Trustpilot Reviews Scraper - $0.40/1K + Fake Review Signals

Turn Trustpilot pages into review, reply, sentiment, topic, risk, company, and transparency datasets.

Scrape Trustpilot reviews, replies, ratings, verification details, sentiment, topics, company profiles, AI summaries, transparency metrics, and search results. Clean datasets for reputation analysis, support triage, and competitor tracking.

All examples below use fictional DEMO-* identifiers, reserved .test domains, and masked contact details. They do not represent real people, listings, products, or companies.

🚀 What this Actor does

• Flexible collection: AUTO, REVIEWS, and SEARCH.
• Structured output: clean JSON records organized into reviews, review_intelligence, company_replies, errors views.
• Production-ready: concurrency, retries, result limits, and source-aware diagnostics are exposed through the Actor input.
• Easy automation: run from the Apify Console, API, schedules, webhooks, Make, Zapier, or any HTTP client.

🎛️ Modes and workflows

Mode or workflow	What it does
AUTO	Detect company, review, or search inputs automatically.
REVIEWS	Collect company profiles, reviews, replies, sentiment, topics, and risk signals.
SEARCH	Discover matching Trustpilot companies from keyword queries.

🏢 Company intelligence

With includeCompanyProfile=true, every review can include the public company data available on its Trustpilot page:

• lifetime and last-12-month review counts;
• 1–5 star distribution and review-language distribution;
• category IDs, hierarchy, ranks, and primary category;
• description, website, contacts, profile country, and contact country;
• claimed, subscription, paid-feature, review-collection, and AI-response flags;
• reply behavior and company verification flags;
• Trustpilot's public AI review summary and topic summaries, when available.

Set includeTransparency=true to add public collection-method counts, reports, removals, reactivations, reply metrics, and the transparency-period star distribution. These fields are conditional because not every Trustpilot profile publishes every block.

🔬 Review authenticity

Turn on analyzeAuthenticity and every company gains an authenticity block that measures how a rating was built, not just what it is. It reads the reviews the run already collected, so it costs no extra requests:

Metric	What it means
oneReviewAccountsPct	Share of reviews from accounts with no other review
unverifiedPct	Share Trustpilot did not verify
middleRatingsPct	Share of 2-4 star reviews — healthy profiles always keep a middle
backdatedMedianDays	Median gap between the experience and the publication date
countryMismatchPct	Reviewers based outside the company's country
duplicatePhrasePct	Reviews repeating near-identical wording
reviewBursts	Days whose volume dwarfed the company's own daily median

The block also carries score (0-100, higher is cleaner), the signals that fired with plain-English explanations, and confidence based on how many reviews were sampled.

The same switch adds a responsiveness block — responseRatePct, negativeResponseRatePct and medianResponseHours — so you can see whether a company actually answers its critics.

Read these as statistical patterns, not proof. A burst can be a marketing campaign, and one-review accounts are normal for a small shop. Below 50 collected reviews no score is issued at all, and every block reports the sample it was measured on, including coveragePct against the company's full review count.

💡 Common use cases

• Reputation monitoring
• Support and risk triage
• Competitor sentiment and topic analysis
• Due diligence on a marketplace seller or an acquisition target
• Proving to a client that a competitor's rating does not add up

📥 Input schema

Configure the Actor in the Input tab or send the same JSON through the API. Fields not needed for your workflow can be omitted.

Field	Type	Description	Default
mode	string	AUTO chooses the right flow. REVIEWS scrapes review pages for known companies. SEARCH discovers companies from Trustpilot search and can also scrape their reviews. Allowed: AUTO, REVIEWS, SEARCH.	AUTO
companyDomains	array<string>	Business domains to scrape on Trustpilot, for example trustpilot.com, amazon.com, apple.com, or shopify.com.	[]
startUrls	array	Trustpilot review URLs or search URLs. Use this when you already have exact Trustpilot links.	[]
businessUnitIds	array<string>	Optional Trustpilot business unit IDs. Use plain IDs or id:domain pairs.	[]
searchQueries	array<string>	Company names or keywords to search on Trustpilot.	[]
maxResults	integer	Safety cap for total items in the default dataset. Increase this when scraping many companies or many reviews per company.	100
maxReviewsPerCompany	integer	Maximum number of reviews to collect for each company.	25
maxPagesPerCompany	integer	Pagination safety limit for each company. Increase it when you need more reviews than one page can contain.	3
sort	string	Trustpilot review sort order. Allowed: recency, relevance.	recency
stars	array<string>	Trustpilot star ratings to keep. Leave empty for all ratings. Example: 1 and 2 for negative reviews.	[]
verified	string	Filter reviews by Trustpilot verification state when supported. Allowed: ``, true, false.	``
scrapeReviews	boolean	Collect individual review rows. Turn this off for a fast company-only search or company profile output.	true
includeCompanyProfile	boolean	Attach company profile, category hierarchy, rating and language distributions, AI summary, subscription flags, and reply behavior to every review where available.	true
includeTransparency	boolean	Add public review-collection, reporting, removal, reactivation, reply, and 12-month star metrics when available.	false
rawOutput	boolean	Keep empty optional fields and selected parser fields. Usually leave this off for cleaner tables.	false
analyzeAuthenticity	boolean	Add an authenticity block per company: one-review accounts, unverified share, missing middle ratings, backdated reviews, reviewer-country mismatch, near-duplicate wording and volume spikes, plus reply rate and median response time. Needs 50+ reviews per company for a score.	false
htmlReport	boolean	Build a shareable HTML report (TrustScore, sentiment, rating distribution, top topics, top complaints vs praises, plus a brand comparison for multiple companies) and save it to the key-value store as 'report'.	true
maxConcurrency	integer	Maximum parallel HTTP fetches. Keep the default for broad runs; increase after a successful small test.	4
maxRetries	integer	Retry budget for temporary HTTP errors and parse misses.	5

▶️ Example input

{
  "mode": "REVIEWS",
  "companyDomains": [
    "demo-company.test"
  ],
  "maxReviewsPerCompany": 100,
  "includeCompanyProfile": true,
  "includeTransparency": true
}

📦 Output schema

Each successful item is written to the default dataset. Select a dataset view in the Apify Console or export the full dataset as JSON, CSV, Excel, XML, or RSS.

reviews — Reviews

One record or grouped payload for reviews, depending on the source schema.

Fields: companyName, rating, title, text, sentiment, issueSeverity, isVerified, verificationLevel, verificationSource, reviewSourceName, consumerIsVerified, hasCompanyReply, datePublished, companyDomain, reviewUrl, type, scrapedAt

review_intelligence — Review intelligence

Derived sentiment, topics, severity, and risk signals.

Fields: companyName, companyDomain, rating, sentiment, sentimentScore, topics, riskSignals, issueSeverity, companyPrimaryCategory, companyReviewCountLast12Months, companyHasSubscription, companyIsUsingAIResponses, companyAiSummary, companyAiTopicNames, reviewLength, reviewUrl

company_replies — Replies

Reviews joined with public company replies.

Fields: companyName, companyDomain, rating, title, hasCompanyReply, companyReplyText, companyReplyDate, datePublished, reviewUrl

errors — Errors

Recoverable failures and source diagnostics.

Fields: type, errorType, companyDomain, sourceUrl, page, error, detectedAt

📤 Example output

{
  "companyName": "Demo Company",
  "rating": 2,
  "title": "Example service review",
  "text": "Fictional review text used only for documentation.",
  "sentiment": "negative",
  "issueSeverity": "medium",
  "isVerified": true,
  "verificationLevel": "invited",
  "verificationSource": "invitation",
  "hasCompanyReply": false,
  "companyDomain": "demo-company.test",
  "companyReviewCountLast12Months": 1200,
  "companyPrimaryCategory": "Software Company",
  "companyHasSubscription": true,
  "companyAiTopicNames": ["Product", "Customer service"],
  "companyTransparencyAvailable": true,
  "reviewUrl": "https://www.trustpilot.com/reviews/DEMO-REVIEW-01",
  "type": "review"
}

Missing source values are returned as null, empty arrays, or documented availability/status fields; the Actor does not invent unavailable source data.

🔌 API example

Replace the placeholder with an Apify token and send the same input used in the Console:

curl -X POST "https://api.apify.com/v2/acts/trakk~trustpilot-review-intelligence-scraper/runs?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"mode": "REVIEWS", "companyDomains": ["demo-company.test"], "maxReviewsPerCompany": 100, "includeCompanyProfile": true, "includeTransparency": true}'

For synchronous integrations, use the run-sync-get-dataset-items API endpoint. For larger jobs, start an asynchronous run and consume its default dataset when the run succeeds.

🧩 Automation and exports

• Schedule recurring runs from the Apify Console.
• Trigger downstream systems with webhooks when a run succeeds or fails.
• Export dataset views to JSON, CSV, Excel, XML, or RSS, or access items through the Apify API.

❓ FAQ

Do I need a login or browser session?

No Trustpilot login is required for the public company, review, and transparency fields described here.

Why can some fields be empty?

Source pages vary by region, content type, privacy settings, and availability. Optional enrichment also depends on the selected mode. Empty values are preserved honestly instead of being guessed.

How should I run this at scale?

Start with a small representative input, inspect the dataset and cost, then raise item limits and concurrency gradually. Use schedules and webhooks for recurring collection.

Is the example data real?

No. Every example in this README is intentionally fictional and uses demo identifiers, reserved domains, or masked contact values.