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Trustpilot Reviews — examples

Runnable examples for the Trustpilot Reviews Scraper | from $2/1K on Apify.

Scrape Trustpilot reviews for any business. Full fields: rating, title, text, author, country, verified, company reply + date, date of experience. Filter by stars (multi), language, date range. Derived: star % distribution, parse_confidence per record. Residential proxy required.

What you get per record

author · author_country · author_review_count · author_verified · business_domain · business_name · business_url · date_experience · date_published · language · likes · overall_rating · page_number · parse_confidence · rating · reply · reply_date · review_id · star_1_pct · star_2_pct · star_3_pct · star_4_pct · star_5_pct · text · title · total_reviews · url · verification_level · verified · warnings

Who uses this

  • Reputation / brand monitoring — watch a competitor's or your own Trustpilot score and new reviews over time.
  • Voice-of-customer & CX research — mine review text for recurring complaints and feature requests.
  • Lead-gen / sales intel — a wave of 1-star reviews on a rival is a displacement opening.

Quickstart

  1. Get your Apify token: https://console.apify.com/account/integrations
  2. Run a language example below. Both call the actor and print the results.
Example File
Python (apify-client) examples/python/run.py
JavaScript (apify-client) examples/javascript/run.js
Sample output (real records) examples/sample_output.json

Example input

{
  "domains": [
    "amazon.com"
  ],
  "maxReviews": 100,
  "stars": [
    "1",
    "2"
  ],
  "language": "all",
  "dateRange": "all",
  "sort": "recency",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}

Links


MIT-licensed examples. The actor runs on the caller's Apify account (you pay platform compute + per-result).

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