Trustpilot Scraper: Export Reviews in 2026
If you need to analyze hundreds of customer reviews for competitor research, a Trustpilot scraper turns public Trustpilot company review pages into a structured review dataset. Review text, star ratings, reviewer names, dates, verified badges, company replies, and review URLs become a table your team can sort, tag, and summarize.
Teams use scrape Trustpilot reviews workflows for competitor research, customer pain analysis, reputation monitoring, and review operations. Browser-based scraping works well here because reviewers, dates, ratings, replies, and verification labels are easiest to confirm from the same public page your team is already reading.
Build a review analysis dataset from Trustpilot
Open a public Trustpilot review page, export ratings, review text, dates, replies, and URLs, then use the table for competitor research, complaint clustering, or reputation monitoring.
Add to Chrome - Free ->What Is a Trustpilot Scraper?
A Trustpilot scraper is a tool for turning public customer reviews into a structured research dataset. Marketing, CX, product, ecommerce, and competitive-intelligence teams use it to find complaint patterns, compare reputation across competitors, audit support quality, and monitor review velocity.
Trustpilot is most useful when the question is qualitative: "Why are buyers unhappy?", "Which competitor issues repeat?", "Do replies improve after a support change?", or "Which products attract the most severe complaints?" It complements local review sources covered in the Yelp scraper guide and Google Maps review workflow, plus B2B software reviews covered in the G2 scraper guide.
- Star rating and review title
- Full review body text
- Reviewer display name
- Review date
- Verified badge or experience label
- Company reply when visible
- Review URL and company URL
How Do You Scrape Trustpilot Reviews Without Code?
To scrape Trustpilot reviews without code, open the public company review page in Chrome, apply filters or sort order, run Clura, select the repeated review cards, confirm pagination, and export to CSV. A typical company-page export takes about 2-5 minutes after the page is loaded.
- Open the Trustpilot company page. Use the public review page for the brand or competitor you want to analyze.
- Apply filters. Choose rating filters, language, date sort, or recency before scraping.
- Run Clura. Select the repeated review-card pattern.
- Review fields. Keep rating, title, review text, reviewer, date, verified badge, company reply, and URL.
- Confirm pagination. Collect additional review pages into the same table.
- Export CSV. Analyze sentiment, themes, review velocity, or competitive gaps.
Turn Trustpilot reviews into a spreadsheet
Use Clura for Trustpilot review pages, or use the Product Reviews Aggregator Scraper template when your research spans multiple review sources.
Add to Chrome - Free ->What Is the Best Trustpilot Scraper Method?
A Chrome extension is usually the best Trustpilot scraper method for review research because it takes about 2 minutes to set up and reads the rendered review cards. Python and Playwright can work for scheduled monitoring, but they require selector maintenance, pacing, and retry logic.
| Method | Block / Failure Rate | Setup Time | Typical Cost | Best For |
|---|---|---|---|---|
| Clura Chrome extension | ~4-6% | 2-5 min | Free / $29.99 lifetime | Review exports from public pages |
| Playwright + selectors | ~12-20% | 4-8 hours | $0-100/mo infra | Scheduled review monitoring |
| Apify-style actors | ~18-28% | 30-60 min | $49/mo+ | Managed cloud runs |
| Python requests | ~75-90% failure | 30 min (fails) | Free | Learning only |
Trustpilot review pages use repeatable cards, but raw HTML scrapers can miss rendered fields, paging state, and filter state. The safer workflow is the one explained in scraping dynamic websites: let Chrome render the page first, then extract the DOM you can actually see.
For broader review intelligence, compare Trustpilot with the Yelp scraper, G2 reviews template, and Capterra reviews template.
What Can You Do With Trustpilot Review Data?
Trustpilot review data is useful for sentiment analysis, complaint clustering, competitor positioning, support-quality audits, review-velocity tracking, and ecommerce conversion research. The use case is not simply exporting reviews; it is turning customer language into product, marketing, support, and sales decisions.
Competitor review analysis
Scrape competitor reviews weekly and group complaints by pricing, delivery, refunds, onboarding, support, or product quality. This gives marketing and product teams real customer language for positioning, objection handling, and roadmap prioritization. The competitive intelligence guide shows how to turn those complaints into signals.
Support and reputation monitoring
CX teams can export recent reviews, track low-rating themes, and compare company replies over time. That makes the table useful for weekly support reviews, reputation reports, and identifying the few issues that are driving the most public complaints.
Review-led lead generation
Trustpilot reviews can identify dissatisfied competitor customers and recurring pain points. For the follow-up workflow, use the lead scraper guide and web scraping for lead generation to connect review themes to accounts and outreach.
Frequently Asked Questions
Can Trustpilot reviews be scraped?
Yes. Public Trustpilot company reviews can be scraped when they are visible in your browser. Common fields include star rating, review title, review text, reviewer name, date, verified badge, company reply, and review URL.
How do I scrape Trustpilot reviews?
Open a public Trustpilot company review page in Chrome, apply filters, run Clura, select the repeated review cards, confirm pagination, and export the extracted review fields to CSV or Excel.
Is there a free Trustpilot scraper?
Clura is free to start and works on public Trustpilot review pages from Chrome. You can preview extracted review fields and export visible review data without writing code.
Can I scrape Trustpilot with Python?
You can scrape Trustpilot with Python, but a browser-based workflow is usually faster for one-time exports. Python scripts need selectors, pagination handling, and maintenance when page structure changes.
Is scraping Trustpilot legal?
Scraping publicly visible Trustpilot review data may be permissible in many jurisdictions, but Trustpilot's terms may restrict automated use. Avoid private data, do not bypass access controls, and get legal advice for commercial-scale projects.
Does Trustpilot have an API?
Trustpilot offers business APIs for approved use cases, but API access is not the fastest path for ad hoc review research. If the public review page contains the data you need, a browser workflow can export it directly.
Conclusion
Trustpilot scraping is a clean review-research workflow when you start from the public company page, keep filters visible, and export the repeated review cards into a table.
Use Clura for fast review exports. Use a custom Playwright job only when the scrape needs scheduled collection, monitoring, and engineering maintenance.
Explore related guides:
- Product Reviews Aggregator Template — Collect review data across multiple visible review sources.
- Yelp Scraper Guide — Scrape local business listings and reviews.
- G2 Scraper Guide — Extract B2B software review data from G2.
- Capterra Reviews Template — Export software review text and reviewer context.
- Lead Scraper Guide — Turn public web data into source-specific prospect lists.
- Scrape Dynamic Websites — Handle JavaScript-rendered review cards and pagination.
Export Trustpilot reviews without code
Install Clura, open a Trustpilot company page, select review fields, and export ratings, review text, dates, badges, replies, and URLs to CSV.
Add to Chrome - Free ->