🥃 Trustpilot Reviews Scraper API: Extract Verified Company Reviews, Ratings & Customer Feedback at Scale

The Trustpilot Reviews Scraper by The Wolves is an Apify Actor that extracts customer reviews, star ratings, verification status, experience dates, reviewer profiles, and engagement data from any Trustpilot company page. This trustpilot review scraper api delivers 11 structured fields per review at speeds of 100-200 reviews per second — with no proxy configuration required on your end.

$0.50 per 1,000 reviews. Scrape Trustpilot reviews from any company listing at scale. Every review includes the verified/unverified distinction, experience date (when the customer actually used the product, not just when they wrote the review), and a likes count that signals review visibility and social proof.

Built by The Wolves — a pack of data scientists with over a decade of experience in web scraping and API development. We build scrapers the way data teams actually need them: rich output, precise filtering, and pricing that scales.

Limitation: The scraper extracts the first 10 pages per URL (200 reviews per company URL, at 20 reviews per page). To collect more reviews from a single company, use multiple URL variations or page offsets where available.

Pricing: $0.50 per 1,000 reviews | 100-200 reviews/second | No proxy setup required

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Table of Contents

1. What Does the Trustpilot Reviews Scraper Do?
2. Features and Capabilities
3. Pricing
4. Input Parameters
5. Output Format and Data Fields
6. Custom Map Function
7. AI Agent Integration via MCP
8. The Wolves Scraper Pack
9. Demo Mode and Free Testing
10. Automated Scheduling and Monitoring
11. Quick Start Guide
12. Use Cases and Industries
13. Troubleshooting
14. Frequently Asked Questions
15. Contact

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What Does the Trustpilot Reviews Scraper Do?

Trustpilot review extraction is the automated process of collecting customer reviews, ratings, verification status, and reviewer metadata from Trustpilot company pages. Trustpilot hosts over 300 million reviews across 1 million+ business profiles — making it the largest dedicated business review platform, particularly strong in e-commerce, SaaS, financial services, and B2B.

The Wolves Trustpilot Reviews Scraper extracts structured review data that includes fields most scrapers overlook. Each review comes with a verified/unverified flag, an experience date (distinct from the publish date), likes count, and reviewer country code — data points that are critical for credible sentiment analysis and review quality assessment.

The distinction between experience date and publish date matters. A customer might use a product in January but write the review in March. When you're tracking post-launch sentiment or measuring support response impact, the experience date gives you the accurate timeline — not the publish date.

What You Get From Every Review

Review Content and Rating

• Full review body text and title
• Star rating (1–5)
• Verified or unverified status
• Likes count (social proof indicator)

Date Intelligence

• Experience date (when the customer used the product/service)
• Published date (when the review was posted)
• Updated date (when the review was last modified)

Reviewer Profile

• Reviewer name
• Country code
• Unique reviewer ID

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Features and Capabilities

Input Flexibility

Input Type	Example	Best For
Trustpilot Company URL	https://www.trustpilot.com/review/apify.com	Targeting a specific company's reviews

Core Capabilities

• High-Speed Extraction — 100-200 reviews per second
• Verified Status — Distinguish between verified and unverified reviews
• Experience Date Tracking — Know when the customer actually used the product, not just when they wrote the review
• Likes Count — Measure review visibility and social proof
• Triple Date Fields — Experience date, publish date, and update date per review
• Reviewer Country — Country code for geographic analysis
• No Proxy Required — The scraper handles proxy rotation internally
• Custom Map Function — Transform output with custom JavaScript before saving
• Multiple Export Formats — JSON, CSV, Excel direct download
• API Integration — RESTful API for Python, Node.js, or any HTTP client

Known Limitations

• 200 reviews per URL — The scraper extracts the first 10 pages per URL (20 reviews per page = 200 reviews). This is a per-URL limit, not a total limit — you can provide multiple URLs to collect more data.

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Pricing

Pay-Per-Review Pricing

No subscriptions, no rentals, no minimum commitments. You pay only for the reviews you extract:

Metric	Price
Per 1,000 reviews	$0.50
Per review	$0.0005
Per 100,000 reviews	$50.00

Example: Extracting 200 reviews from 25 companies (5,000 reviews total) costs $2.50. Monitoring your top competitors monthly on Trustpilot keeps costs predictable and low.

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Input Parameters

Field	Type	Description	Default
startUrls	array	Trustpilot company review URLs. The scraper extracts the first 10 pages (200 reviews) per URL	[]
maxItems	number	Maximum number of reviews to output	Infinity
customMapFunction	string	JavaScript function to transform each review object (transformation only, not filtering)	null

Input Examples

Single Company — All Available Reviews:

{
    "startUrls": [
        "https://www.trustpilot.com/review/apify.com"
    ],
    "maxItems": 200
}

Multiple Companies — Competitive Analysis:

{
    "startUrls": [
        "https://www.trustpilot.com/review/apify.com",
        "https://www.trustpilot.com/review/octoparse.com",
        "https://www.trustpilot.com/review/parsehub.com"
    ],
    "maxItems": 600
}

Limited Output — Quick Sample:

{
    "startUrls": [
        "https://www.trustpilot.com/review/apify.com"
    ],
    "maxItems": 50
}

Output Format and Data Fields

Each extracted review is a structured JSON object containing 11 fields. Here is a sample:

{
    "id": "663c7bd3350fc6a8eb8960b7",
    "user": {
        "name": "User Name",
        "countryCode": "FR",
        "id": "669c7bcbc225536a02f1f7e6"
    },
    "experiencedDate": "2024-05-07T00:00:00.000Z",
    "updatedDate": "2024-05-12T00:00:00.000Z",
    "publishedDate": "2024-05-09T09:31:32.000Z",
    "title": "Great customer care!",
    "body": "Awesome! Apify customer support is what set them apart from the competition. Love the tool and love the fact that they are customer-centric.",
    "rating": 5,
    "likes": 120,
    "isVerified": false
}

Complete Field Reference

Field	Type	Description
id	string	Unique Trustpilot review identifier
user.name	string	Reviewer's display name
user.countryCode	string	Reviewer's country code (e.g., FR, US, GB)
user.id	string	Unique Trustpilot reviewer identifier
experiencedDate	string	ISO 8601 date when the customer used the product/service
updatedDate	string	ISO 8601 date when the review was last modified
publishedDate	string	ISO 8601 date when the review was published
title	string	Review title/headline
body	string	Full review body text
rating	number	Star rating (1-5)
likes	number	Number of likes/upvotes from other users
isVerified	boolean	Whether the review is verified by Trustpilot

Data Fields by Use Case

Use Case	Key Fields
B2B/SaaS Sentiment Analysis	body, title, rating, experiencedDate, isVerified
Review Credibility Assessment	isVerified, likes, user.countryCode, experiencedDate vs publishedDate
Competitive Benchmarking	rating, body, title, publishedDate, isVerified
Geographic Market Analysis	user.countryCode, rating, body, experiencedDate
Customer Support Impact Tracking	experiencedDate, publishedDate, rating, body, updatedDate
NLP Training Data	body, title, rating (as label), isVerified (as quality filter)

Why Three Date Fields Matter

Date Field	What It Tells You	Best For
experiencedDate	When the customer actually used the product	Post-launch tracking, support impact measurement
publishedDate	When the review was written	Monitoring review volume trends
updatedDate	When the review was last edited	Detecting sentiment changes over time

Example: A customer experiences a product on January 15, writes a 2-star review on February 10, then updates it to 4 stars on March 5 after receiving great support. All three dates are captured — enabling you to measure the full customer journey and support impact.

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Custom Map Function

Transform each review before it's saved to the dataset. The customMapFunction parameter accepts a JavaScript function that reshapes every review object. Use this to flatten nested structures, rename properties, or compute derived values.

Important: The custom map function is for transformation only, not filtering. Do not use it for filtering purposes.

Example: Flatten for Spreadsheet Analysis

(review) => ({
    id: review.id,
    reviewer: review.user?.name,
    country: review.user?.countryCode,
    rating: review.rating,
    title: review.title,
    body: review.body,
    experienceDate: review.experiencedDate,
    publishDate: review.publishedDate,
    updatedDate: review.updatedDate,
    likes: review.likes,
    verified: review.isVerified
})

Example: Extract for Cross-Platform Comparison

(review) => ({
    platform: "Trustpilot",
    rating: review.rating,
    text: review.body,
    title: review.title,
    date: review.publishedDate,
    reviewer: review.user?.name,
    country: review.user?.countryCode,
    verified: review.isVerified
})

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AI Agent Integration via MCP

Apify provides a hosted Model Context Protocol (MCP) server at mcp.apify.com that allows AI agents and LLM-based applications to discover and run Apify Actors as tools — including this Trustpilot Reviews Scraper.

What This Means

If you're building AI agents using Claude Desktop, VS Code with MCP support, or any framework that implements the MCP specification, you can give your agent the ability to extract Trustpilot reviews autonomously. The agent can call this scraper as a tool, receive structured JSON results with verification status and experience dates, and use them in downstream analysis.

How to Connect

Add this scraper to your MCP client configuration:

https://mcp.apify.com?tools=thewolves/trustpilot-reviews-scraper

Or use the CLI for local development:

$npx @apify/actors-mcp-server --tools thewolves/trustpilot-reviews-scraper

Use Cases for AI Agent Integration

• Automated reputation monitoring — An AI agent extracts Trustpilot reviews weekly, summarizes sentiment trends, and flags companies where ratings are dropping or where negative verified reviews are spiking.
• Competitive intelligence pipelines — Extract reviews from competitor Trustpilot pages, compare verified vs unverified review ratios, and generate strategic reports automatically.
• Multi-platform analysis — Combine Trustpilot reviews with TripAdvisor or Google Play reviews in a single agent workflow for unified cross-platform reputation reporting.

For full setup instructions, see the Apify MCP documentation.

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The Wolves Scraper Pack

All tools below are built and maintained by The Wolves — a pack of data scientists with over a decade of experience building high-performance scrapers and APIs. Powerful, easy to use, and priced for scale.

Tool	Platform	Price	Best For
Trustpilot Reviews Scraper	Trustpilot	$0.50/1K reviews	B2B/SaaS reputation analysis (You are here)
TripAdvisor Reviews Scraper	TripAdvisor	$0.50/1K reviews	Hospitality intelligence
Google Play Reviews Scraper	Google Play	$0.10/1K reviews	Android app intelligence
App Store Reviews Scraper	Apple App Store	$0.10/1K reviews	iOS app intelligence

What Makes The Wolves Trustpilot Scraper Different

Capability	This Tool	Basic Alternatives
Verified/unverified status	Per-review flag	Not available
Experience date	Separate from publish date	Publish date only
Updated date	Tracks review edits	Not available
Likes count	Social proof metric	Not available
Reviewer country	Country code per reviewer	Not available
Proxy management	Handled internally	User must configure
Speed	100-200 reviews/second	Varies

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Demo Mode and Free Testing

Free plan users can test this Trustpilot reviews scraper in Demo Mode with a maximum of 10 items per run. Demo Mode is designed to validate the output format, data quality, and field coverage before committing to larger runs.

Demo Mode Limitations:

• Maximum 10 reviews per run
• API access not available on Free plan
• Full functionality requires a paid Apify plan

How to Test:

• Run the scraper with maxItems: 10 to preview the output structure
• Verify that isVerified, experiencedDate, and likes fields are present
• Test the customMapFunction with a sample transformation
• Confirm the output matches your pipeline requirements

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Automated Scheduling and Monitoring

Trustpilot reviews appear continuously. For e-commerce brands, SaaS companies, and reputation management agencies, automated recurring runs ensure you capture new customer feedback as it's posted.

Why Schedule Review Extraction?

• Brand monitoring — Detect negative reviews early and respond before they accumulate
• Competitive tracking — Monitor competitor Trustpilot pages weekly for rating shifts
• Product launch tracking — Use experiencedDate to measure customer sentiment after releases
• Support impact analysis — Track whether support improvements correlate with better reviews over time
• Agency reporting — Automated data collection for client reputation dashboards

How to Set Up Scheduled Runs

1. Open the Actor in Apify Console
2. Configure your input parameters (startUrls, maxItems)
3. Click Schedule and set frequency (daily, weekly, monthly)
4. Optionally add a webhook to push new data to your pipeline

Webhook Integration

Combine scheduled runs with webhooks to build fully automated review monitoring:

Scheduled Run -> New Reviews Extracted -> Webhook fires -> Your system receives data

Use webhooks to trigger:

• Slack alerts for 1-star verified reviews requiring immediate response
• Database updates with new review data
• Dashboard refreshes for reputation analytics platforms
• Email digests summarizing weekly customer sentiment trends

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Quick Start Guide

For Non-Technical Users (Apify Console)

1. Go to Trustpilot Reviews Scraper on Apify
2. Click Try for free
3. Paste a Trustpilot company URL (e.g., https://www.trustpilot.com/review/apify.com) into the startUrls field
4. Set maxItems (up to 200 per URL)
5. Click Start and wait for results
6. Export Trustpilot reviews to CSV from the Storage tab

For Developers (Python API)

from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
run = client.actor("thewolves/trustpilot-reviews-scraper").call(run_input={
    "startUrls": [
        "https://www.trustpilot.com/review/apify.com"
    ],
    "maxItems": 200
})
items = client.dataset(run["defaultDatasetId"]).list_items().items

For Competitive Analysis (Multi-Company)

{
    "startUrls": [
        "https://www.trustpilot.com/review/COMPANY_A.com",
        "https://www.trustpilot.com/review/COMPANY_B.com",
        "https://www.trustpilot.com/review/COMPANY_C.com"
    ],
    "maxItems": 600
}

Extract 200 reviews from each competitor in a single run. Use the customMapFunction to add a company field derived from the URL for easy segmentation in analysis.

For Data Scientists (Verified Review Analysis)

Use the customMapFunction to separate verified from unverified reviews and compute review age:

(review) => ({
    rating: review.rating,
    text: review.body,
    verified: review.isVerified,
    country: review.user?.countryCode,
    experienceDate: review.experiencedDate,
    publishDate: review.publishedDate,
    daysBetweenExperienceAndReview: Math.round(
        (new Date(review.publishedDate) - new Date(review.experiencedDate)) / (1000 * 60 * 60 * 24)
    ),
    likes: review.likes
})

This produces a flat dataset with a computed daysBetweenExperienceAndReview field — useful for analyzing whether delayed reviews tend to be more positive or negative.

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Use Cases and Industries

E-Commerce Reputation Monitoring

Extract Trustpilot reviews from your own company page and competitor pages to track customer satisfaction over time. The verified/unverified distinction is critical for e-commerce — verified reviews carry more weight with potential customers and are more reliable for internal analytics. Track the likes count to identify which negative reviews are most visible to potential buyers.

Key fields: rating, body, isVerified, likes, publishedDate, user.countryCode

SaaS and B2B Customer Feedback

Trustpilot is increasingly used by SaaS companies and B2B service providers. Extract reviews to understand customer pain points, measure satisfaction after product updates, and identify feature requests. The experiencedDate field lets you correlate reviews with specific product releases or service changes.

Key fields: body, title, rating, experiencedDate, isVerified

Competitive Benchmarking

Extract reviews from multiple companies in the same industry to compare customer sentiment, identify competitive advantages, and discover common pain points. Run multi-company extractions in a single scraper run. The isVerified flag helps ensure you're comparing apples to apples — verified reviews only.

Key fields: rating, body, title, isVerified, publishedDate

Geographic Market Analysis

Use the user.countryCode field to segment reviews by geography. Understand how customer satisfaction varies across markets. A SaaS product might have excellent reviews from US customers but complaints about localization from European markets — data that drives targeted product improvements.

Key fields: user.countryCode, rating, body, experiencedDate

Customer Support Impact Measurement

The triple date fields (experiencedDate, publishedDate, updatedDate) enable sophisticated support impact analysis. Track whether customers who received support update their reviews to higher ratings. Measure the time gap between experience and review publication — shorter gaps often correlate with stronger emotional responses (both positive and negative).

Key fields: experiencedDate, publishedDate, updatedDate, rating, body

NLP and Sentiment Analysis Training

Extract Trustpilot reviews with ratings as sentiment labels for training classifiers. The isVerified field serves as a quality filter — verified reviews tend to be more substantive and representative. The likes count indicates which reviews resonate with the community, useful for weighting training examples.

Key fields: body, title, rating, isVerified, likes, user.countryCode

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Troubleshooting

Common Issues and Solutions

Issue	Cause	Solution
Only 200 reviews returned	10-page per-URL limit	This is a per-URL limit. Provide additional URLs to collect more reviews
Getting more results than requested	High-speed extraction overshoots slightly	You are billed only for the number you requested, not the extra results delivered
Missing data in output	Results stored in Apify dataset	Navigate to the "Storage" tab and select "Download the results" or "Open in a New Tab"
Empty results	Invalid URL format	Ensure you're using a valid Trustpilot company URL (e.g., https://www.trustpilot.com/review/company.com)
Some reviews show isVerified as false	Not all reviews are verified by Trustpilot	This is accurate data — not all reviewers complete the verification process

Performance Tips

• Start small: Test with maxItems: 10 (Demo Mode) to validate your setup before scaling
• Multiple companies in one run: Provide multiple URLs in the startUrls array for competitive analysis
• Flatten nested data: Use the customMapFunction to produce flat, analysis-ready output
• Monitor billing: You are billed per review extracted, not per maxItems setting — if fewer reviews exist, you pay only for what's delivered
• Schedule strategically: Run weekly extractions with the same URLs to build a time-series dataset of review trends

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Frequently Asked Questions

What Trustpilot review data can I extract?

Extract review text, titles, star ratings (1-5), verified/unverified status, experience dates, publish dates, update dates, reviewer names, reviewer country codes, reviewer IDs, and likes count — all in structured JSON or CSV format.

Can I export Trustpilot reviews to CSV?

Yes. Download Trustpilot reviews directly from Apify Console in JSON, CSV, or Excel format. Use the customMapFunction to flatten nested objects (like the user profile) into a single-row-per-review format ideal for spreadsheets.

Why is there a 200-review limit per URL?

The scraper extracts the first 10 pages per URL (20 reviews per page = 200 reviews). This is a per-URL limit, not a total limit. You can provide multiple company URLs in the startUrls array to collect reviews from many companies in a single run.

What does the isVerified field mean?

The isVerified field indicates whether Trustpilot has verified that the reviewer actually had an experience with the company. Verified reviews are generally more credible and are given higher visibility on Trustpilot. This field is valuable for filtering training data or weighting sentiment analysis results.

What is the difference between experiencedDate and publishedDate?

The experiencedDate is when the customer actually used the product or service. The publishedDate is when they wrote and posted the review. These can differ by days, weeks, or even months. For post-launch sentiment tracking or support impact analysis, the experiencedDate provides the accurate timeline.

Can I scrape reviews from multiple companies at once?

Yes. Provide multiple Trustpilot company URLs in the startUrls array (e.g., ["https://www.trustpilot.com/review/company-a.com", "https://www.trustpilot.com/review/company-b.com"]). Each company's reviews are extracted within a single Actor run.

Can I use Python to scrape Trustpilot reviews?

Yes. Full Python support via the Apify Client library. See the Quick Start Guide for Python integration with client.actor("thewolves/trustpilot-reviews-scraper").

Can AI agents use this scraper?

Yes. Through Apify's Model Context Protocol (MCP) server, AI agents built with Claude Desktop, VS Code, or any MCP-compatible framework can call this scraper as a tool. This enables automated reputation monitoring, competitive analysis, and multi-platform review pipelines. See AI Agent Integration via MCP for setup details.

How fast is the extraction?

100-200 reviews per second, depending on the company listing and Trustpilot's response times. This scraper is optimized for maximum throughput with internal proxy management.

Do I need to set up proxies?

No. This scraper handles all proxy rotation internally. You don't need to configure, purchase, or manage any proxy infrastructure.

Does this extract company TrustScores?

This scraper focuses on individual reviews, not company-level aggregate data. Each review includes the reviewer's star rating (1-5), but the overall company TrustScore is not extracted per review.

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Contact

Built by The Wolves — a pack of data scientists with over a decade of experience building scrapers and APIs. We build them powerful, we build them fast, and we price them fair.

For questions, feature requests, or support:

• Discord: Reach out to Tommy the Wolf — always available

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Ready to extract Trustpilot review data at scale? At $0.50 per 1,000 reviews with 100-200 reviews/second, verified/unverified review tracking, triple date fields, and reviewer country data, this Trustpilot Reviews Scraper API by The Wolves delivers the data B2B and e-commerce teams need for credible reputation intelligence. Start scraping today.