Arcadium Data Scrapers
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Trustpilot reputation monitoring

Follow your Trustpilot score and new reviews, and those of your competitors.

Steps

  1. List the Trustpilot company pages.
  2. Schedule the actor and alert on new low ratings.

Actors for this job

Trustpilot Reviews Scraper

Give it company domains or Trustpilot review pages and it returns one row per company (TrustScore, review count, star split, categories, reply rate) and one JSON row per review: stars, title, text, date, language, the verified flag and the company's reply with its date. From $0.52 per 1,000 reviews on the free plan, and you pay only for the review rows you get.

$0.52 per 1,000 reviews on the Free plan, down to $0.27 on higher plans

Apify Store · Guide · Comparison

Review Monitor

Give it a watchlist of hotels, local businesses, apps or SaaS products (their pages on Booking.com, Agoda, Trip.com, Tripadvisor, Google Maps, Google Hotels, Yelp, Google Play, the App Store, Capterra or TrustRadius) and every run returns what changed since the last one: an alert row per new 1★ or 2★ review and a summary row per entity with rating drift, 30-day vs lifetime average, owner-reply rate and lag, review velocity and, for apps, per-version rating regressions. $12 per 1,000 entity checks and $2 per 1,000 alerts; you pay only for rows you get.

$12.00 per 1,000 entities checked on the Free plan, down to $9.00 on higher plans

  • Hotel groups and franchises: one feed for every location on Booking, Tripadvisor and Yelp; reply to the new 1★ reviews first, watch ownerReplyRate90d per location.
  • Agencies: a weekly reputation report per client from the summary rows (ratingChange, rating30dVsLifetime, reviewCountChange).
  • App teams: versionRegression shows when a release averages clearly lower than the one before it; alerts carry the appVersion.

Apify Store · Guide · Comparison

Quick start

Run the first actor from Python (set APIFY_TOKEN):

# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/trustpilot-reviews").call(run_input={
    "companies": ["www.bestbuy.com"],
    "maxReviewsPerCompany": 20,
    "sort": "recency",
    "verified": False,
    "withReplies": False,
    "includeCompanyInfo": True,
    "splitFilters": True,
    "companySort": "most_relevant",
    "claimedOnly": False,
    "maxCompaniesPerCategory": 20,
    "onlyNewReviews": False,
})
items = client.dataset(run.default_dataset_id).list_items().items  # apify-client 3.x returns a Run object
print(items)

Or give an AI assistant both actors as tools:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/trustpilot-reviews,arcadium/reputation-monitor",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}