Trustpilot Reviews Scraper — Ratings, Replies & Confidence

Extract customer reviews from any Trustpilot business page. Full review fields including rating, title, text, author, country, verified status, company reply + reply date, date of experience, and derived rating distribution per star. Filter by stars (multi-select), language, and date range. Every record includes parse_confidence for structured drift detection.

Pricing: $2.00 per 1,000 reviews (pay-per-result, no subscription).

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What you get

Field	Description
business_name	Company display name on Trustpilot
business_domain	Domain (e.g. amazon.com)
overall_rating	Trust score (1.0–5.0)
total_reviews	Total review count on Trustpilot
star_5_pct … star_1_pct	Derived: % reviews at each star level
review_id	Trustpilot review UUID
url	Direct link to the review
rating	Star rating (1–5)
title	Review headline
text	Full review body
author	Reviewer display name
author_country	ISO 2-letter country code
author_review_count	Total reviews by this reviewer
author_verified	Whether reviewer profile is verified
date_published	ISO 8601 UTC publish datetime
date_experience	ISO 8601 UTC experience date
verified	Trustpilot verified purchase flag
verification_level	"verified" / "not-verified" / "invited"
language	ISO language code (e.g. "en", "de")
likes	Helpful vote count
reply	Company reply text (null if none)
reply_date	ISO 8601 UTC company reply date
page_number	Review page this was scraped from
parse_confidence	Page-level parse quality (0.0–1.0) — our reliability edge
warnings	Machine-readable warning codes

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Our edge over competitors

Feature	This actor	Most competitors
parse_confidence per record	✅	❌
Rating distribution (star_N_pct)	✅ derived	❌
reply_date (ISO)	✅	❌ or partial
Multi-star filter (e.g. [1,2])	✅	❌ (one at a time)
date_experience (ISO)	✅	❌ or partial
PPE pricing (no rental)	✅	Mixed
Under maintenance?	✅ active	Several broken

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Quick start

{
  "domains": ["amazon.com"],
  "maxReviews": 100,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

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Input parameters

Parameter	Type	Default	Description
domains	string[]	required	Company domains or full Trustpilot URLs
maxReviews	integer	100	Max reviews per company. 0 = unlimited
stars	integer[]	all	Star filter — multi-select, e.g. [1, 2]
language	string	"all"	ISO language code or "all"
dateRange	string	"all"	"all" / "last30days" / "last3months" / "last6months" / "last12months"
sort	string	"recency"	"recency" or "relevance"
proxyConfiguration	object	—	Required — use Apify Residential group

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Use cases

• Brand reputation monitoring — daily scheduled runs, filter to 1-2 stars
• Competitor analysis — compare overall_rating, star_N_pct, reply rate
• NLP / sentiment datasets — verified text + rating ground truth
• Market research — track review velocity and response patterns
• Lead generation — identify active reviewers in your niche

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Access reality (honest limits)

Trustpilot uses AWS WAF that blocks datacenter and home IP addresses with a JavaScript challenge page (HTTP 403). This is IP-reputation-based, not TLS fingerprinting — residential proxies pass through cleanly.

A proxy is required. Configure proxyConfiguration with Apify's Residential proxy group. The buyer (you) pays for proxy compute — this keeps the per-review price low.

Without a proxy you will see: Trustpilot blocked request: http_403 in logs.

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Performance

Reviews	Estimated time
100	~30–60 seconds
500	~3–5 minutes
5,000	~25–35 minutes
All (unlimited)	Depends on company size

Trustpilot shows 20 reviews per page. The actor paginates via the Next.js /_next/data/ JSON endpoint (no HTML parsing after page 1) at ~20 req/min to stay under WAF rate limits.

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Pricing

$2.00 per 1,000 reviews (PPE, pay-per-result).

Apify's free plan includes $5 credit = ~2,500 reviews at no cost.

Proxy cost (Apify Residential): ~$3.50/GB. A typical review page is ~50KB, so 1,000 reviews (50 pages) ≈ 2.5MB ≈ under $0.01 in proxy costs.

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Integrations

Built for brand and CX teams tracking reputation, mining customer sentiment, and benchmarking competitors on Trustpilot — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Legal

This actor accesses publicly visible review data on Trustpilot — the same data any browser user can see without logging in. Users are responsible for compliance with Trustpilot's Terms of Service, GDPR, and CCPA as applicable. Do not republish review content as your own. This actor is not affiliated with or endorsed by Trustpilot A/S.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Upwork Talent Scraper
• Website Contact Extractor
• Yellowpages Scraper
• Yelp Scraper
• Zoominfo Scraper
• 2GIS Places Scraper

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.