Dive into authentic business and service reviews with our Trustpilot Scraper — ScrapeIt delivers structured review data, company info, and ratings, neatly organized and ready for analysis or integration.
Trustpilot pages are rich with dynamic content — but when you need to scrape Trustpilot for specific insights, we extract only what matters. Whether you’re focused on particular companies, industries, or keywords, we parse review pages, rating histories, and profile metadata with precision. You define the scope, and we deliver the structured output: filtered, labeled, and formatted for your analysis pipeline. No bloat, no duplicated records — just clean, relevant data from one of the world’s largest review platforms.
From each Trustpilot profile, the Trustpilot Scraper extracts structured business data such as the company name, TrustScore, total number of reviews, industry category, and profile URL. On the review level, it captures the title, written feedback, date of posting, reviewer name (or alias), and any official responses from the company. When available, it also collects verification status, review tags (like “Excellent Service” or “Fast Delivery”), and content flags. This detailed review dataset is ideal for sentiment analysis, trend tracking, or competitive benchmarking.
Trustpilot is more than just a review board — it offers layers of insight that reveal how businesses interact with customers over time. ScrapeIt captures dynamic fields such as the frequency of replies, average response time, and whether a company actively invites reviews. We also extract labels like “Verified Company,” content moderation flags, and indicators of whether a review was flagged or disputed. These elements help paint a deeper picture of reputation management, customer engagement, and overall credibility — critical for brand analysis or market audits.
Trustpilot is a global review platform that prioritizes transparency and the consumer voice. Founded in Copenhagen in 2007, it now serves users in over 25 countries and supports reviews in 20+ languages. Unlike closed feedback systems controlled by brands, trustpilot.com allows any consumer to leave a review — making it one of the most open and trusted feedback ecosystems in the world.
The platform hosts reviews for millions of businesses — from SaaS platforms, e-commerce stores, and banks to travel companies, logistics providers, and local services. Each company profile shows a TrustScore (1–5 scale), full review history, response records, verified badges, and analytics like review frequency and timing. Filters allow users to sort by star rating, country, language, or tag, helping both buyers and B2B researchers make informed decisions.
Its audience is broad: consumers vetting brands, marketers tracking reputation, and B2B teams analyzing supplier reliability. Many companies — particularly in fintech, fashion, travel, electronics, and health — actively manage their presence, respond to feedback, and integrate reviews into their sales flows.
A standout feature is invitation-based reviews, where businesses collect verified feedback directly via CRM tools. Additionally, Trustpilot publicly displays flagging and moderation activity, offering transparency into how disputes are handled — something rare in the review industry.
Ultimately, Trustpilot is more than a ratings site. It functions as a real-time reputation engine, surfacing signals around customer satisfaction, product quality, and brand trust in highly competitive markets.
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Trustpilot holds massive value — but manually reviewing pages or copying data won’t scale. A Trustpilot web scraper allows you to extract thousands of reviews, company profiles, and engagement signals at once, filtered by location, category, or score. Whether you're monitoring competitor feedback, building a sentiment dashboard, or sourcing leads in specific industries, scraping Trustpilot provides structured, unbiased review data you can actually act on. It turns a noisy, user-generated ecosystem into a clean asset for research, outreach, or reputation analysis.
Learn how to use web scraping to solve data problems for your organization
If you work in travel tech, an OTA, a hotel chain, or at an airport, you are in a price-and-availability arms race. Fares change by the hour, room inventory disappears in minutes, and competitors test new bundles and ancillaries constantly.
If you sell online, run a marketplace, or advise e-commerce clients, you already know why eBay matters: it’s one of the few places where big retailers compete side by side with thousands of small merchants and private sellers.
E-commerce teams do not just need “some” competitor data anymore. They need a continuous stream of real prices, discounts, stock levels, reviews, and seller behavior from the platforms that actually shape their markets.
With our Trustpilot scraper, you don’t need to worry about navigating pagination, extracting nested review content, or dealing with platform rate limits. We do all of that for you — and more. You tell us what you’re after: specific companies, industries, countries, or review ranges. We handle the extraction, clean the output, and structure the data around your workflow. Whether you need a bulk snapshot for analysis or ongoing updates, ScrapeIt ensures you get precise, filtered review data — ready to use, no post-processing required.
Yes. Trustpilot supports reviews in over 20 languages, and we can include multilingual content in your dataset or filter it by language, depending on your needs.
Absolutely. We can schedule recurring extractions to monitor how scores, review volumes, or public responses evolve week by week or month by month.
Where available, yes — we extract reviewer locations, verification status, and tags such as “Invited” or “Verified.” These are helpful for segmentation and trust analysis.
We typically provide structured outputs in CSV, Excel, or JSON — easy to integrate into BI tools, dashboards, or reporting workflows.
Our clients include reputation managers, marketing analysts, e-commerce teams, and B2B platforms looking to track competitors, audit public perception, or map customer sentiment at scale.
1. Make a request
You tell us which website(s) to scrape, what data to capture, how often to repeat etc.
2. Analysis
An expert analyzes the specs and proposes a lowest cost solution that fits your budget.
3. Work in progress
We configure, deploy and maintain jobs in our cloud to extract data with highest quality. Then we sample the data and send it to you for review.
4. You check the sample
If you are satisfied with the quality of the dataset sample, we finish the data collection and send you the final result.
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