TrustRadius Reviews Scraper

Pay-per-review: $2.00/1K reviews. Reviewer role + company name included. No login, no proxy, no monthly fee.

B2B software buyers trust TrustRadius more than any other review platform. This scraper gives you full review text, reviewer job title, company name, and rating — without a TrustRadius account. Perfect for competitive intelligence, NPS analysis, and building targeted account lists.

Scrape B2B software reviews from TrustRadius — the leading platform for peer reviews of enterprise software.

No proxy required — works from Apify cloud IPs without external credentials.

What you get

Field	Description
review_id	Stable MD5 hash of review slug
product	Product name
title	Review headline
rating / rating_max	Numeric rating (scale shown in rating_max)
body	Full use-cases / main review text
pros	List of listed pros
cons	List of listed cons
author	Reviewer display name
reviewer_role	Job title / role (e.g. "Director in Information Technology")
reviewer_company	Company name (e.g. "Devtics Technologies")
date	ISO 8601 review date
url	Direct link to review
aggregate_rating	Product overall rating
aggregate_count	Total number of ratings on the product
parse_confidence	0–1 quality score per record
warnings	Machine-readable quality flags

Input

{
  "productUrls": ["slack", "hubspot", "https://www.trustradius.com/products/salesforce/reviews"],
  "maxReviews": 25,
  "maxPages": 10
}

• productUrls — TrustRadius product slugs or full review URLs
• maxReviews — max reviews per product (0 = no limit)
• maxPages — max pages to fetch per product (~5 reviews/page)

Pricing example

Reviews scraped	Cost
100 reviews	$0.20
500 reviews	$1.00
1,000 reviews	$2.00
10,000 reviews	$20.00

No proxy, no login, no monthly fee — pay only for results returned.

Output sample

{
  "review_id": "a3f8b1c2d4e5f6a7",
  "product": "Slack",
  "title": "Great for async teams, but noisy at scale",
  "rating": 8,
  "rating_max": 10,
  "body": "We use Slack across 5 departments. The thread model helps async collaboration but notification fatigue is real above 20 channels.",
  "pros": ["Deep integrations", "Search history", "Mobile app quality"],
  "cons": ["Notification overload", "Channel sprawl", "Expensive at enterprise tier"],
  "author": "Jane D.",
  "reviewer_role": "Director of Engineering",
  "reviewer_company": "Acme SaaS Inc.",
  "date": "2025-11-04",
  "url": "https://www.trustradius.com/reviews/slack-2025-11-04-1",
  "aggregate_rating": 8.4,
  "aggregate_count": 1247,
  "parse_confidence": 0.95,
  "warnings": []
}

FAQ

Do I need a TrustRadius account or login? No — TrustRadius renders reviews in static HTML accessible without authentication. No account, no cookie, no proxy needed.

What export formats are available? JSON, CSV, Excel, and XML — all downloadable from the dataset page or via the Apify REST API.

Can I track competitor reviews on a schedule? Yes — enable monitoringMode: true and set up a recurring Apify Scheduler run. A low-cost monitoring charge is applied per run instead of per-review charges.

What if the actor returns 0 reviews for a product? Confirm the product slug exists on trustradius.com (e.g. slack, salesforce, hubspot). TrustRadius only serves ~5 reviews per page in static HTML; some niche products may have fewer pages.

Why this beats the competition

	This actor	Other review scrapers
reviewer_role (job title)	Yes	Rarely
reviewer_company	Yes	No
pros / cons structured	Yes (lists)	Raw text only
No login required	Yes	Often requires cookie
Rating scale preserved	Yes (rating_max)	Normalized only
parse_confidence	Yes	No
Price	$2.00/1K	$3-5/1K

Every record ships a parse_confidence score (0.0–1.0). Below 0.7 is a machine-readable signal that the page structure has drifted — your data pipeline can filter automatically.

Use with AI agents (MCP)

This scraper is callable as a tool by AI agents (Claude Desktop, Cursor, VS Code, n8n, LangGraph, CrewAI, or any MCP-compatible client) via Apify's hosted Model Context Protocol server. An agent can pull competitor reviews mid-conversation: "Give me the top 20 TrustRadius reviews for Salesforce, sorted by reviewer company size."

Point your MCP client at this tool:

{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.apify.com/?tools=bovi/trustradius-reviews",
        "--header",
        "Authorization: Bearer <YOUR_APIFY_TOKEN>"
      ]
    }
  }
}

Monitoring mode — recurring brand tracking

Set monitoringMode: true and schedule a weekly run to track competitor review velocity and rating changes. A monitoring-run event is charged once per run (priced lower than scraping new reviews) — ideal for ongoing competitive intelligence without paying full scrape cost every time.

{
  "productUrls": ["salesforce", "hubspot"],
  "maxReviews": 10,
  "monitoringMode": true
}

Schedule via Apify Scheduler (or n8n/Zapier) for hands-off brand tracking.

Notes

• TrustRadius renders ~5 reviews per page in static HTML; the rest are loaded client-side. This actor harvests the server-side rendered batch. Static HTML = fast, stable, cheap — no JS execution needed.
• reviewer_role and reviewer_company are available when the reviewer has filled in their profile.
• Not affiliated with TrustRadius.

Integrations

Built for B2B competitive-intelligence and sales teams mining enterprise software reviews with reviewer role and company data — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.