Trustpilot Business Search: Discover Companies by Category with TrustScore Data

If you need every business in a Trustpilot category — not the reviews for one company you already know, but the list of companies itself — there’s no official Trustpilot API for that. Trustpilot’s category and search pages are public, but they’re fronted by an AWS WAF JavaScript challenge that blocks plain HTTP requests, so a naive requests.get() call returns nothing useful.

The Trustpilot Business Search Scraper solves the discovery problem: give it a category or a keyword and it returns a structured list of companies with their TrustScore, review count, verification status and domain. That last field — domain — is the important one, because it’s what chains this actor into the Trustpilot Reviews Scraper for a full search-to-reviews pipeline.

Why You Can’t Just Scrape This With requests

Trustpilot serves every category and search page behind a WAF challenge that TLS-fingerprints the request before it ever reaches the page content. A plain HTTP client gets a challenge page, not business data. The Business Search Scraper runs a real Chromium browser (Crawlee’s PlaywrightCrawler with a full fingerprint stack) through residential proxies, which is what actually clears the challenge. Once the page renders, the actor reads business data either out of the __NEXT_DATA__ JSON island on legacy pages or directly from business-card links on the newer App-Router pages.

No account, no cookies, no API key, no third-party unblocking service — it’s Apify-native end to end.

What You Get Per Business

Each result is a flat record:

• domain — the business domain, e.g. pipedrive.com. This is the field that feeds the Reviews Scraper.
• name — display name
• trustScore — Trustpilot’s 1–5 TrustScore
• reviewsCount — total review count
• stars — star rating band
• categories — array of Trustpilot category tags
• isVerified — whether the business is verified
• isClaimed — whether the profile has been claimed by the business
• city, country — location
• logoUrl, profileUrl — logo image and the Trustpilot review page URL
• scraped_at — ISO timestamp of the scrape

Two Search Modes

The actor supports category mode and keyword mode, and they behave differently:

• Category mode browses a Trustpilot category page (e.g. electronics_technology) and paginates through it — this gives you the broadest coverage of a niche.
• Keyword mode runs a free-text search when you already know a company name or a specific term.

Search a Category in Python

import os
from apify_client import ApifyClient

apify = ApifyClient(os.environ["APIFY_TOKEN"])

run = apify.actor("themineworks/trustpilot-business-search").call(run_input={
    "query": "electronics_technology",
    "searchMode": "category",
    "maxResults": 50,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "US",
    },
})

for business in apify.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{business['name']} ({business['domain']})")
    print(f"  TrustScore: {business.get('trustScore')} — {business.get('reviewsCount', 0):,} reviews")
    print(f"  Verified: {business.get('isVerified')}  Claimed: {business.get('isClaimed')}")

Keyword Search

run = apify.actor("themineworks/trustpilot-business-search").call(run_input={
    "query": "travel insurance",
    "searchMode": "keyword",
    "maxResults": 30,
})

results = [b for b in apify.dataset(run["defaultDatasetId"]).iterate_items()]
top_rated = sorted(results, key=lambda b: b.get("trustScore", 0), reverse=True)

for b in top_rated[:10]:
    print(f"{b['trustScore']}  {b['name']}  ({b['reviewsCount']} reviews)")

Filtering for Lead Quality

A raw category pull mixes small, unclaimed profiles with established, verified businesses. If you’re building a lead list rather than a market map, filter on isClaimed, isVerified and a minimum reviewsCount so you’re not chasing companies that barely have a Trustpilot presence:

qualified_leads = [
    b for b in results
    if b.get("isClaimed") and b.get("isVerified") and b.get("reviewsCount", 0) >= 50
]

From Search to Reviews: The domain Field

Business Search is deliberately the front half of a pipeline. Every result carries a domain field, and the Reviews Scraper’s input is companyDomain — the two actors share that key so you can chain them directly:

# 1) Find businesses in a category
search_results = [b for b in apify.dataset(run["defaultDatasetId"]).iterate_items()]

# 2) Pull reviews for each one
for business in search_results[:5]:
    if not business.get("domain"):
        continue
    reviews_run = apify.actor("themineworks/trustpilot-reviews").call(run_input={
        "companyDomain": business["domain"],
        "maxResults": 100,
    })
    print(f"Pulled reviews for {business['domain']}")

For the full chained workflow with error handling and batching, see Building a Review Monitoring Pipeline: Trustpilot Business Search to Reviews in One Workflow.

Pricing

Pay-per-event at $2 per 1,000 businesses ($0.002 each), plus a small per-run start fee. Blocked pages or failed requests are never charged.

Use in an AI Agent

The actor is exposed as an MCP tool:

https://mcp.apify.com/?tools=themineworks/trustpilot-business-search

Connected to Claude or another MCP client, you can ask something like “find the top 50 electronics companies on Trustpilot with their TrustScore and review count” and get a structured answer without writing a script.

Where This Fits

Business Search is category- and keyword-agnostic — it works for SaaS, e-commerce, financial services, or any other vertical Trustpilot covers. If your use case is specifically hospitality — hotels, restaurants, attractions — Trustpilot isn’t the right source at all; see our TripAdvisor reviews guide for that instead. Trustpilot’s strength is B2B, SaaS and e-commerce companies where a TrustScore functions as a de facto reputation benchmark.