⭐ Trustpilot Reviews Scraper — Ratings & Replies avatar

⭐ Trustpilot Reviews Scraper — Ratings & Replies

Pricing

$5.00 / 1,000 reviews

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⭐ Trustpilot Reviews Scraper — Ratings & Replies

⭐ Trustpilot Reviews Scraper — Ratings & Replies

Scrape Trustpilot business reviews by domain: reviewer, star rating, title, text, date, company reply, trust score & total count. No login, beats the AWS WAF via residential proxies. Works in Claude, ChatGPT & any MCP agent.

Pricing

$5.00 / 1,000 reviews

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0.0

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Developer

The Mine Works

The Mine Works

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1

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4 hours ago

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⭐ Trustpilot Reviews Scraper — Ratings, Replies & TrustScore (No Login)

What is the Trustpilot Reviews Scraper?

The Trustpilot Reviews Scraper pulls the reviews and ratings for any business on Trustpilot into a clean dataset. Give it a company domain — like amazon.com — and it returns every review it can reach: reviewer name, star rating, review title, full text, publish date, the company's official reply, review URL and review ID — plus a business-level record with the overall TrustScore and total review count. Output is JSON, CSV or Excel.

It is built for anyone who needs Trustpilot review data at scale without copy-pasting:

  • Monitor your brand reputation and catch new negative reviews fast.
  • Analyze competitor sentiment and benchmark satisfaction over time.
  • Mine reviews for product feedback, feature requests and complaints.
  • Build sentiment / NLP training datasets from real review text.
  • Feed dashboards and alerts with fresh, structured review data.

No login, no API key — a real browser that clears the WAF

Trustpilot fronts every page with an AWS WAF "Verifying your connection" JavaScript challenge that TLS-fingerprints plain HTTP requests and blocks them, so simple scrapers get nothing. This actor uses a real Chromium browser (Crawlee's PlaywrightCrawler with a full fingerprint stack) routed through residential proxies. The browser actually runs the WAF challenge, the session clears, the page renders, and the scraper reads the reviews straight out of Trustpilot's server-rendered __NEXT_DATA__ JSON island. No account, no cookies, no API key, and no third-party unblocker — it is Apify-native end to end.

What data does the Trustpilot scraper extract?

Each review is a flat record. Real fields:

🔑 FieldDescription
🌐 business_domainCompany domain scraped (e.g. amazon.com)
👤 reviewer_nameDisplay name of the reviewer
ratingStar rating (1–5)
📝 titleReview headline / title
💬 textFull review body text
📅 review_dateISO-8601 publish date
↩️ reply_textBusiness reply text (if present)
🔗 review_urlDirect URL to the review
🆔 review_idTrustpilot review ID
🕒 scraped_atISO-8601 timestamp of the scrape

The run also emits one business record per domain with business_name, overall_rating (TrustScore), total_reviews and the Trustpilot URL.

How to scrape Trustpilot reviews in 5 steps

  1. Open the actor and enter a Company domain (e.g. booking.com). A full Trustpilot URL works too — it is normalised to the bare host.
  2. Set Max reviews — how many reviews to collect across all pages.
  3. (Optional) Add a Star rating filter (e.g. ["1","2"] for negative reviews only).
  4. Leave the residential proxy on (required — Trustpilot's WAF blocks datacenter IPs).
  5. Click Start and download the results as JSON, CSV or Excel from the Storage tab.

Example input

{
"companyDomain": "amazon.com",
"maxResults": 100,
"starsFilter": ["1", "2"],
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "US"
}
}

Example output

Each review record looks like this:

{
"business_domain": "amazon.com",
"reviewer_name": "Constance",
"rating": 2,
"title": "Delivery was late twice",
"text": "Ordered two items and both arrived days after the promised date...",
"review_date": "2026-02-01T16:57:28.000Z",
"reply_text": "We're sorry to hear about the delay — please reach out to support...",
"review_url": "https://www.trustpilot.com/reviews/697f69d898b1919e835668fe",
"review_id": "697f69d898b1919e835668fe",
"scraped_at": "2026-07-10T09:16:10.004Z"
}

Use cases

  • Reputation monitoring — schedule daily runs and alert on new 1–2 star reviews as they land.
  • Competitor benchmarking — compare TrustScore and review sentiment across rivals in one dataset.
  • Voice-of-customer analysis — extract recurring complaints, praise and feature requests from text.
  • Sentiment / NLP datasets — build labelled training data from real reviews and star ratings.
  • Support & CX triage — surface unanswered negative reviews (reply_text empty) for follow-up.
  • Market research — track how satisfaction moves over time for a brand or category.

FAQ

Do I need a Trustpilot account or API key?

No. The scraper reads publicly visible review pages with a real browser. There is no login, no cookie and no API key.

Why are residential proxies required?

Trustpilot's AWS WAF challenge blocks datacenter IPs. Residential proxies (the default) let the browser clear the challenge and render the page.

Can I get only negative or only positive reviews?

Yes. Use the Star rating filter — e.g. ["1","2"] for negative reviews or ["4","5"] for positive ones. Leave it empty to keep all ratings.

Does it include the company's replies and TrustScore?

Yes. Each review carries reply_text when the business has replied, and the run emits a business record with the overall TrustScore and total review count.

What does it cost?

Pricing is pay-per-event at $5 per 1,000 reviews ($0.005 each). Missing domains, blocked pages and failures are never charged, and the first 25 reviews are free for life.

Search for businesses first, then chain into reviews

Do not have a list of domains yet? Run the Trustpilot Business Search Scraper first: search a Trustpilot category or keyword, get back a list of businesses with their domain field, then feed those domains into this Reviews Scraper. Search once → pull reviews for every company you find. The two actors are built as a search → reviews pipeline on the shared domain key.

Use in Claude, ChatGPT & any MCP agent

This actor is an MCP (Model Context Protocol) tool, so AI assistants can call it directly. Point your MCP client at:

https://mcp.apify.com/?tools=themineworks/trustpilot-reviews

Then ask, e.g. "Get the latest 100 one-star Trustpilot reviews for booking.com."

You can also call it programmatically with the Apify client:

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('themineworks/trustpilot-reviews').call({
companyDomain: 'amazon.com',
maxResults: 100,
starsFilter: ['1', '2'],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

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