Is it legal to scrape Trustpilot?

Scraping publicly available reviews is generally legal for internal research and analysis. However, you must comply with GDPR when handling personal information like reviewer names, and you should avoid reselling the data in a way that violates Trustpilot's copyright or Terms of Service.

Does Trustpilot have an official API?

Yes, Trustpilot offers an official API, but it is primarily designed for businesses to manage their own reviews. For researchers or those wanting competitor data, the API is often restricted or requires a high-cost Enterprise subscription, making scraping a more accessible alternative.

How to avoid getting blocked by Trustpilot?

The key to avoiding blocks is using residential proxies and a tool that can solve Cloudflare Turnstile challenges. Additionally, you should rotate your browser's fingerprint and keep your request frequency low to avoid being flagged by their rate-limiting systems.

What format is the data extracted in?

Data is typically extracted in JSON, CSV, or Excel formats. JSON is highly recommended for Trustpilot data because it can easily store the nested relationships between reviewers, their ratings, and the business's responses.

How often should I scrape reviews?

For brand reputation monitoring, a daily scrape is ideal to catch and respond to new feedback quickly. For broader industry research or competitive analysis, a weekly or monthly update is usually sufficient to track long-term trends.

Which proxies work best for Trustpilot?

Residential proxies are by far the most effective because they provide IPs from real home internet connections. Data center proxies are often identified and blocked immediately by Trustpilot's security filters, leading to frequent Error 1015 messages.

Do I need to be logged in to scrape Trustpilot?

No, most review data is publicly visible without an account. It is actually safer to scrape without logging in, as it prevents Trustpilot from linking the scraping activity to a specific user profile and banning it.

Can I scrape reviews for specific industries?

Yes, Trustpilot organizes businesses into categories. You can scrape individual category pages (e.g., 'Bank' or 'Electronics Store') to gather a broad dataset of all competitors within a specific market sector.

What data fields can I extract?

You can extract almost everything visible on a profile, including the star rating, review title, body text, review date, reviewer's location, verification status, and the company's public response text and date.

How to Scrape Trustpilot: Extract Reviews & Ratings (2025)

Master Trustpilot scraping to monitor brand reputation. Learn to extract review text, star ratings, and TrustScores while bypassing Cloudflare blocks.

Start Scraping Free

trustpilot.comHard

Coverage:GlobalUnited StatesUnited KingdomGermanyFranceDenmarkAustralia

Available Data8 fields

TitleLocationDescriptionImagesSeller InfoPosting DateCategoriesAttributes

All Extractable Fields

Company NameTrustScoreTotal Review CountCategoryReviewer NameReviewer LocationStar RatingReview TitleReview Body TextReview DateVerification StatusBusiness Response TextBusiness Response DateReviewer Review CountReviewer Avatar URL

Technical Requirements

JavaScript Required

No Login

Has Pagination

Official API Available

Anti-Bot Protection Detected

CloudflareCloudflare TurnstileRate LimitingIP BlockingBrowser FingerprintingreCAPTCHA v3

View API Documentation

About Trustpilot

Learn what Trustpilot offers and what valuable data can be extracted from it.

The Global Standard for Customer Feedback

Trustpilot is a leading global review platform that serves as a bridge between businesses and consumers through genuine feedback. Founded in 2007 and headquartered in Denmark, it provides a transparent space for people to share their buying and service experiences with millions of companies across a vast range of industries. The platform has become one of the most trusted resources for online shoppers and a critical tool for businesses to manage their online presence.

High-Value Qualitative Data

The website hosts a wealth of data including company TrustScores, categorized business listings, and detailed, timestamped user reviews. Each review often includes a star rating, a specific title, detailed text description, and the reviewer's verification status. This structured and qualitative data provides a comprehensive view of customer satisfaction and brand performance over time.

Why Scrape Trustpilot?

Scraping Trustpilot allows businesses and researchers to aggregate thousands of individual experiences into structured datasets for large-scale analysis. This data is invaluable for monitoring brand reputation, performing sentiment analysis, tracking competitor performance, and identifying emerging market trends. By automating data collection, organizations can gain real-time insights into customer pain points and service excellence.

Why Scrape Trustpilot?

Discover the business value and use cases for extracting data from Trustpilot.

Real-Time Reputation Management

Monitor brand sentiment across global markets to identify and address negative feedback before it impacts conversion rates.

Competitor Weakness Discovery

Analyze competitor reviews to find recurring customer complaints and use those insights to improve your own product's value proposition.

High-Intent Lead Generation

Identify users who leave 1-star reviews for competitors as warm leads who are actively looking for a more reliable alternative.

Sentiment Analysis for NLP

Extract massive datasets of authentic human language to train machine learning models for industry-specific sentiment and emotion detection.

Market Trend Identification

Scrape category-wide data to observe shifts in consumer expectations and service standards across different industries in real-time.

Dynamic Social Proof Integration

Automate the collection of your latest 5-star reviews to display them as live social proof on your checkout and landing pages.

Scraping Challenges

Technical challenges you may encounter when scraping Trustpilot.

Advanced Anti-Bot Mitigation

Trustpilot uses Cloudflare and Turnstile challenges that frequently block standard automated requests and headless browsers.

Deep Pagination Restrictions

The platform often limits review visibility or triggers login walls for users attempting to navigate deep into search results beyond the initial pages.

Volatile Frontend Structure

Frequent updates to the website's React-based DOM structure and dynamic class names can break fragile, selector-based scraping scripts.

Strict Rate Limiting

Sending requests too rapidly from the same IP range will trigger Error 1015, resulting in temporary or permanent IP bans.

Scrape Trustpilot with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

Describe What You Need

Tell the AI what data you want to extract from Trustpilot. Just type it in plain language — no coding or selectors needed.

AI Extracts the Data

Our artificial intelligence navigates Trustpilot, handles dynamic content, and extracts exactly what you asked for.

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Native Turnstile Solving: Automatio handles complex Cloudflare challenges and Turnstile checks automatically, ensuring your scrapers don't get stuck on bot detection screens.

Point-and-Click Interface: Map out complex review data—including ratings, reviewer locations, and company replies—using a visual interface without writing any code.

Headless Browser Handling: It manages the full JavaScript rendering process, ensuring all dynamic review content and star ratings are fully loaded before extraction begins.

Smart Proxy Integration: Easily rotate through high-quality residential proxies within the tool to mimic real user behavior and stay hidden from anti-scraping systems.

Automated Update Schedules: Set your Trustpilot scrapers to run on a daily or weekly schedule to keep your data warehouses and sentiment dashboards updated automatically.

Start Scraping Free

No credit card requiredFree tier availableNo setup needed

No-Code Web Scrapers for Trustpilot

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Trustpilot. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

Install browser extension or sign up for the platform

Navigate to the target website and open the tool

Point-and-click to select data elements you want to extract

Configure CSS selectors for each data field

Set up pagination rules to scrape multiple pages

Handle CAPTCHAs (often requires manual solving)

Configure scheduling for automated runs

Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Using a custom session to simulate a real browser
def scrape_trustpilot(slug):
    url = f'https://www.trustpilot.com/review/{slug}'
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36'
    }
    
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        reviews = []
        # Selector for review containers (note: classes change often)
        for card in soup.select('section.styles_reviewCard__hc_vR'):
            data = {
                'title': card.select_one('h2').text if card.select_one('h2') else None,
                'rating': card.select_one('div.star-rating_starRating__Bdb_f img')['alt'] if card.select_one('img') else None,
                'text': card.select_one('p[data-service-review-text-typography]').text if card.select_one('p') else None
            }
            reviews.append(data)
        return reviews
    return None

# Example usage
print(scrape_trustpilot('www.apple.com'))

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

●Fastest execution (no browser overhead)
●Lowest resource consumption
●Easy to parallelize with asyncio
●Great for APIs and static pages

Limitations

●Cannot execute JavaScript
●Fails on SPAs and dynamic content
●May struggle with complex anti-bot systems

import asyncio
from playwright.async_api import async_playwright

async def run():
    async with async_playwright() as p:
        browser = await p.chromium.launch(headless=True)
        context = await browser.new_context(user_agent='Mozilla/5.0')
        page = await context.new_page()
        
        await page.goto('https://www.trustpilot.com/review/www.apple.com')
        
        # Wait for dynamic content to load
        await page.wait_for_selector('section.styles_reviewCard__hc_vR')
        
        reviews = await page.evaluate('''() => {
            return Array.from(document.querySelectorAll('section.styles_reviewCard__hc_vR')).map(card => ({
                author: card.querySelector('span.typography_appearance-default__S8ne3')?.innerText,
                rating: card.querySelector('.star-rating_starRating__Bdb_f img')?.alt,
                date: card.querySelector('time')?.getAttribute('datetime')
            }));
        }''')
        
        print(reviews)
        await browser.close()

asyncio.run(run())

When to Use

Use when content loads dynamically via JavaScript, or when you need to interact with the page (clicks, scrolls, form fills). Handles modern anti-bot detection better.

Advantages

●Executes JavaScript like a real browser
●Handles SPAs and dynamic content
●Better anti-bot evasion with stealth plugins
●Can take screenshots and PDFs

Limitations

●Slower than HTTP requests
●Higher memory/CPU usage
●More complex to set up

import scrapy

class TrustpilotSpider(scrapy.Spider):
    name = 'trustpilot'
    start_urls = ['https://www.trustpilot.com/review/www.apple.com']

    def parse(self, response):
        for review in response.css('section.styles_reviewCard__hc_vR'):
            yield {
                'author': review.css('span.typography_appearance-default__S8ne3::text').get(),
                'rating': review.css('div.star-rating_starRating__Bdb_f img::attr(alt)').get(),
                'title': review.css('h2.styles_reviewTitle__m9_V_::text').get(),
                'date': review.css('time::attr(datetime)').get()
            }

        next_page = response.css('a[name="pagination-button-next"]::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)

When to Use

Ideal for large-scale crawling projects that need to scrape thousands of pages. Built-in support for rate limiting, retries, and data pipelines.

Advantages

●Built for scale (millions of pages)
●Automatic request throttling
●Built-in data export pipelines
●Middleware system for proxies/headers

Limitations

●Steeper learning curve
●Overkill for small projects
●No native JavaScript rendering

const puppeteer = require('puppeteer-extra');
const StealthPlugin = require('puppeteer-extra-plugin-stealth');
puppeteer.use(StealthPlugin());

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  await page.goto('https://www.trustpilot.com/review/www.apple.com', { waitUntil: 'networkidle2' });

  const data = await page.evaluate(() => {
    const items = document.querySelectorAll('section.styles_reviewCard__hc_vR');
    return Array.from(items).map(item => ({
      title: item.querySelector('h2')?.innerText,
      body: item.querySelector('p')?.innerText
    }));
  });

  console.log(data);
  await browser.close();
})();

When to Use

Choose this if you're in a Node.js/JavaScript ecosystem or need tight integration with frontend tools. Similar capabilities to Playwright.

Advantages

●Native JavaScript/TypeScript support
●Chrome DevTools Protocol access
●Large ecosystem and community
●Good for JS-heavy projects

Limitations

●Chrome-only (vs Playwright's multi-browser)
●Similar overhead to Playwright
●Less mature stealth options

How to Scrape Trustpilot with Code

Python + Requests

import requests
from bs4 import BeautifulSoup

# Using a custom session to simulate a real browser
def scrape_trustpilot(slug):
    url = f'https://www.trustpilot.com/review/{slug}'
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36'
    }
    
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        reviews = []
        # Selector for review containers (note: classes change often)
        for card in soup.select('section.styles_reviewCard__hc_vR'):
            data = {
                'title': card.select_one('h2').text if card.select_one('h2') else None,
                'rating': card.select_one('div.star-rating_starRating__Bdb_f img')['alt'] if card.select_one('img') else None,
                'text': card.select_one('p[data-service-review-text-typography]').text if card.select_one('p') else None
            }
            reviews.append(data)
        return reviews
    return None

# Example usage
print(scrape_trustpilot('www.apple.com'))

Python + Playwright

import asyncio
from playwright.async_api import async_playwright

async def run():
    async with async_playwright() as p:
        browser = await p.chromium.launch(headless=True)
        context = await browser.new_context(user_agent='Mozilla/5.0')
        page = await context.new_page()
        
        await page.goto('https://www.trustpilot.com/review/www.apple.com')
        
        # Wait for dynamic content to load
        await page.wait_for_selector('section.styles_reviewCard__hc_vR')
        
        reviews = await page.evaluate('''() => {
            return Array.from(document.querySelectorAll('section.styles_reviewCard__hc_vR')).map(card => ({
                author: card.querySelector('span.typography_appearance-default__S8ne3')?.innerText,
                rating: card.querySelector('.star-rating_starRating__Bdb_f img')?.alt,
                date: card.querySelector('time')?.getAttribute('datetime')
            }));
        }''')
        
        print(reviews)
        await browser.close()

asyncio.run(run())

Python + Scrapy

import scrapy

class TrustpilotSpider(scrapy.Spider):
    name = 'trustpilot'
    start_urls = ['https://www.trustpilot.com/review/www.apple.com']

    def parse(self, response):
        for review in response.css('section.styles_reviewCard__hc_vR'):
            yield {
                'author': review.css('span.typography_appearance-default__S8ne3::text').get(),
                'rating': review.css('div.star-rating_starRating__Bdb_f img::attr(alt)').get(),
                'title': review.css('h2.styles_reviewTitle__m9_V_::text').get(),
                'date': review.css('time::attr(datetime)').get()
            }

        next_page = response.css('a[name="pagination-button-next"]::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)

Node.js + Puppeteer

const puppeteer = require('puppeteer-extra');
const StealthPlugin = require('puppeteer-extra-plugin-stealth');
puppeteer.use(StealthPlugin());

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  await page.goto('https://www.trustpilot.com/review/www.apple.com', { waitUntil: 'networkidle2' });

  const data = await page.evaluate(() => {
    const items = document.querySelectorAll('section.styles_reviewCard__hc_vR');
    return Array.from(items).map(item => ({
      title: item.querySelector('h2')?.innerText,
      body: item.querySelector('p')?.innerText
    }));
  });

  console.log(data);
  await browser.close();
})();

What You Can Do With Trustpilot Data

Explore practical applications and insights from Trustpilot data.

Brand Health Monitoring

Companies use real-time review data to track customer sentiment and respond to negative feedback before it goes viral.

How to implement:

1Set up a daily scraper for your company's Trustpilot profile.
2Analyze the 'Body Text' for sentiment polarity using an NLP tool.
3Trigger automatic alerts for any 1-star or 2-star reviews received.

Use Automatio to extract data from Trustpilot and build these applications without writing code.

More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents

Web Automation

Smart Workflows

Get Started Free

Pro Tips for Scraping Trustpilot

Expert advice for successfully extracting data from Trustpilot.

Target Hidden JSON-LD

Extract data from the 'application/ld+json' script tags in the page source; this structured data is more reliable than scraping the visible HTML.

Exclusively Use Residential Proxies

Data center IPs are easily flagged by Trustpilot's security layers. Residential proxies provide the legitimacy needed for high-volume extraction.

Implement Randomized Delays

Add sleep timers between 5 and 15 seconds between page loads to mimic a human browsing pattern and avoid triggering rate limits.

Rotate User Agents and TLS

Ensure your scraper rotates User-Agent strings and matches the TLS fingerprints of modern browsers to avoid detection by advanced bot filters.

Filter for Verified Reviews

When scraping for market research, focus on reviews with the 'Verified' badge to ensure your dataset contains authentic customer experiences.

Monitor for CSS Changes

Trustpilot updates its UI regularly. Periodically check your visual selectors to ensure they still map to the correct review elements.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Mohammed Ibrahim

CEO, qannas.pro

Ben Bressington

CTO, AiChatSolutions

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Related Web Scraping

Frequently Asked Questions About Trustpilot

Find answers to common questions about Trustpilot

How to Scrape Trustpilot: Extract Reviews & Ratings (2025)

About Trustpilot

The Global Standard for Customer Feedback

High-Value Qualitative Data

Why Scrape Trustpilot?

Why Scrape Trustpilot?

Real-Time Reputation Management

Competitor Weakness Discovery

High-Intent Lead Generation

Sentiment Analysis for NLP

Market Trend Identification

Dynamic Social Proof Integration

Scraping Challenges

Advanced Anti-Bot Mitigation

Deep Pagination Restrictions

Volatile Frontend Structure

Strict Rate Limiting

Scrape Trustpilot with AI

How It Works

Why Use AI for Scraping

How to scrape with AI:

Why use AI for scraping:

No-Code Web Scrapers for Trustpilot

Typical Workflow with No-Code Tools

Common Challenges

No-Code Web Scrapers for Trustpilot

Typical Workflow with No-Code Tools

Common Challenges

Code Examples

How to Scrape Trustpilot with Code

Python + Requests

Python + Playwright

Python + Scrapy

Node.js + Puppeteer

What You Can Do With Trustpilot Data

Brand Health Monitoring

Competitive Market Gap Analysis

B2B Lead Generation

Product Roadmap Prioritization

Dynamic Social Proof

What You Can Do With Trustpilot Data

Supercharge your workflow with AI Automation

Pro Tips for Scraping Trustpilot

Target Hidden JSON-LD

Exclusively Use Residential Proxies

Implement Randomized Delays

Rotate User Agents and TLS

Filter for Verified Reviews

Monitor for CSS Changes

What Our Users Say

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Frequently Asked Questions About Trustpilot

Is it legal to scrape Trustpilot?

Does Trustpilot have an official API?

How to avoid getting blocked by Trustpilot?

What format is the data extracted in?

How often should I scrape reviews?

Which proxies work best for Trustpilot?

Do I need to be logged in to scrape Trustpilot?

Can I scrape reviews for specific industries?

What data fields can I extract?