Trustpilot Reviews Scraper - Ratings & Feedback

This Trustpilot reviews scraper turns any company's Trustpilot page into a clean, analysis-ready feed — one flat row per review with the star rating, headline, full text, reviewer name and country, the review date (ISO + plain date), a verified flag, the company's reply, and a 0–100 review score for fast triage. Give it a company domain, filter to what you care about, and export to CSV, JSON, or Excel.

Built for reputation and CX teams, market researchers, founders, and analysts who want a spreadsheet of reviews — not a nested scrape. It reads only public review data: no login, no cookies.

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How to scrape Trustpilot reviews

1. Enter a company domain — e.g. pipedrive.com (or paste a full Trustpilot review URL).
2. Choose how many reviews, the sort order, and any filters (star ratings, date window, language, verified-only).
3. The scraper pulls the reviews via the proven automation-lab/trustpilot engine.
4. Each review is normalized: snake_case fields, ISO 8601 dates plus a split published_date, a boolean verified flag, and a has_reply flag.
5. Duplicates are removed, your filters applied, and every review gets a 0–100 review_score (rating + recency + verified + engagement + completeness).
6. You get a clean table to download as CSV, JSON, or Excel — or pull via API.

No coding, no Trustpilot account, no API key.

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What data you get

Every row is one review:

• Rating, title, and full text — the core review content.
• Reviewer name, country, and history — reviewer_total_reviews shows how prolific the reviewer is.
• Verified flag + raw verification level — know which reviews are verified at a glance.
• Dates — published_at (ISO 8601 UTC), published_date (YYYY-MM-DD), and experience_date.
• Company reply — has_reply, reply_text, reply_published_at, reply_updated_at.
• Likes — how many people found the review useful.
• A 0–100 review_score — blends rating, recency, verified status, engagement, and text completeness.

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Filters & options

• Star ratings — fetch only 1★, 5★, etc.
• Date window — last 30 days / 3 / 6 / 12 months.
• Languages — keep only chosen languages.
• Verified only — fetch only verified reviews.
• Search within reviews — only reviews containing a phrase.
• Minimum rating — drop reviews below N stars (applied after scraping).
• Only with a company reply — keep reviews the company answered.

Input

Field	Type	Description
companyDomain	string	Company to scrape, e.g. pipedrive.com. Required.
maxReviews	integer	Max reviews to fetch. Default 100.
sort	string	recency (newest) or relevancy.
stars	array	Only these star ratings (["1","5"]).
dateWindow	string	last30days / last3months / last6months / last12months.
languages	array	Language codes to keep.
onlyVerified	boolean	Fetch verified reviews only.
includeReplies	boolean	Include company replies. Default true.
searchText	string	Only reviews containing this text.
minRating	integer	Drop reviews below N stars (0 = no filter).
onlyWithReply	boolean	Keep only replied-to reviews.

Example input:

{
  "companyDomain": "pipedrive.com",
  "maxReviews": 200,
  "sort": "recency",
  "stars": ["1", "2"],
  "dateWindow": "last3months",
  "includeReplies": true,
  "onlyWithReply": true
}

JSON output sample

{
  "review_score": 88,
  "review_id": "6627f1a0e4b0abc123",
  "reviewer_name": "Jane D.",
  "rating": 5,
  "title": "Best CRM we've used",
  "text": "Setup took ten minutes and support replied within the hour…",
  "language": "en",
  "published_at": "2026-05-14T21:34:45+00:00",
  "published_date": "2026-05-14",
  "experience_date": "2026-05-12",
  "verified": true,
  "verification_level": "verified",
  "reviewer_country": "US",
  "reviewer_total_reviews": 3,
  "likes": 2,
  "has_reply": true,
  "reply_text": "Thanks so much for the kind words, Jane!",
  "reply_published_at": "2026-05-15T09:02:11+00:00",
  "reply_updated_at": null
}

Results render as a clean, sortable table on the Output tab and export to CSV, JSON, or Excel.

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Use cases

• Reputation monitoring — track new 1★ reviews for your brand or a competitor.
• CX analysis — pull thousands of reviews to find recurring complaints and themes.
• Competitive research — compare review sentiment and reply rates across companies.
• Review response audits — has_reply shows how responsive a company is.

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Use with AI agents & automation

Plug this into your stack: run it from the Apify MCP server so AI agents (Claude, ChatGPT, Cursor) can pull reviews as a tool call, schedule runs through Make, n8n, or Zapier to alert on new negative reviews, or sync the dataset to Google Sheets for a live reputation dashboard. Clean flat JSON drops into sentiment pipelines with no glue code.

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Pricing

Pay-per-result — you're charged only for the reviews delivered after your filters. Use maxReviews and the filters to keep cost predictable. See the Apify Store page for the current per-result price.

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FAQ

Do I need a Trustpilot account or API key? No. It reads public reviews with no login and no key.

How is verified determined? From Trustpilot's verification level — verified/invited reviews are flagged true, and the raw level is kept in verification_level.

Can I scrape a competitor's reviews? Yes — any company with a public Trustpilot page. Just use their domain.

Is scraping Trustpilot legal? This collects public reviews only. Trustpilot's terms restrict automated access and reviews contain personal data (names, countries), so handle the data lawfully (GDPR) and follow Trustpilot's terms. For research/monitoring use.

Can I export to CSV or Google Sheets? Yes — CSV, JSON, or Excel from the Output tab, or sync to Google Sheets via Make, n8n, or Zapier.

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