Trustpilot Company Review Scraper

What this Actor does

Extract company review data from public Trustpilot review pages (or any other public review listing page) as clean, structured JSON.

It processes user-provided public URLs, prioritizes JSON-LD / schema.org structured data (Review, AggregateRating, Organization, LocalBusiness), and can optionally use a conservative fallback that reads visible public review blocks. It normalizes useful fields, deduplicates rows, and saves structured records to the Apify dataset.

Why this Actor is useful

Brand, product, and CX teams pay for this kind of extraction because it replaces manual copy-pasting of reviews, creates repeatable review monitoring, feeds spreadsheets, dashboards, and sentiment pipelines, and turns scattered public review pages into a clean, API-ready dataset.

Who this is for

• Brand and reputation managers
• Customer experience (CX) and support teams
• Product and marketing analysts
• Competitive intelligence researchers
• Agencies monitoring client reputation
• Data teams building review datasets

Common use cases

• Track new reviews for your company or competitors
• Feed review text and ratings into a sentiment pipeline
• Monitor average rating and total review count over time
• Build recurring reputation-monitoring datasets
• Export reviews for analysis in spreadsheets or BI tools

Input

Field	Type	Description
startUrls	array (required)	Public Trustpilot or review listing pages to extract from. Use only pages you may access without login or bypassing access controls.
maxItems	integer	Maximum rows to save. Default 50, min 1, max 10000.
maxConcurrency	integer	Pages processed in parallel. Default 3, min 1, max 20.
extractionMode	string	structuredDataOnly or structuredDataWithFallback (default). The fallback safely reads visible public review blocks.
requestTimeoutSecs	integer	Maximum time per page. Default 30, min 5, max 180.
proxyConfiguration	object	Optional Apify proxy configuration where permitted by your source review.

Output

Field	Description
companyName	Name of the reviewed company or business.
companyDomain	Domain of the reviewed company when available.
companyRatingValue	Aggregate rating value for the company when published.
companyReviewCount	Total number of reviews reported for the company.
reviewTitle	Title or headline of the individual review.
reviewText	Body text of the review.
reviewRating	Star rating given in the review (typically 1-5).
reviewAuthor	Display name of the review author.
reviewDate	Date the review was published.
reviewUrl	Public URL of the review when available.
sourceUrl	URL where the data was extracted.
detectedAt	Timestamp when this Actor extracted the row.
extractionMethod	structured_data for schema data, or fallback_public_review_listing for visible public reviews.
confidenceScore	Heuristic confidence based on structured data availability and completeness.
missingFields	Required fields that were not available from the source page.

Sample input

{
  "startUrls": [
    {
      "url": "https://www.trustpilot.com/review/www.apify.com"
    }
  ],
  "maxItems": 25,
  "maxConcurrency": 3,
  "extractionMode": "structuredDataWithFallback",
  "requestTimeoutSecs": 30
}

Sample output

{
  "companyName": "Apify",
  "companyDomain": "apify.com",
  "companyRatingValue": 4.6,
  "companyReviewCount": 128,
  "reviewTitle": "Excellent web scraping platform",
  "reviewText": "The Actors are reliable and the support team is responsive.",
  "reviewRating": 5,
  "reviewAuthor": "Jane D.",
  "reviewDate": "2026-06-15",
  "reviewUrl": "https://www.trustpilot.com/reviews/abc123",
  "sourceUrl": "https://www.trustpilot.com/review/www.apify.com",
  "detectedAt": "2026-06-27T00:00:00.000Z",
  "extractionMethod": "structured_data",
  "confidenceScore": 0.95,
  "missingFields": []
}

Pricing

This Actor uses a pay-per-event model: $0.005 per review result saved to the dataset. You pay only for the structured review rows you receive, which makes recurring monitoring predictable and low-cost.

How to use

Run this Actor on Apify with public review page URLs, export the dataset as JSON, CSV, or Excel, or pull it through the Apify API. Connect the output to Google Sheets, Make, Zapier, a webhook, your CRM, or an internal dashboard. For monitoring, save the input as an Apify task and schedule recurring runs to catch new reviews.

Best practices

• Start with a small set of reviewed public review URLs.
• Prefer pages that expose schema.org / JSON-LD structured data.
• Use structuredDataOnly for highest precision; use structuredDataWithFallback for pages that only show visible review blocks.
• Keep maxConcurrency low for smaller sites.
• Review each source website's rules before scheduling recurring runs.

Compliance and responsible use

This Actor is for public data only. It must not be used to bypass logins, paywalls, CAPTCHAs, or security systems, to collect private or sensitive personal data, or to support spam or abuse. Reviews processed here should be publicly published review notices. You are responsible for following applicable laws and each source website's rules.

Limitations

• Output quality depends on the public structured data available on the source pages.
• Fallback extraction is intentionally conservative and only looks for visible public review block patterns. It does not claim universal site support.
• Dates and ratings are extracted as published; formats vary by site and are not reformatted or converted.
• Some fields may be empty when the source does not publish them; these appear in missingFields.
• The Actor does not claim support for any specific third-party review platform.
• Website markup and access policies can change.

Troubleshooting

• Empty output usually means the page has no public structured review data and no visible review-block patterns.
• Invalid URL errors mean one or more input URLs are malformed.
• Slow runs can usually be improved by lowering maxConcurrency.
• Missing fields are source-data limitations, not inferred values.

Changelog

• v0.1.0: Initial release with structured-data-first extraction, conservative public review-listing fallback, and confidence scoring.

Use Trustpilot Company Review Scraper with AI agents (MCP)

Give Claude, ChatGPT, Cursor, VS Code or any MCP client this Actor as a tool through the hosted Apify MCP server. The agent sees the input fields with descriptions and example values, runs the Actor, and reads the results.

MCP server URL (this Actor only):

https://mcp.apify.com/?tools=technicaldost/trustpilot-review-scraper

Claude Code:

$claude mcp add --transport http apify "https://mcp.apify.com/?tools=technicaldost/trustpilot-review-scraper" --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Cursor, VS Code, Claude Desktop and other clients (mcp.json or the client's MCP settings):

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=technicaldost/trustpilot-review-scraper",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Clients that support sign-in (such as Claude.ai connectors) can use the URL without a token and log in to Apify instead. Get your token in Apify Console → Settings → API & Integrations, or generate a ready config for your client at mcp.apify.com. In the agent the tool is named technicaldost--trustpilot-review-scraper; ask it, for example, to "run Trustpilot Company Review Scraper with {"startUrls": [{"url": "https://www.trustpilot.com/review/www.apify.com"}]}".

AI agents without an Apify account can also run and pay for this Actor per request with x402 agentic payments.

Run Trustpilot Company Review Scraper via API

Run the Actor and get its results in one call (replace YOUR_APIFY_TOKEN):

curl -X POST "https://api.apify.com/v2/acts/technicaldost~trustpilot-review-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "https://www.trustpilot.com/review/www.apify.com"}]}'

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("technicaldost/trustpilot-review-scraper").call(run_input={"startUrls": [{"url": "https://www.trustpilot.com/review/www.apify.com"}]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / TypeScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('technicaldost/trustpilot-review-scraper').call({"startUrls": [{"url": "https://www.trustpilot.com/review/www.apify.com"}]});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Long runs: start them with POST /v2/acts/technicaldost~trustpilot-review-scraper/runs and fetch the dataset when the run finishes, or receive a webhook.

Related Actors

• B2B SaaS Review Buyer Intent Monitor — Extract review-site complaints, alternatives, and buyer-intent signals for SaaS competitors
• Yelp Business & Review Scraper — Scrape Yelp business listings and reviews: name, category, address, phone, rating, review count and individual
• App Store Review Analyzer: Feature Roadmap — Collect public Apple App Store review feeds or import reviews, then group feature requests, usability complain
• App Store Review Scraper (Apple iOS) — Scrape Apple App Store reviews and app metadata: rating, title, text, author, version, plus average rating and

FAQ

Can I use Trustpilot Company Review Scraper with AI agents like Claude or ChatGPT?

Yes. Connect the Apify MCP server with ?tools=technicaldost/trustpilot-review-scraper (see above) and the agent can run the Actor and read its results on its own.

Can I call Trustpilot Company Review Scraper from my own code?

Yes. Use the REST API, or the official Python and JavaScript clients shown above. Results are available as JSON, CSV, Excel, XML or HTML.

How do I run it on a schedule?

Save your input as a task in Apify Console and add a schedule (for example, daily). Use webhooks or integrations to send each run's results onward.

Is it legal to use this Actor?

It works with publicly available data. Make sure your use complies with the source website's terms and with data protection laws such as GDPR, especially for personal data.

Something doesn't work or I need a feature. What should I do?

Open an issue in the Issues tab on this Actor's page with an example input, and we'll look into it.