Trustpilot Reviews Scraper — Full Review Coverage

What does Trustpilot Reviews Scraper do?

Trustpilot Reviews Scraper extracts structured review data from trustpilot.com — the world's largest open review platform with over 300 million reviews across 1 million+ businesses. Extract reviews, company profiles, transparency reports, and competitive intelligence in seconds.

No login required. No credentials needed. Just enter a company domain and get structured data.

Features

• ⭐ Review extraction — rating, title, full text, dates, language, likes, verification status, and reviewer profile
• 🏢 Company profiles — trust score, star breakdown, categories, website, city, country, and contact data (email + phone)
• 📊 Transparency reports — reply rates, organic vs. invited review share, flagged review counts, and monthly distributions
• 🔍 14+ filters — star rating, language, date range, topics, verified only, with reply, reviewer country, and keyword search
• 🌍 Multi-language — filter by language or extract the full language distribution for any company
• 📈 Incremental monitoring — only return new or changed reviews on recurring runs, saving time and cost
• 💬 Company replies — reply text, reply date, response rate, and average response time
• 👤 Reviewer profiles — name, country, total reviews, verification status, and reviews on same domain
• 🤖 AI-ready output — compact mode (16 fields), custom field selection, and descriptionMaxLength for token-efficient payloads
• 🔗 4 modes — Reviews, Company Info, Search Companies, and Browse Categories in a single actor
• 🔄 Similar companies — discover competitors based on Trustpilot's own similarity data
• 🧠 AI summary — extract Trustpilot's AI-generated review summary when available

What Trustpilot review data can you extract?

Each review record includes up to 52 fields covering the review itself, the reviewer, the company, and enrichment data. Every field is always present — unavailable data points are returned as null, never omitted.

Review data: reviewId, reviewUrl, rating, title, text, language, reviewSource (Organic/Invitation), likes, publishedDate, experiencedDate, updatedDate, isVerified, verificationLevel

Reviewer data: authorId, reviewerName, reviewerCountry, reviewerTotalReviews, reviewerIsVerified, reviewerImageUrl, reviewsOnSameDomain

Company reply: replyText, replyDate, replyUpdatedDate

Company profile (when includeCompanyInfo is enabled): companyTrustScore, companyStars, companyTotalReviews, companyWebsite, companyIsClaimed, companyCategories, companyCity, companyCountry, companyContactEmail, companyContactPhone, companyResponseRate, companyResponseTime

Star breakdown: companyRating1Star through companyRating5Star

Enrichment: languageDistribution, similarCompanies, aiSummary, productReviews

Input

Enter a company domain, company name, or a direct Trustpilot URL to get started. The actor resolves company names automatically.

Key parameters

• mode — What to scrape: reviews (default), searchCompanies, categories, or companyInfo
• companyDomain — Company domain as used on Trustpilot, e.g. booking.com or wise.com
• companyName — Company name to search for (resolved automatically to the Trustpilot domain slug)
• startUrls — Direct Trustpilot review page URLs
• maxResults — Maximum reviews to return per company. 0 = unlimited (default: 200)
• stars — Filter by star rating, e.g. [1, 2] for negative reviews only
• languages — Filter by review language ISO codes, e.g. ["en", "de"]
• date — Time period: last30days, last3months, last6months, last12months, or older
• lookbackDays — Rolling window: only reviews from the last N days (1-365)
• topics — Topic filter: customer_service, delivery_service, price, product, and 15 more
• verified — Only verified reviews
• withReplies — Only reviews with a company reply
• search — Keyword search within review text
• countryOfReviewer — Filter by reviewer country (ISO code)
• includeCompanyInfo — Include company metadata, trust score, contact, and star breakdown (default: true)
• includeTransparency — Fetch the Trustpilot transparency report per company
• compact — Return 16 core fields only, ideal for AI agents and LLM pipelines
• fields — Return only these specific fields, e.g. ["reviewId", "rating", "text"]. Overrides compact mode
• incrementalMode — Only return new and changed reviews compared to the previous run
• descriptionMaxLength — Truncate review text to N characters (useful for token budgets)

Input example

{
  "companyDomain": "booking.com",
  "maxResults": 50,
  "includeCompanyInfo": true
}

Output

Each run produces a dataset of structured review records. Download as JSON, CSV, or Excel from the Dataset tab, or retrieve results programmatically through the Apify API.

Example review record

{
  "type": "review",
  "reviewId": "68362b480787ca52990267fc",
  "reviewUrl": "https://www.trustpilot.com/reviews/68362b480787ca52990267fc",
  "companyDomain": "booking.com",
  "companyName": "Booking.com",
  "rating": 1,
  "title": "Terrible customer service",
  "text": "Called support after my accommodation was cancelled. They hung up without offering an alternative.",
  "language": "en",
  "reviewSource": "Organic",
  "likes": 0,
  "publishedDate": "2025-05-27T23:14:48.000Z",
  "experiencedDate": "2025-05-27T00:00:00.000Z",
  "updatedDate": null,
  "isVerified": false,
  "verificationLevel": "not-verified",
  "authorId": "5f05eec809a036394b2d2f7c",
  "reviewerName": "Ronald",
  "reviewerCountry": "NL",
  "reviewerTotalReviews": 3,
  "reviewerIsVerified": false,
  "replyText": null,
  "replyDate": null,
  "companyTrustScore": 1.8,
  "companyStars": 2,
  "companyTotalReviews": 107769,
  "companyWebsite": "https://www.booking.com",
  "companyIsClaimed": true,
  "companyCategories": ["Travel Aggregator", "Hotel"],
  "companyCity": "Amsterdam",
  "companyCountry": "NL",
  "companyContactEmail": "customer.service@booking.com",
  "companyContactPhone": "+31 20 712 5600",
  "companyResponseRate": 0,
  "companyResponseTime": "0 days",
  "companyRating1Star": 75306,
  "companyRating2Star": 3724,
  "companyRating3Star": 2399,
  "companyRating4Star": 4713,
  "companyRating5Star": 21627,
  "portalUrl": "https://www.trustpilot.com/review/booking.com",
  "scrapedAt": "2026-04-05T13:44:12.000Z",
  "source": "trustpilot.com"
}

In compact mode, output is reduced to 16 core fields: reviewId, reviewUrl, companyDomain, companyName, rating, title, text, language, publishedDate, experiencedDate, isVerified, reviewerName, reviewerCountry, replyText, companyTrustScore, and changeType.

With the fields parameter, you pick exactly which fields you need — nothing more, nothing less.

How to scrape Trustpilot reviews

1. Go to Trustpilot Reviews Scraper in Apify Console.
2. Enter a company domain (e.g. booking.com) or company name.
3. Set maxResults to control how many reviews you need.
4. Add filters: star rating, language, date range, topics, or keyword search.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

For large-scale extraction, set maxResults to 0 (unlimited) and let the actor paginate through all available reviews automatically.

Use Trustpilot Reviews Scraper with AI agents and MCP

This actor is designed to work as a tool for AI agents through Apify's MCP Server. Your AI assistant can search for companies, extract reviews, and analyze sentiment — all within a single conversation.

Supported AI clients

Connect from Claude Desktop, Cursor, VS Code (GitHub Copilot), Claude.ai, or any MCP-compatible client. One-line setup:

{
  "mcpServers": {
    "apify": { "url": "https://mcp.apify.com" }
  }
}

Why this actor is optimized for AI workflows

• Compact mode — 16 core fields instead of 52, keeping LLM context usage minimal
• Custom field selection — use the fields parameter to return only the exact fields your pipeline needs
• descriptionMaxLength — truncate review text to fit token budgets
• Stable JSON schema — every field is always present (null when unavailable), so agents can parse results without defensive error handling
• 4 modes in one actor — search companies, pull reviews, fetch profiles, and get transparency reports without switching tools
• Incremental mode — schedule recurring runs that only return new or changed reviews, ideal for agent-driven monitoring and alerting

Example agent prompts

• "Pull the last 50 reviews for booking.com and summarize the main complaints"
• "Compare trust scores and response rates for the top 5 car insurance companies on Trustpilot"
• "Monitor reviews for my company and alert me when a 1-star review mentions refund"
• "Find all verified negative reviews in German from the last 30 days"

Use cases

• Brand reputation monitoring — track your company's Trustpilot reviews on a schedule and get alerted to new negative reviews.
• Competitive intelligence — compare trust scores, star breakdowns, response rates, and review volumes across competitors.
• Sentiment analysis — extract review text at scale and feed it into NLP or LLM pipelines for topic detection and sentiment scoring.
• Market research — use Search Companies mode to discover businesses in a category and rank them by trust score.
• Lead generation — extract company contact data (email, phone, website) from Trustpilot company profiles.
• Review transparency audits — pull transparency reports to analyze the mix of organic vs. invited reviews, flagged review counts, and response behavior.
• Multi-language analysis — use language distribution data to understand which markets are reviewing a company.
• Customer experience benchmarking — export star breakdowns and response times to compare service quality across an industry.
• AI-powered alerting — combine incremental mode with an AI agent to automatically classify and route new reviews.
• Data enrichment — add Trustpilot trust scores and review counts to your existing business datasets.

How much does it cost to scrape Trustpilot?

Trustpilot Reviews Scraper is free to use. There is no start fee and no per-result charge.

You only pay for the Apify platform resources your run consumes (compute and memory). A typical run extracting 1,000 reviews uses approximately 256 MB of memory and completes in under 10 seconds.

FAQ

How many reviews can I extract from Trustpilot?

There is no hard limit on the number of reviews you can extract. Set maxResults to 0 for unlimited extraction. The actor paginates through all available reviews automatically and can extract thousands of reviews per company.

Does Trustpilot Reviews Scraper support scheduled monitoring?

Yes. Enable incrementalMode and set a stateKey to only receive new or changed reviews on subsequent runs. This is ideal for daily or weekly monitoring where you want to track changes without re-processing the full dataset. Incremental runs are fast because they skip unchanged reviews.

What are the 4 modes?

• Reviews (default) — extract reviews for one or more companies
• Company Info — fetch company profiles with trust scores, contact data, and star breakdowns
• Search Companies — find companies by keyword (e.g. "car insurance") and country
• Categories — browse a Trustpilot category page and extract all listed companies

How does the fields parameter work?

Three levels of output control:

Input	Result
Nothing set	All 52 fields
compact: true	16-field preset: reviewId, reviewUrl, companyDomain, companyName, rating, title, text, language, publishedDate, experiencedDate, isVerified, reviewerName, reviewerCountry, replyText, companyTrustScore, changeType
fields: ["reviewId", "rating", "text"]	Exactly those 3 fields — nothing more

If both compact and fields are set, fields wins (full override).

Unrecognized field names are silently ignored. If you pass fields: ["reviewId", "nonExistentField"], you get only reviewId. No error is thrown — this makes it safe to use a superset of field names across different actors.

Example: all fields (default)

{ "companyDomain": "booking.com", "maxResults": 50 }

Returns 52 fields per review including company info, star breakdown, and enrichment data.

Example: compact mode (AI/MCP preset)

{ "companyDomain": "booking.com", "maxResults": 50, "compact": true }

Returns 16 fields: identity, rating, text, dates, reviewer, and trust score. Designed for LLM context efficiency.

Example: custom field selection

{ "companyDomain": "booking.com", "maxResults": 50, "fields": ["reviewId", "rating", "title", "text", "publishedDate", "reviewerCountry"] }

Returns exactly those 6 fields per review — ideal when you know precisely what your pipeline needs.

Can I integrate Trustpilot Reviews Scraper with other apps?

Yes. The actor works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Trustpilot Reviews Scraper with the Apify API?

Yes. Start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript and Python.

Is it legal to scrape Trustpilot?

This actor extracts publicly available data from trustpilot.com. Web scraping of public information is generally considered legal, but you should review the target site's terms of service and ensure your use case complies with applicable laws, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console.