], "depth": 100, "sortBy": "recency", "minRating": 4, "verifiedOnly": true, "language": "en", "dateFrom": "2026-01-01" }

Example output — company summary

{
  "record_type": "company_summary",
  "company_domain": "nike.com",
  "company_name": "Nike",
  "overall_rating": 1.6,
  "total_reviews": 12635,
  "fetched_reviews": 100,
  "rating_distribution": { "1": 72, "2": 8, "3": 5, "4": 6, "5": 9 }
}

Example output — review

{
  "record_type": "review",
  "company_domain": "nike.com",
  "rating": 5,
  "title": "Great experience",
  "review_text": "Perfect quality, perfect delivery…",
  "author": "ginny Maat",
  "reviewer_country": "US",
  "reviewer_reviews_count": 3,
  "verified": true,
  "language": "en",
  "timestamp": "2026-05-30 17:37:46 +00:00",
  "has_response": false
}

Pricing

Pay per review returned, plus a small per-company summary — no monthly fee, no minimum. Among the cheapest review scrapers anywhere.

FAQ

How do I find a company's domain? Use the domain shown on its Trustpilot page (e.g. nike.com).

How many reviews can I pull? Up to 1,000 per company per run.

Do I need proxies? No — everything is handled.

Good for AI agents? Yes — clean JSON, ideal for MCP servers, n8n, Make, and LLM agents.

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Tags: trustpilot scraper, trustpilot reviews, review scraper, reputation monitoring, sentiment analysis, customer reviews, voice of customer, reviews api, brand monitoring.