B2B product teams, sales enablement managers, and competitive intelligence analysts need structured review data from TrustRadius — but there's no public API, scraping is blocked, and data quality is guarded as a Gartner-adjacent asset.
Why TrustRadius Data Matters for B2B
- Competitor weakness analysis from verified user reviews
- Feature gap identification (what users wish your competitor had)
- Win/loss analysis: understand why deals close or fall through
- Product positioning based on real user sentiment
The Collection Challenge
- No public API available
- Anti-scraping measures protect review content
- Reviews span thousands of software categories
- Gartner-adjacent quality means data is actively guarded
Automated Collection with Apify
from apify_client import ApifyClient
client = ApifyClient("YOUR_API_TOKEN")
run_input = {
"category": "CRM Software",
"competitors": ["salesforce", "hubspot", "pipedrive"],
"maxReviews": 500
}
run = client.actor("your-actor-id").call(run_input=run_input)
dataset = client.dataset(run["defaultDatasetId"]).list_items().items
for review in dataset:
print(f"{review['product']} | Rating: {review.get('rating')} | Pros: {review.get('pros')[:100]}")
Check our Apify profile for B2B review scrapers that handle TrustRadius's protections.
Business Use Cases
- Product teams: prioritize features based on competitor review complaints
- Sales teams: build battlecards from verified user feedback
- Marketing: extract testimonial themes for positioning
- Analysts: track sentiment trends across software categories over time
Getting Started
Ready to turn B2B reviews into competitive advantage? Create a free Apify account and start collecting review intelligence. Browse our scraper catalog for the right tool.
Skip the Build
You don't have to reinvent this. We maintain a production-grade scraper as an Apify actor — proxies, anti-bot, retries, and schema all handled. You can run it on a pay-per-result basis and get clean JSON without writing a single line of scraping code.
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