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How to Scrape Trustpilot Reviews with Apify (2026 Guide)

· 6 min read
Yassine El Haddad
Yassine El Haddad
Software Developer & Automation Specialist

I build production AI agents, web scrapers, and automation pipelines. Most of what I publish here comes from the actual problems they run into: proxies that get banned, anti-bot stacks that fingerprint your client, RAG that drifts when the underlying data moves. Stack: Python, TypeScript, Go, FastAPI, LangChain, Crawlee, Playwright, deployed on AWS, GCP, and Cloudflare.

Quick Answer

Scrape Trustpilot reviews with an Apify Trustpilot Actor: paste a company's Trustpilot URL (or its domain), set how many reviews and which star ratings you want, run the Actor, and export the ratings, review text, dates, and company replies as JSON or CSV. No coding required.

Trustpilot is where customers rate companies at scale, so its reviews are a goldmine for reputation monitoring, competitor benchmarking, and product research. The site's UI paginates and caps what you can see, and it has no export button, which is exactly the gap a scraper fills.

This guide covers no-code Trustpilot extraction on Apify: which Actor to pick, the input fields that matter, what it costs, and how to turn the review text into insight with an LLM.

Start on Apify (free monthly credits) →

Which Trustpilot Actor to use​

Unlike Google Maps, Trustpilot has no single dominant Actor, so pick by pricing model and fields:

  • Trustpilot Reviews Scraper (automation-lab/trustpilot) is the most-used, at about $0.000575 per review (pay-per-event), with ratings, replies, reviewer info, and company data. Good default. A handful of lower-volume Actors undercut it slightly (around $0.0005 per review), so shop on price if you are running millions.
  • Trustpilot Reviews + AI Intelligence (memo23/trustpilot-scraper-ppe) costs about $0.00075 per review plus a small run-start fee, but adds 40+ fields, server-side filters, and no 200-review cap. Pick it when you need depth or high volume.

Both use pay-per-event pricing, so there is no separate compute charge and cost scales with the number of reviews.

Step by step (no code)​

  1. Open a Trustpilot Actor (start with automation-lab/trustpilot) and click Try for free.
  2. Add your targets to companyUrls. You can paste full Trustpilot company URLs or just domains like example.com.
  3. Set filters: maxReviewsPerCompany, a stars filter (e.g. only 1 to 2-star reviews to find complaints), a date range, and a sort order.
  4. Start the run, watch the log, and open the dataset when it finishes.
  5. Export as JSON, CSV, or Excel, or pull the data over the API into your pipeline.

Advanced input (JSON tab)​

{
  "companyUrls": ["https://www.trustpilot.com/review/example.com"],
  "maxReviewsPerCompany": 500,
  "stars": ["1", "2"],
  "sort": "recency",
  "verified": false,
  "withReplies": false,
  "includeCompanyInfo": true
}

Filtering to 1 to 2-star reviews is the fastest way to surface recurring complaints; drop the stars filter to pull everything for a full sentiment baseline.

What it costs​

At the entry (FREE) tier, automation-lab/trustpilot charges about $0.000575 per review with no separate compute charge. So:

  • The Free plan's $5 monthly credit covers roughly 8,600 reviews.
  • 20 competitors at 300 reviews each (6,000 reviews) costs about $3.50.
  • Per-event rates fall at higher monthly-spend tiers.

Confirm the live rate on the Actor's Pricing tab before scaling, and see our Apify pricing guide for how per-event fees fit alongside plans and credits.

Turn Trustpilot data into insight with AI​

Trustpilot text is unstructured until you summarize it. Export the dataset and feed it to an LLM to extract:

  • Sentiment and a rating trend over time
  • Recurring complaint themes (shipping, support, billing)
  • Competitor weaknesses you can position against

Because the Actor returns clean JSON, it drops straight into an LLM prompt. Our guide on connecting ChatGPT and Claude to scraped data shows the wiring for automated weekly review digests. Pair it with Google reviews for a fuller reputation picture across platforms.

Trustpilot reviews are public, and courts have generally treated scraping public data as permissible. The honest caveats:

  • Personal data. Reviewer names and profiles are personal data under GDPR and CCPA. Only collect identities you have a lawful basis to process, and avoid storing what you do not need.
  • Terms of service. Automated access can conflict with Trustpilot's ToS. Aggregating ratings and text for internal analysis is low-risk; republishing reviews verbatim or building a competing directory is not. This is general information, not legal advice.

For monitoring and research, Trustpilot scraping is standard competitive practice.

FAQ​

Frequently Asked Questions

Yes. Add multiple company URLs or domains to companyUrls and the Actor processes them in a single run, returning reviews tagged by company.

The most-used Actor (automation-lab/trustpilot) charges about $0.000575 per review at the entry tier, with no separate compute charge, so the Free plan's $5 credit covers roughly 8,600 reviews. Rates drop at higher monthly-spend tiers; confirm the current price on the Actor's Pricing tab.

Yes. Set the stars filter to ["1", "2"] to return only 1 and 2-star reviews, which is the quickest way to surface recurring complaints and support issues. The values are strings, not numbers, so [1, 2] fails input validation.

Some Actors cap results per company. If you need to pull thousands of reviews for a single company, use an Actor that advertises no cap, such as memo23/trustpilot-scraper-ppe.

Next steps​

Pick the Trustpilot Reviews Scraper, pull reviews for your target companies, then route the text through an LLM analysis pipeline for sentiment and themes. To cover more platforms, add Google reviews from the same businesses.

Create a free Apify account and scrape your first Trustpilot reviews →