Trustpilot hosts over 300 million reviews across 1 million+ businesses. If you work in competitive intelligence, reputation monitoring, or lead generation, that data is valuable — and scraping it at scale is the main way to get it, since Trustpilot's official API is limited to businesses managing their own profiles.
The Apify Store has several Trustpilot scrapers. They range from mediocre to solid. I tested all of them in March 2026 and here is what I found.
Why Scrape Trustpilot?
Three common use cases:
Competitive intelligence. Pull all reviews for a competitor's product, analyze sentiment trends, identify recurring complaints. If 40% of their reviews mention "slow support," that is a gap you can exploit.
Reputation monitoring. Track your own company's reviews over time. Set up a daily scrape, pipe results into a dashboard, and catch negative reviews before they snowball.
Lead generation. Search Trustpilot by business category ("web hosting", "CRM software") to build lists of companies with their trust scores, review counts, and locations. Filter by rating to find businesses that might need your product or service.
The Problem With Existing Scrapers
I searched the Apify Store for "trustpilot" and found three actors. Their ratings tell the story:
| Actor | Author | Rating | Users | Modes | Full Pagination | Date/Rating Filters |
|---|---|---|---|---|---|---|
| Trustpilot Reviews Scraper | casper11515 | 3.64/5 | 2,438 | Reviews only | Partial | No |
| Trustpilot Reviews Scraper | nikita-sviridenko | 3.41/5 | 1,771 | Reviews only | Partial | No |
| Trustpilot | canadesk | 3.31/5 | 417 | Reviews + Sentiment | Limited | No |
| Trustpilot Scraper | cryptosignals | New | New | Reviews, Search, Batch | Yes | Yes |
Ratings between 3.3 and 3.6 usually mean "it works sometimes." The common complaints across all three: missing pagination (only gets the first page of reviews), no filtering options, and stale maintenance.
Deep Dive: Each Actor
casper11515/trustpilot-reviews-scraper (3.64 stars, 2,438 users)
The most popular option by user count. It extracts review titles, descriptions, scores, reviewer info, countries, and company responses. The core data extraction works — when it works. User reviews mention issues with pagination breaking after the first page and the actor not being updated to handle Trustpilot's layout changes. For a company with 50 reviews, it is probably fine. For a company with 5,000 reviews, you will get incomplete data.
Best for: Quick, small-scale review pulls where you only need the first page or two.
nikita-sviridenko/trustpilot-reviews-scraper (3.41 stars, 1,771 users)
Similar feature set to casper11515's version — review extraction with basic fields. The "FREE to use" label attracts users, but you get what you pay for. The main gap is the same: limited pagination and no way to filter by date range or rating. If you need reviews from the last 30 days only, you have to pull everything and filter client-side.
Best for: Free-tier users who need basic review data and don't mind manual filtering.
canadesk/trustpilot (3.31 stars, 417 users)
The smallest and lowest-rated option, but it has one interesting feature: built-in sentiment analysis (Negative, Neutral, Positive). The actor classifies each review as it scrapes. The downside is that the scraping itself is limited — fewer users and lower ratings suggest reliability issues.
Best for: Users who want quick sentiment labels without running a separate NLP pipeline.
cryptosignals/trustpilot-scraper (New)
Full disclosure: I built this one. Here is what it does differently:
Three modes. Reviews mode pulls reviews for a specific business. Search mode finds businesses by keyword (like "web hosting" or "CRM software"). Batch mode processes multiple business domains in a single run.
Full pagination. Follows Trustpilot's ?page=N links automatically. A business with 10,000 reviews across 500 pages? It pages through all of them. This is the gap that most existing actors fail on.
Filters. Filter by date range (dateFrom), minimum rating (minRating), maximum rating (maxRating), and language. Pull only 1-star reviews from the last 90 days without downloading the full review history.
Rate limiting. 1 request per second with jitter, plus user-agent rotation. Designed to be respectful to Trustpilot's servers and avoid blocks.
Data fields. Reviewer name, country, review count, star rating, title, full text, date, verified purchase status, badges, business reply, and direct review URL.
Code Examples
Get Reviews With curl
Pull 5 reviews for apple.com using the Apify API directly:
curl \"https://api.apify.com/v2/acts/cryptosignals~trustpilot-scraper/runs\" \\
-X POST \\
-H \"Content-Type: application/json\" \\
-H \"Authorization: Bearer YOUR_API_TOKEN\" \\
-d '{
\"mode\": \"reviews\",
\"businessUrl\": \"https://www.trustpilot.com/review/apple.com\",
\"maxReviews\": 5
}'
Get Reviews With Python
from apify_client import ApifyClient
client = ApifyClient(\"YOUR_API_TOKEN\")
run = client.actor(\"cryptosignals/trustpilot-scraper\").call(run_input={
\"mode\": \"reviews\",
\"businessUrl\": \"https://www.trustpilot.com/review/apple.com\",
\"maxReviews\": 100,
\"minRating\": 1,
\"maxRating\": 3,
})
for review in client.dataset(run[\"defaultDatasetId\"]).iterate_items():
print(f\"{review['rating']}/5 — {review['title']}\")
print(f\" {review['text'][:120]}...\")
print(f\" By {review['reviewerName']} ({review['country']})\")
print()
This pulls only 1-3 star reviews for Apple — useful for competitor weakness analysis.
Search Businesses by Category
run = client.actor(\"cryptosignals/trustpilot-scraper\").call(run_input={
\"mode\": \"search\",
\"searchQuery\": \"web hosting\",
\"maxResults\": 20,
})
for biz in client.dataset(run[\"defaultDatasetId\"]).iterate_items():
print(f\"{biz['name']} — {biz['trustScore']}/5 ({biz['reviewCount']} reviews)\")
Output:
Bluehost — 4.2/5 (1,847 reviews)
Web Hosting Canada — 4.7/5 (2,080 reviews)
SiteGround — 4.6/5 (3,212 reviews)
...
When to Use curl vs. an Apify Actor
For a one-time pull of 20 reviews, you can scrape Trustpilot directly. The site is server-rendered HTML — no JavaScript rendering needed. A simple requests + BeautifulSoup script works.
But when you need:
- Scale: Thousands of reviews across dozens of businesses
- Scheduling: Daily or weekly automated runs
- Pagination: Full review histories, not just page one
- Filtering: Only recent reviews, only low ratings, specific languages
- Reliability: Automatic retries, proxy rotation, monitoring
That is when an Apify Actor saves engineering time. You trade compute cost for development time — and for most B2B use cases, that trade-off makes sense.
Conclusion
The Trustpilot scraper market on Apify has been underserved. Three actors with 3.3-3.6 star ratings suggest that users are not fully satisfied with what is available. The main gaps are pagination (most actors only get the first page), filtering (no date or rating filters), and maintenance.
If you need basic review data and don't mind incomplete results, the existing options from casper11515 or nikita-sviridenko will get you started.
For production-scale collection with full pagination, search capabilities, and filtering, the Trustpilot Scraper by cryptosignals is built to handle those use cases.
All actors mentioned are available on the Apify Store. Ratings and user counts are as of March 2026.
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