Trustpilot Reviews Scraper
Scrape Trustpilot reviews and TrustScore profiles by domain, company name or URL, no login
Datapika Trustpilot Reviews Scraper is our scraping tool published as openclawai/trustpilot-reviews-scraper on Apify. Datapika maintains the product; Apify hosts execution and billing. About the publisher.
What is this API for?
Collect public Trustpilot reviews and company profiles by domain, company name or review page URL. Review rows with rating, title, text, dates, verification flag, reviewer country and company reply, plus a free profile row with TrustScore and rating distribution.
Limits: Not an official Trustpilot API. Trustpilot serves at most 200 reviews per filter stream; the deep sweep combines streams but very large brands will not return every review.
$0.005 per review
2 users
63 runs
Takes a website domain, a company name or a Trustpilot review page URL and returns every review as one row: star rating, title, text, language, dates, verification flag, reviewer country, likes and the company reply, plus one free company profile row with TrustScore, rating distribution, review counts, categories and reply rate. Server-side filters for stars, date range, language, verified only and replied only, and a deep sweep that goes past Trustpilot's 200-review page limit. $0.005 per review.
- No account, app token or cookie: reads Trustpilot's public pages through an anti-bot proxy included in the price.
- Deep sweep combines star, date and language streams to recover thousands of reviews per company, deduplicated.
- Free company profile row with TrustScore, rating distribution, reply rate and average days to reply.
Apify store response dated . Figures are cached and may lag; confirm current rates on Apify.
The displayed rate is the primary result event. Start fees, additional events, platform usage, or plan charges may apply. Check the current pricing before running.
Built for
The data contract
Know the fields before you run.
Selected fields from the published build 1.0.2, reviewed September 4, 2026. This is a schema reference, not a live result sample. Fields can be absent or empty depending on the source and selected options.
Download the dated input and field references (.json)| Field | Type | Meaning / availability |
|---|---|---|
| dataType | string | review | company | hint | error |
| id | string | Review or company ID. |
| company | string | Company display name. |
| rating | integer | Star rating 1–5. |
| title | string | Review title. |
| text | string | Review text. |
| language | string | Review language code. |
| publishedAt | string | When the review was published (ISO 8601). |
| isVerified | boolean | Verified review. |
| reviewerCountry | string | Reviewer country code. |
| hasReply | boolean | Company replied. |
| replyText | string | Company reply. |
| trustScore | number | TrustScore 0–5. |
| numberOfReviews | integer | Total reviews. |
| ratingDistribution | object | Review count per star. |
Call it from code or an agent
curl -X POST \
"https://api.apify.com/v2/acts/openclawai~trustpilot-reviews-scraper/run-sync-get-dataset-items?format=json" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"companies":["www.notion.so","Airbnb"],"maxReviews":100,"stars":[],"dateRange":"all","deepSweep":true}'Set APIFY_TOKEN to your own token. This small input was checked against the published schema; it is not an executed benchmark. Running it can incur charges. For large jobs, use the asynchronous /runs endpoint.
Full input schema and OpenAPI spec on the actor API page.
Questions, answered
How much does it cost to scrape 1,000 Trustpilot reviews?
$5. The only charged event is one review row at $0.005; company profile rows, hints and error rows are free. A 200-review pull for one company takes about a minute and a 1,500-review deep sweep about five minutes, measured on 2026-09-06.
Why does Trustpilot stop at 200 reviews and how does the deep sweep get more?
Trustpilot serves at most 10 pages of 20 reviews for any one filter combination. The deep sweep requests many combinations of star rating, date bucket and language, then removes duplicates, so a company with thousands of reviews yields thousands rather than 200.