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A Trustpilot scraper for full business review history

The Kavex Trustpilot scraper turns any Trustpilot business page into a clean spreadsheet of reviews. Give it a Trustpilot URL or just a bare domain and it returns every review with its rating, text, author and date. It is built for competitor research and reputation tracking, where the detail in the reviews tells you far more than the headline score. You pay per review returned, so a focused job stays cheap.

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What it does

The Trustpilot scraper accepts either a full Trustpilot review URL or simply a company domain — it resolves the domain to the right Trustpilot page for you, so you do not have to look each one up by hand.

It then paginates through the business’s review history and returns each review as a row: the star rating, the review title and body, the author and the date. The business name and overall TrustScore travel with the rows, so a single export holds both the summary and the underlying detail.

A per-business cap controls depth, letting you take a recent slice across many competitors or pull a full history for a deep dive. The output is structured for a spreadsheet or a sentiment tool, with nothing to clean up first.

Trustpilot reviews carry a signal a star count hides: intent. A reviewer who writes at length about a billing problem or a slow response is describing a switching trigger, and a list of those reviewers is a list of warm prospects for a competitor win-back campaign. Pulling the full text and dates also lets you separate old complaints that have since been fixed from fresh ones still live. Run a competitor domain before a sales cycle and you walk in knowing exactly where they are weak; run your own and you see the themes worth addressing before they spread. Either way the export is raw evidence, not a summary.

Use cases

  • Sales teams checking a competitor’s service quality on Trustpilot before pitching against them.
  • Win-back campaigns finding the unhappy customers of a rival who are worth a targeted offer.
  • Brand owners tracking how their own Trustpilot rating and review themes drift month to month.
  • Researchers gathering review text in bulk to analyse complaints and praise across a whole category.

Sample output

Each review is one row, tied to its business:

BusinessTrustScoreAuthorRatingDateReview
brightlabs.co4.2Marc V.52026-04-24Support answered within the hour every time.
brightlabs.co4.2Hannah T.22026-04-12Billing was confusing and hard to change.
varzace.de3.6Lena V.32026-04-21Good tool, onboarding docs are thin.
varzace.de3.6Paul R.42026-04-09Reliable, does what it promises.

How it works

The Trustpilot scraper fetches each business page directly and paginates through the review list, collecting entries until it hits your per-business cap. Trustpilot pages are reachable without a browser engine, so the job is quick and lightweight.

Every run is live, so the reviews and the TrustScore reflect the page as it stands that day. When you pass a bare domain, the scraper handles the lookup to the matching Trustpilot profile, which means a list of competitor domains is all you need to start.

Frequently asked questions

Can I pass a domain instead of a Trustpilot URL?

Yes. The Trustpilot scraper accepts a bare company domain and resolves it to the matching Trustpilot business page, so a plain list of competitor domains is enough to run a job.

How many reviews does it return per business?

You set a per-business cap and the scraper paginates up to it. Use a small cap for a quick sample across many competitors, or a large one for a full-history deep dive.

Does each review include a date?

Yes, every review row carries the date it was posted, so you can filter to a recent window or chart how sentiment has moved over time.

How do results export?

Reviews download as a CSV with one review per row — business, TrustScore, author, rating, date and full text — ready for filtering or analysis.

Try it free — 1000 credits on us

Pay per result — no subscription, no seats. New accounts start with 1,000 free credits.

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