Trustpilot Scraper

Scrape Trustpilot reviews and export Trustpilot data to CSV, JSON, or Excel for research and reporting. This Trustpilot API alternative collects public reviews with clear inputs and structured output.

Collect public company reviews with star ratings, review text, dates, language, verification, public replies, and company context. Enter one or more company domains or Trustpilot review URLs, then filter the records that matter to your research.

What data can you extract from Trustpilot?

Each dataset row is one review. The field names below are the keys in the JSON export; optional fields remain null when the public source does not supply a value.

Field	Description	Example
reviewId	Trustpilot review ID	"6ab6e755c9f3e608a2405e8f"
reviewUrl	Direct link to the review	"https://www.trustpilot.com/reviews/6ab6e755c9f3e608a2405e8f"
rating	Stars, 1-5	1
title	Review headline	"2 weeks still my order didn't arrive"
text	Review body	"I order some coffee. After 2 weeks it still hasn't arrived. …
language	ISO language code	"en"
publishedAt	ISO date the review was published	"2026-09-25T23:27:49.000Z"
experiencedAt	Date of the experience	"2026-09-25T00:00:00.000Z"
updatedAt	Date the review was last updated, when supplied.	null
likes	Public like count on the review.	0
source	Review source label shown by Trustpilot.	"Organic"
isVerified	Verified by Trustpilot	false
verificationLevel	Verification detail label, when supplied.	"not-verified"
authorName	Public reviewer display name.	"Robin Robillard"
authorId	Public reviewer identifier.	"6400ded5e424c0001381c33f"
authorCountry	ISO country code	"US"
authorReviewCount	Public value shown with the review.	29
authorImageUrl	Public reviewer image URL, when present.	"https://user-images.trustpilot.com/6400ded5e424c0001381c33f/7…
replyText	Company's public reply	null
replyPublishedAt	Date of the public company reply, when present.	null
companyName	Company display name.	"Amazon"
companyDomain	Company domain on Trustpilot.	"www.amazon.com"
companyTrustScore	Public value shown with the review.	1.6
companyReviewCount	Company review total shown with the review.	49416
companyUrl	Trustpilot company review page URL.	"https://www.trustpilot.com/review/www.amazon.com"

How to scrape Trustpilot

1. Paste a company domain such as www.amazon.com, or its Trustpilot review URL, into companies.
2. Choose a per-company limit and a total maxItems limit if you need a bounded export.
3. Optionally choose stars, language, dateRange, verifiedOnly, or withRepliesOnly.
4. Run the actor, inspect the dataset, and download CSV, JSON, or Excel.

A run stores its results in the default dataset. Review a few rows there before exporting, especially if you plan to combine several searches or compare snapshots over time. Keep the record ID or source URL in your export so you can remove duplicates and return to the public page behind a result.

Input

Enter these values in the actor input. A prefilled example is a starting point, while a default is the value used when the field is omitted. Required inputs are identified below.

Name	Type	Default	Description
companies	array	["www.amazon.com"]	Required. Company domains (e.g. amazon.com) or Trustpilot review URLs (e.g. https://www.trustpilot.com/review/www.amazon.com).
maxReviewsPerCompany	integer	100	Stop after this many reviews per company. 0 = as many as possible.
maxItems	integer	0	Hard cap across all companies. 0 = no cap.
stars	array	[]	Only reviews with these star ratings (1-5). Empty = all.
language	string	"all"	ISO language code (en, de, fr...) or 'all'.
dateRange	string	""	Only reviews from this period.
verifiedOnly	boolean	false	Verified reviews only.
withRepliesOnly	boolean	false	Only reviews with a company reply.
proxyConfiguration	object	{"useApifyProxy": true}	Apify Proxy is used automatically; override only if needed.

A realistic input:

{
  "companies": [
    "www.amazon.com"
  ],
  "maxReviewsPerCompany": 100,
  "language": "en",
  "stars": [
    1,
    5
  ]
}

The example keeps the run small enough to inspect while showing the main search path. Increase the item limit only after the initial results match your intended scope. When multiple filters are available, start with the most important one and then refine the next run based on the public results.

Output example

The following item came from a successful published run. Long review or description text is shortened here for readability; the dataset keeps the full value.

{
  "reviewId": "6ab6e755c9f3e608a2405e8f",
  "reviewUrl": "https://www.trustpilot.com/reviews/6ab6e755c9f3e608a2405e8f",
  "rating": 1,
  "title": "2 weeks still my order didn't arrive",
  "text": "I order some coffee. After 2 weeks it still hasn't arrived.  They said it couldn't be delivered but I received other deliveries.  Now they won't refun…",
  "language": "en",
  "publishedAt": "2026-09-25T23:27:49.000Z",
  "experiencedAt": "2026-09-25T00:00:00.000Z",
  "updatedAt": null,
  "likes": 0,
  "source": "Organic",
  "isVerified": false,
  "verificationLevel": "not-verified",
  "authorName": "Robin Robillard",
  "authorId": "6400ded5e424c0001381c33f",
  "authorCountry": "US",
  "authorReviewCount": 29,
  "authorImageUrl": "https://user-images.trustpilot.com/6400ded5e424c0001381c33f/73x73.png",
  "replyText": null,
  "replyPublishedAt": null,
  "companyName": "Amazon",
  "companyDomain": "www.amazon.com",
  "companyTrustScore": 1.6,
  "companyReviewCount": 49416,
  "companyUrl": "https://www.trustpilot.com/review/www.amazon.com"
}

The example shows the shape of one record, not a guarantee that every optional value will be present in every result. CSV and Excel exports present the same fields as columns. JSON retains the native number, boolean, array, and null values that make further filtering easier.

Use cases

• Customer experience teams can watch changes in complaint themes and reply coverage for their own company.
• Market researchers can compare public ratings and review language across competing brands.
• Support leads can identify recurring service problems within a selected star rating or date window.
• Reputation analysts can compare review volume, trust score, and public response patterns.
• Localization teams can examine feedback in a particular language or country code.

These workflows use public listing or review data as a starting point. Check the linked source page before acting on a single record, because public content, counts, and availability can change after a run. Store the run date alongside each export when comparing data over time.

How much does it cost to scrape Trustpilot?

The price is $0.60 per 1,000 results, with platform usage included. Charges scale with the number of results produced: 100 results cost $0.060, 1,000 results cost $0.60, and 5,000 results cost $3.00. The 5,000-result figure is a pricing illustration, not a promise that a single search exposes that many public results. Set the item limit for the amount of data you need and check the actual result count after the run.

Tips for best results

For a large company, set a specific language or star rating to narrow the search. The actor also divides broad searches by language and stars, tries additional sort and date views, and removes duplicate review IDs. This can expose more than the first 200 reviews, but it does not guarantee every historical review. Set maxReviewsPerCompany for a balanced comparison when companies have different review volumes. Set maxItems to limit the whole run. Narrow dateRange when you need recent feedback; combine it with stars only when that smaller subset is useful. Empty stars means all ratings, and language all means all languages.

When creating a repeatable workflow, save the input that produced a useful dataset. Compare later exports by stable ID where available, and inspect a few source links whenever a value matters to a decision. A narrow input usually makes the output easier to validate and reduces time spent processing unrelated results.

Limits

Anonymous Trustpilot pages expose at most 10 pages, or about 200 reviews, for one filter combination. The actor uses multiple combinations to reach beyond that view, but some old or overlapping records can remain inaccessible. Filters change which reviews are visible; they do not promise a complete archive. Public replies, images, experience dates, update dates, and verification details may be absent. A company may have fewer public reviews than its displayed total. The actor deduplicates review IDs and stops at the supplied per-company or total limit.

These limits come from the public data exposed to the actor at run time. Source pages can change, so a run can return fewer rows than its requested maximum. A maximum item count is a stop condition, not a minimum or a guarantee of coverage. Use the source URL in each row when you need to verify a particular detail.

Use with AI agents (MCP)

The actor can be called through the Apify MCP connection with the same input fields shown above. Ask for a bounded result set and name the fields that matter to the task. A useful prompt also asks for source links, so each conclusion can be checked against its public record.

• “Collect the newest English one-star Trustpilot reviews for www.amazon.com and summarize recurring delivery complaints with review URLs.”
• “Compare five-star and one-star public reviews for two company domains, grouped by company and language.”

For recurring research, keep the search input and the requested output columns consistent. Compare records by their IDs or source URLs when results from different runs are combined. If an optional field is missing, keep it empty in downstream analysis instead of guessing a value.

FAQ

Is it legal to scrape this data? This actor reads public data. Follow the source site’s terms, applicable law, and GDPR requirements. Do not misuse personal data or republish material without the rights to do so.

Do I need to provide proxies? No. The default proxy configuration is already supplied. You can override proxyConfiguration if your workflow requires different settings.

How fast is a run? Time depends on the number of pages or products, the selected limits, and how quickly public pages respond. Start with a small limit to estimate the time for your search; fetching optional detail pages can add time.

Can I schedule and monitor runs? Yes. Use Apify scheduling and run monitoring for repeat collections. Save each run’s dataset so you can compare snapshots and spot missing or changed records.

Can I export to Google Sheets or Excel? Yes. Download CSV, JSON, or Excel from the dataset, or connect the dataset to Google Sheets through an integration. Keep IDs or URLs as columns for deduplication.

What if a field is empty? The public source did not supply that value for the record, or the value was unavailable in the view used. Treat null as missing data, not as zero or a negative answer.

Does a company domain work instead of a URL? Yes. Enter a domain such as www.amazon.com in companies; full Trustpilot review URLs are accepted too.

Can I request only one-star reviews? Yes. Set stars to [1], or include several ratings in the array.

Can I get more than 200 reviews? Often. The actor slices broad result sets, though public view limits mean full historical coverage is not guaranteed.

Integrations

Use the Apify API to start runs and read the default dataset. Webhooks can notify another system when a run finishes; Zapier, Make, and n8n can move results into reporting workflows or Google Sheets. Scheduling supports regular snapshots, and exported CSV or Excel files work for manual analysis. Keep the source record ID and URL in downstream systems so updates can be matched to earlier exports.

Support

Open an issue on the Issues tab; we reply within 24h and add fields on request.