Trustpilot Reviews Scraper

Trustpilot Reviews Scraper

Scrape Trustpilot reviews from any merchant page, up to a million per run. Every review comes with star rating, body text, date, reviewer country, and company reply. No login or API key. Export to CSV, JSON, Excel, or XML.

Trustpilot's web interface only shows the most recent ~200 reviews, and their API requires a business partnership and rate limits. This Actor reads the public review feed directly, bypassing those caps, and returns every review in one flat schema. Filter by star rating or date range as you go.

Who uses it	What they scrape Trustpilot for
Market researchers	Analyze customer sentiment trends for a brand or industry over time.
Competitive intelligence analysts	Monitor competitor reviews to spot product weaknesses and strengths.
Brand managers	Track own-brand reviews daily for reputation management and response.
Data scientists	Build training datasets for NLP models on review text and ratings.
SEO specialists	Extract review keywords and phrases to inform content strategy.

What it does

This Actor collects Trustpilot reviews from any merchant review page and returns each review as a flat row with rating, text, date, reviewer info, and company reply.

• 📊 Incremental mode: Pull only reviews newer than a given date, so daily syncs stay cheap and avoid duplicates.
• 🔍 Filter by star rating: Scrape only 1-star, 5-star, or any combination in between.
• 📅 Filter by date range: Set a start and end date to focus on a specific period.
• 💬 Company replies included: Each review row includes the company's public reply text and date when available.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with Trustpilot data

📈 Track brand sentiment over time.

A brand manager runs the Actor weekly on their own Trustpilot page, filters by date, and exports to a dashboard to monitor rating trends and respond to negative reviews.

🔍 Analyze competitor reviews.

A competitive analyst scrapes reviews for three rival brands, compares star distributions and common complaints, and presents findings to the product team.

📊 Build a review dataset for NLP.

A data scientist scrapes 50,000 reviews across multiple merchants, filters by 1-star and 5-star, and trains a sentiment classifier on the text.

📝 Find keywords for SEO.

An SEO specialist extracts review body text from a merchant page, runs a word frequency analysis, and uses the top phrases to optimize product pages.

🛡️ Monitor for fake reviews.

A compliance officer scrapes all reviews for a merchant, flags sudden spikes in 5-star ratings from new accounts, and investigates potential fraud.

Why choose this scraper

	What you get
No API key needed	Scrape public Trustpilot data without registering for an API or paying per-call fees.
Past the 200-review cap	Trustpilot's web UI hides older reviews; this Actor reads them all, up to 1 million per run.
Incremental updates	Set a cutoff date to fetch only new reviews since your last run, saving time and credits.
40+ data fields	Each review includes rating, title, body, date, reviewer name, country, and company reply.
Export anywhere	Download as CSV, JSON, Excel, or XML, or push to a database via webhook.

How it compares

This Actor competes directly with other Trustpilot scrapers on Apify, offering a simpler input and a flat schema.

Feature	ParseForge	Trustpilot All Reviews Scraper 💰$0.5+ · No Cap · Incremental
No API key required	Yes	Not listed
Incremental mode (date filter)	Yes	Yes
Filter by star rating	Yes	Yes
Filter by date range	Yes	Not listed
Company replies included	Yes	Not listed
Reviewer country field	Yes	Not listed
Max 1,000,000 reviews per run	Yes	Not listed

Configure the run

Drive the Actor from a single Trustpilot merchant URL. Filters for star rating and date range run as each review is read, so only matching reviews reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
  "startUrl": "https://www.trustpilot.com/review/www.amazon.com",
  "maxItems": 10
}

A larger pull:

{
  "startUrl": "https://www.trustpilot.com/review/www.amazon.com",
  "maxItems": 200
}

Pricing

Pay-per-result: $0.01599 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$1.60
1,000 results	$15.99
10,000 results	$159.90

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the Trustpilot Reviews Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to Trustpilot through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/trustpilot-reviews-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check that the URL is a valid Trustpilot review page (e.g., https://www.trustpilot.com/review/www.amazon.com). If the merchant has no reviews, the dataset will be empty.

The Actor only returned 10 reviews.

Free accounts are limited to a 10-review preview. Upgrade to a paid plan to scrape up to 1,000,000 reviews.

The URL is rejected as invalid.

Ensure the URL starts with https:// and includes 'trustpilot.com/review/'. Subdomains like 'uk.trustpilot.com' are also supported.

Reviews are missing the company reply.

Not all reviews have a company reply. If the merchant never replies, that field will be empty for all rows.

The run is taking too long.

Large datasets (100k+ reviews) take time. Reduce the maxItems limit or use incremental mode to fetch only new reviews.

I see duplicate reviews across runs.

Use incremental mode with a cutoff date set to your last run date to fetch only new reviews and avoid duplicates.

FAQ

Question	Answer
Do I need a Trustpilot API key?	No. This Actor reads the public review pages directly, so no API registration or key is required.
How many reviews can I scrape?	Free users get a preview of up to 10 reviews. Paid users can scrape up to 1,000,000 reviews per run.
Can I scrape reviews older than the 200 shown on the web?	Yes. The Actor bypasses the web cap and can retrieve all reviews for a merchant, going back years.
Does it include company replies?	Yes. Each review row includes the company's public reply text and date, if one exists.
Can I filter by star rating?	Yes. You can choose to scrape only 1-star, 2-star, etc., or any combination.
Can I filter by date range?	Yes. Set a start and end date to scrape only reviews from a specific period.
What is incremental mode?	Incremental mode lets you set a cutoff date so the Actor only fetches reviews newer than that date, ideal for daily syncs.
What formats can I export to?	You can download the dataset as CSV, JSON, Excel, or XML, or push it via webhook to your own system.
Does it work for any Trustpilot merchant page?	Yes, as long as the URL follows the pattern https://www.trustpilot.com/review/domain.com.
Is it legal to scrape Trustpilot reviews?	Scraping public data for personal or analytical use is generally allowed, but check Trustpilot's terms of service and your local laws.
What if the merchant has no reviews?	The Actor will return an empty dataset. Double-check the URL is correct and the merchant page exists.
Can I scrape multiple merchants in one run?	This Actor takes one URL per run. To scrape multiple merchants, run the Actor separately for each URL.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Trustpilot A/S. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.