How to Scrape Trustpilot Company data (Step-by-Step Guide)

How

Trustpilot is one of the largest online review platforms, hosting millions of company profiles where customers share ratings and feedback about businesses across industries. Trustpilot company listings contain structured information such as company names, TrustScore ratings, review counts, categories, and links to company websites. In this guide, you will learn how to scrape Trustpilot company listings using Web Scraper and extract structured company data directly from category and listing pages without writing code. The collected data can be exported in CSV, Excel, or JSON formats for further analysis, reputation monitoring, market research, or integration into other systems.

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What Data Can You Extract From Trustpilot Company Listings

Trustpilot company listings contain structured information about businesses and their customer reviews that can be collected and organised into datasets for analysis, reputation monitoring, and market research. Each company profile typically includes details such as the company name, TrustScore rating, review count, category, and links to the company website, which help identify and evaluate businesses across different industries.

Below are examples of the structured data fields that can be extracted from Trustpilot company listings.

business_url
business_name
category
address
phone_number
email
website_url
rating
review_count
review_ai_summary
company_details
images


The extracted dataset can be exported in CSV, Excel, or JSON formats, allowing the data to be analysed, stored, or integrated into external systems and data workflows.


Method 1 - Use a Prebuilt Trustpilot Company Listings Scraper (Recommended)

The simplest way to scrape Trustpilot company data is to use the ready-made Trustpilot businesses listings scraper available in the Web Scraper Marketplace.

This scraper is preconfigured to collect structured business information from Trustpilot category and search result pages, follow pagination, open company profiles, and extract company-level data automatically.

Instead of setting up selectors, pagination, and listing navigation manually, you can start with Trustpilot category or search URLs and use the scraper to collect the dataset with minimal setup.

Trustpilot businesses listings scraper

https://webscraper.io/marketplace/trustpilot-businesses-listings-scraper

Steps:

  1. Open the Trustpilot company listings scraper
  2. Import it into Web Scraper Cloud
  3. Add Trustpilot category or search result URLs as start URLs
  4. Run the scraper
  5. Export the dataset

Example start URL:

https://www.trustpilot.com/categories/music_store

The scraper automatically:

  • navigates category/search result pages
  • handles pagination across listing pages
  • discovers company listings
  • opens company profile pages
  • extracts structured company information

This allows you to collect large datasets of Trustpilot company data without manually building a scraper.


Method 2 - Build Your Own Trustpilot Scraper

You can also create a custom scraper using the Web Scraper Chrome extension.

Steps:

  1. Install the Web Scraper Chrome extension
  2. Open a Trustpilot category or search results page. Example:. Example: https://www.trustpilot.com/categories/music_store
  3. Click the Web Scraper icon in the top-right corner of your browser
  4. Start the Sitemap Wizard, which automatically detects listing elements on the page (detects 20 company listings)
  5. Configure pagination using the pagination selector tool and select the Next button
  6. Click Select Link and choose the company profile links to follow
  7. Review generated selectors and modify them if additional data is needed
  8. Run the scraper locally or execute it in Web Scraper Cloud

For more detailed instructions, see the Web Scraper tutorials.


Technical Considerations and Anti-Bot Protections When Scraping Trustpilot

When scraping Trustpilot company listings, several technical factors may affect how data is collected and how pagination behaves during extraction.

Bot protection Trustpilot internal anti-bot protection with CDN-level request filtering
Browser check / fingerprinting Browser fingerprinting and behavioural detection may be present
CAPTCHA presence reCAPTCHA challenges may appear during higher request volumes
Rendering Next.js framework with server-rendered HTML and dynamically loaded elements
Proxy requirement Datacenter proxies suitable for smaller scraping jobs; residential proxies recommended for larger-scale scraping
Request throttling 2-5 second delays recommended between requests
Scraping difficulty Medium


IP rotation and request management

Large scraping jobs may require distributing requests across multiple IP addresses to avoid temporary request limits or automated traffic restrictions. When collecting large datasets across multiple Trustpilot categories or search queries, spreading requests across different IPs and introducing request delays helps maintain stable extraction. Web Scraper Cloud can help manage request distribution and reduce the risk of temporary blocking during larger scraping runs.

Pagination limits and listing availability

Trustpilot company listings are displayed with 20 companies per page and allow a maximum of 500 pagination pages, meaning that up to 10,000 companies can be accessed within a single category. If a category contains more companies than this limit, some listings may not be reachable through pagination.

To ensure full data coverage, it is recommended to narrow category scope or apply filters so the total number of listings remains within these limits.

Pagination result shifting

Trustpilot may dynamically reorder companies between pagination pages when navigating results by loading pagination URLs directly. During scraping, a company that initially appears on one page may shift to a different page as pagination progresses. This behaviour can cause some listings to be duplicated or missed.

Using JavaScript click pagination instead of URL-based pagination helps reduce this issue by loading the next page within the same browsing session and maintaining more stable result ordering.

Web Scraper Cloud execution limits

When using JavaScript click pagination with Web Scraper Cloud, the scraper runs inside a continuous browser session. To avoid exceeding execution limits, a single scraping job should typically remain below 200 pagination pages or approximately 4,000 listings.

If a category contains more listings, the dataset can be collected by splitting the scraping task into smaller segments.

Review pagination limitation

If extracting company reviews, Trustpilot only allows access to the first 10 review pages before displaying a login prompt to access additional reviews. This limitation restricts review collection from company profiles unless authenticated access is used.

Anti-bot protections

Trustpilot uses automated traffic monitoring systems that may detect high-frequency automated browsing behaviour. Under higher request volumes, protections such as reCAPTCHA challenges or temporary request limits may appear. Introducing request delays, distributing requests across multiple IP addresses, and limiting concurrent scraping jobs can help reduce the likelihood of blocking during larger scraping tasks.


Automate Trustpilot Scraping With Web Scraper Cloud

For larger scraping jobs, running scrapers locally can become unreliable. Long scraping sessions may stop if the browser closes, and collecting data across multiple Trustpilot categories or search queries may require controlled request execution and pagination management.

Web Scraper Cloud runs scrapers on cloud infrastructure and supports automated large-scale data extraction.

With Web Scraper Cloud, you can:

  • Schedule scraping jobs
  • Run long scraping tasks without local execution
  • Export datasets automatically (CSV, Excel, JSON)
  • Send data to external services such as Google Sheets, Dropbox, Amazon S3, and others
  • Control and integrate scraping workflows through the Web Scraper API
  • This enables automated scraping and continuous updates of structured datasets.

When using JavaScript click pagination with Web Scraper Cloud, scrapers run inside a continuous browser session. Because of execution limits, a single scraping job should typically remain below 200 pagination pages or approximately 4,000 listings. If a Trustpilot category contains more listings, the scraping task should be split into smaller segments.

These capabilities allow automated Trustpilot data collection and continuous updates of structured company datasets.


Related Scrapers (Directory and Company Listings Scrapers)

Web Scraper also provides ready-made scrapers for extracting structured listing data from other directories and platforms.

Browse the full scraper library: Web Scraper Marketplace.


Related Scraping Guides

If you want to learn how to scrape other websites, these guides may also be useful.

Browse all scraping tutorials in the Web Scraper Blog.


Common Use Cases for Trustpilot Company Listings Data

B2B lead generation

Trustpilot company listings can be used to identify businesses operating within specific industries or categories. Extracting these listings helps organisations discover potential partners, vendors, or service providers and build targeted outreach lists based on company categories and online presence.

Lead database development and enrichment

Trustpilot company profiles contain structured information such as company names, TrustScore ratings, review counts, categories, and links to company websites. This data can be used to build new lead databases or enrich existing CRM records with reputation metrics and company profile information.

Customer sentiment analytics

Trustpilot hosts large volumes of customer reviews and ratings across thousands of companies. Extracting review statistics and TrustScore data allows analysts to measure customer satisfaction, track brand reputation, and identify companies with strong or declining public perception.

Market and competitor analysis

Businesses and analysts can use Trustpilot company data to understand how companies are positioned within different categories. By collecting ratings, review volumes, and company listings, it becomes possible to identify competitors, benchmark reputation metrics, and monitor market visibility across industries.

Reputation monitoring datasets

Aggregated Trustpilot company data can be used to build datasets that track reputation trends across industries. Analysts can monitor how ratings and review volumes evolve over time and identify companies with strong customer feedback or emerging reputation risks.


FAQ

Can Trustpilot company data be scraped?

Yes. Trustpilot category and company pages contain publicly accessible information about businesses and their review statistics. This data can be collected using web scraping tools, provided that scraping activities comply with Trustpilot’s terms of service and applicable data regulations.

What is the best Trustpilot scraper?

Web Scraper is well-suited for collecting Trustpilot company listings. The Sitemap Wizard can automatically detect listing elements on category or search result pages and helps configure pagination and company profile extraction without writing code.

Can I scrape Trustpilot without coding?

Yes. Web Scraper provides a visual interface that allows users to generate selectors automatically, follow company profile links, and extract structured data such as company names, ratings, and review counts without writing scripts.

What Trustpilot company data can be extracted?

Typical fields include company name, TrustScore rating, review count, category, company profile URL, and links to the company website. Additional information can be extracted from company pages depending on the scraping configuration.

How many companies appear per Trustpilot page?

Trustpilot typically displays 20 companies per listing page. Pagination allows navigation through up to 500 pages, meaning that up to 10,000 companies can be accessed within a single category.


Conclusion

Trustpilot contains millions of public company profiles with customer reviews, ratings, and reputation metrics across a wide range of industries. Extracting this data allows businesses and analysts to study customer sentiment, benchmark competitors based on TrustScore and review volume, and build structured datasets of companies together with their reputation signals.

With Web Scraper, Trustpilot company listings can be collected automatically from category and search result pages without writing code. The scraper can navigate listing pagination, follow company profile links, and extract structured company information such as company names, TrustScore ratings, review counts, and profile URLs. The collected data can then be exported in CSV, Excel, or JSON formats for analysis, reporting, or integration into external systems.

To simplify the setup process, you can use the Trustpilot company listings scraper available in the Web Scraper Marketplace. The template is preconfigured to discover company listings, handle pagination, and extract structured company data from Trustpilot pages, allowing you to start building Trustpilot datasets quickly.



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