Structured Trustpilot business reviews with star ratings, review text, verification status, company profiles, business replies, and review dates.
Reputation teams, market researchers, and sentiment-analysis developers
The exact schema depends on the collection. These are the commonly available fields to validate in your sample.
review_idbusiness_namebusiness_domaintrustscoreratingreview_titlereview_textreview_dateverified_statusconsumer_countrybusiness_replyreply_dateThis anonymized, illustrative record shows the expected shape. Confirm actual fields and values using the sample for your selected collection.
{
"review_id": "TP_72C91",
"business_name": "Example Company",
"business_domain": "example.com",
"trustscore": 4.3,
"rating": 4,
"review_title": "Responsive support",
"review_text": "The support team resolved my issue quickly.",
"review_date": "2026-08-21",
"verified_status": "verified",
"consumer_country": "GB",
"business_reply": "Thank you for sharing your experience."
}Classify review sentiment and compare rating-to-text agreement.
Identify recurring product, service, feature, or support themes.
Compare ratings, review volume, response patterns, and customer concerns.
Develop retrieval, summarization, classification, and language-analysis workflows.
Measure how feedback changes by version, business, market, or time period.
Before purchasing or training a model, verify the collection date, geographic and language coverage, rating distribution, duplicate rate, missing fields, deleted-content policy, and source-specific limitations.
A current snapshot is suitable for present-state analysis. Measuring changes over time requires dated recurring snapshots collected with a consistent method.
Scope the collection by app, business, country, language, rating, or date range when those filters are exposed by Trustpilot. We can also discuss recurring delivery and a normalized schema.
Discuss your review data requirementsCompare mobile app, business, product, and hotel review collections from the main reviews hub.