TrustRadius Reviews Scraper

Pull B2B software reviews from TrustRadius at scale — overall ratings, per-feature scores, pros, cons, ROI write-ups, alternatives considered, likelihood-to-recommend reasoning, and reviewer firmographics for every product on the platform. Built for competitive intelligence teams, product marketers, and sales analysts who need fresh customer-voice data for objection handling, positioning, and win/loss research without manually copying reviews one by one.

Why This Scraper?

• 43 fields per review — captures everything TrustRadius surfaces: overall rating, letter grade, per-feature scores, pros, cons, ROI text, alternatives considered, "other software used", trust badge tier, structured Q&A sections, reviewer firmographics, and per-reviewer verification status (LinkedIn or screenshot proof).
• Per-feature rating breakdown — every review's individual feature scores (ease of use, customer support, integrations, reporting, etc.) returned as a [{feature, score}] array — gold for feature-gap analysis.
• Four sort orders — Most Recent, Most Relevant, Most Positive, Most Critical. Pair "Most Critical" with a max cap to mine pain-point language for sales objection handling.
• Five-tier star filter and three company-size buckets — pull only 5-star reviews, only 1-star reviews, only mid-market (51–1,000 employees), or any combination — server-side filtering, no paid rows wasted.
• Date range filtering with smart short-circuit — set reviewsStartDate with sort = "Most Recent" and the scraper stops paginating as soon as it crosses the cutoff, making nightly incremental runs cheap.
• Multi-product runs — queue a portfolio of competitor products in a single job. The competitor's actor only accepts one URL at a time.
• Search by product name, not just URL — type "HubSpot" or "Salesforce" and the scraper resolves it to the right product page automatically.
• Privacy-by-default reviewer block — reviewer email is never extracted, and a single includeReviewerInfo toggle strips all firmographics (name, title, company, industry, LinkedIn, years experience) for GDPR-sensitive workflows.
• Flat $2.30 per 1,000 reviews — undercuts every subscription tier of the closest TrustRadius scraper on the platform without requiring an Apify paid plan.

Use Cases

Competitive Intelligence

• Track every new review of a competitor's product as it lands
• Compare your product's pros/cons against the leader in your category
• Flag reviews mentioning specific feature gaps or pricing complaints
• Build a sentiment timeline across product releases

Sales Enablement & Objection Handling

• Mine "Most Critical" reviews for the exact language your prospects use when comparing vendors
• Surface reviews that name your product in alternativesConsidered to learn why deals were lost
• Pull customer ROI quotes for case-study and battlecard content
• Build talk-tracks from real "what we like / what we don't" patterns

Product Marketing & Positioning

• Identify the top 5 features users praise — use those as homepage proof points
• Find feature requests buried in cons sections to feed the roadmap
• Compare per-feature ratings across your product and competitors
• Quantify NPS-style likelihood-to-recommend by company size

VC & Strategy Research

• Score sentiment trends over time during pre-investment due diligence
• Compare review volume and quality across companies in a target category
• Aggregate reviewer firmographics to validate ICP claims
• Track how a product's average rating moves quarter over quarter

Customer Insights & Lead Research

• Find heavy users of competing tools by industry and company size
• Build outreach lists segmented by reviewer role and department
• Identify products that show up alongside yours in otherSoftwareUsed
• Spot upsell signals — power users describing workarounds

Getting Started

Quick Start — One Product

{
    "productUrls": ["https://www.trustradius.com/products/notion/reviews"],
    "maxReviewsPerProduct": 100
}

Search by Product Name

No URL needed — the scraper resolves names to the right product page:

{
    "searchTerms": ["HubSpot", "Salesforce", "Pipedrive"],
    "maxReviewsPerProduct": 200,
    "sortBy": "recent"
}

Pain-Point Mining (Sales / PMM)

Pull only critical reviews for objection-handling research:

{
    "productUrls": ["https://www.trustradius.com/products/zoom-workplace/reviews"],
    "maxReviewsPerProduct": 150,
    "sortBy": "critical",
    "starRating": ["1", "2", "3"],
    "includeReviewerInfo": true
}

Incremental Daily Run

Pair date range with "Most Recent" — collection auto-stops when it crosses the cutoff:

{
    "productUrls": [
        "https://www.trustradius.com/products/asana/reviews",
        "https://www.trustradius.com/products/monday/reviews",
        "https://www.trustradius.com/products/clickup/reviews"
    ],
    "maxReviewsPerProduct": 0,
    "sortBy": "recent",
    "reviewsStartDate": "2026-04-01"
}

Mid-Market 5-Star Reviews — Lean Output

{
    "searchTerms": ["Tableau", "Looker", "Power BI"],
    "maxReviewsPerProduct": 50,
    "sortBy": "positive",
    "starRating": ["5"],
    "companySize": ["medium"],
    "includeReviewerInfo": false
}

Input Reference

What to Scrape

Parameter	Type	Default	Description
productUrls	string[]	["https://www.trustradius.com/products/zoom-workplace/reviews"]	TrustRadius product reviews page URLs. Add as many products as you like — they all run in one job.
searchTerms	string[]	[]	Product names to look up on TrustRadius (e.g. "Salesforce", "HubSpot"). Used when you don't have direct URLs — each name resolves to its top-matching product.

Limits

Parameter	Type	Default	Description
maxReviewsPerProduct	integer	100	Maximum reviews to collect per product. You pay per review — keep this low for test runs. Set to 0 to pull every review on the product (an internal upper cap protects against runaway pagination).

Filters

Parameter	Type	Default	Description
sortBy	select	Most Recent	Order returned reviews: Most Recent, Most Relevant, Most Positive, or Most Critical. Affects which reviews you get when capped.
starRating	string[]	[]	Only collect reviews with these star ratings (1–5). Multi-select. Empty = all ratings.
companySize	string[]	[]	Only collect reviews from companies of these sizes: Small (1–50 employees), Medium (51–1,000), Large (1,001+). Multi-select. Empty = all sizes.
reviewsStartDate	string	null	Only collect reviews posted on or after this date (YYYY-MM-DD). Pair with sortBy = Most Recent for cheap incremental runs.
reviewsEndDate	string	null	Only collect reviews posted on or before this date (YYYY-MM-DD).

Output

Parameter	Type	Default	Description
includeReviewerInfo	boolean	true	Include reviewer firmographics: name, job title, department, industry, company, company size, years of experience, LinkedIn URL, and avatar. Disable for a leaner, GDPR-friendly output that strips reviewer-level identifiers.

Output

Each row is one review. Here's a representative result:

{
    "url": "https://www.trustradius.com/reviews/notion-makes-collaboration-effortless-2026-04-15",
    "slug": "notion-makes-collaboration-effortless-2026-04-15",
    "heading": "Notion makes cross-team collaboration effortless",
    "rating": 9,
    "grade": "A",
    "publishedDate": "2026-04-15T00:00:00Z",
    "editedDate": null,
    "productName": "Notion",
    "productSlug": "notion",
    "productUrl": "https://www.trustradius.com/products/notion/reviews/all",
    "productLogo": "https://images.trustradius.com/notion-square180.png",
    "vendorName": "Notion Labs",
    "categories": ["Knowledge Management", "Note-Taking", "Project Management"],
    "primaryCategory": "Knowledge Management",
    "useCases": "We use Notion across product, design, and engineering for specs, runbooks, and OKRs...",
    "pros": ["Flexible page templates", "Real-time collaboration", "Powerful databases"],
    "cons": ["Mobile app slower than desktop", "Search across workspaces is weak"],
    "likelihoodToRecommendScore": 9,
    "likelihoodToRecommend": "Excellent for cross-functional teams that need a single source of truth...",
    "roi": "Replaced Confluence and saved roughly $14k/year in licensing while doubling adoption.",
    "alternativesConsidered": ["Confluence", "Coda", "Almanac"],
    "alternativesFollowup": "Notion's database flexibility tipped the decision...",
    "featureRatings": [
        { "feature": "Ease of use", "score": 9, "notApplicable": false },
        { "feature": "Customer support", "score": 7, "notApplicable": false }
    ],
    "otherSoftwareUsed": ["Slack", "Linear", "Figma"],
    "sections": [
        { "title": "Overall Satisfaction", "questions": [ { "publicTitle": "Likelihood to Recommend", "text": "Excellent for cross-functional teams..." } ] }
    ],
    "trustBadge": "TrustRadius Top Rated 2026",
    "reviewerName": "Jane Doe",
    "reviewerFirstName": "Jane",
    "reviewerLastName": "Doe",
    "reviewerTitle": "Director of Product Operations",
    "reviewerJobType": "Manager",
    "reviewerDepartment": "Product",
    "reviewerCompany": "Acme SaaS Inc.",
    "reviewerCompanySize": "201-500 employees",
    "reviewerCompanySizeGroup": "medium",
    "reviewerIndustry": "Computer Software",
    "reviewerYearsExperience": 11,
    "reviewerRoles": ["Decision-maker", "End-user"],
    "reviewerLinkedInUrl": "https://www.linkedin.com/in/jane-doe-example",
    "reviewerAvatarUrl": "https://images.trustradius.com/avatars/jane-doe.png",
    "reviewerIsVerified": true,
    "reviewerVerifiedBy": "LinkedIn",
    "scrapedAt": "2026-05-08T14:30:00Z"
}

Review Identity

Field	Type	Description
url	string	Direct URL to the review on TrustRadius
slug	string	Review slug used in the URL
heading	string	Reviewer's headline for the review
publishedDate	string	When the review was first published (ISO 8601)
editedDate	string	When the review was last edited (null if never)
scrapedAt	string	When this row was collected (ISO 8601)

Product Context

Field	Type	Description
productName	string	Product reviewed
productSlug	string	Product slug
productUrl	string	Normalized product reviews URL
productLogo	string	Product logo image URL
vendorName	string	Vendor / company that makes the product
categories	string[]	All TrustRadius categories the product is listed under
primaryCategory	string	Primary product category
trustBadge	string	TrustRadius badge tier (e.g. "Top Rated 2026"), if assigned

Ratings

Field	Type	Description
rating	number	Overall rating on TrustRadius's 1–10 scale
grade	string	Letter grade derived from rating (e.g. "A", "B+")
likelihoodToRecommendScore	number	0–10 likelihood-to-recommend score
likelihoodToRecommend	string	Reviewer's free-text reasoning for the score
featureRatings	object[]	Per-feature score breakdown — [{feature, score, notApplicable}]

Review Content

Field	Type	Description
useCases	string	Reviewer's described use cases and deployment scope
pros	string[]	Reviewer's listed pros
cons	string[]	Reviewer's listed cons
roi	string	Reviewer's described ROI and business outcomes
alternativesConsidered	string[]	Other products evaluated before choosing this one
alternativesFollowup	string	Reasoning for choosing this over the alternatives
otherSoftwareUsed	string[]	Other software the reviewer uses alongside this product
sections	object[]	Structured Q&A — full set of section/question/answer entries

Reviewer (when includeReviewerInfo is on)

Field	Type	Description
reviewerName	string	Reviewer's display name
reviewerFirstName	string	First name
reviewerLastName	string	Last name
reviewerTitle	string	Job title
reviewerJobType	string	Job type / function
reviewerDepartment	string	Department
reviewerCompany	string	Company name (often anonymized by TrustRadius)
reviewerCompanySize	string	Company size band (e.g. "201-500 employees")
reviewerCompanySizeGroup	string	Mapped bucket: small / medium / large
reviewerIndustry	string	Reviewer's industry
reviewerYearsExperience	number	Years of professional experience
reviewerRoles	string[]	Reviewer's listed roles (decision-maker, end-user, etc.)
reviewerLinkedInUrl	string	LinkedIn URL when public
reviewerAvatarUrl	string	Avatar image URL
reviewerIsVerified	boolean	Whether TrustRadius has authenticated this reviewer
reviewerVerifiedBy	string	The verification method (e.g. "LinkedIn", "Screenshot")

Reviewer email is never returned, regardless of the toggle.

Tips for Best Results

• Use sortBy = Most Critical for objection handling — the lowest-rated reviews are where prospects' real concerns surface. Pair with a small maxReviewsPerProduct to keep cost down.
• Run incrementals with reviewsStartDate + Most Recent — collection auto-stops at the cutoff, so a nightly job costs only the new reviews.
• Both rating scales are returned — rating is the native 1–10 score, grade is the TrustRadius letter, and starRating (input) maps to the 5-star UI buckets. You'll have everything you need for either presentation.
• Toggle off includeReviewerInfo for GDPR workflows — you'll still get the full review body, ratings, pros, cons, and per-feature scores, just without reviewer-level identifiers.
• Combine productUrls and searchTerms — both inputs run in the same job, so you can mix exact URLs for products you know with name lookups for products you don't.
• For broad categories, queue 3–5 competing products — running side by side gives you ready-made comparison data instead of separate exports you have to merge.
• Reviewer company is often anonymized — TrustRadius redacts company names for many reviews. Industry, role, department, and company size are still populated.

Pricing

$2.30 per 1,000 results — flat rate, undercuts every subscription tier of the closest TrustRadius scraper on the platform.

No compute charges — you only pay per result returned. A result is one review row in your dataset.

Reviews	Cost
100	$0.23
1,000	$2.30
10,000	$23.00
100,000	$230.00

Apify platform fees ($0.05 per run + $0.01 per 1,000 dataset items) are billed separately and depend on your plan.

Integrations

Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps via:

• Zapier / Make / n8n — Workflow automation
• Google Sheets — Direct spreadsheet export
• Slack / Email — Notifications on new reviews
• Webhooks — Trigger custom APIs on run completion
• Apify API — Full programmatic access

Legal & Ethical Use

This actor is designed for legitimate competitive research, market analysis, and product marketing. Users are responsible for complying with applicable laws and TrustRadius's Terms of Service. Do not use extracted data for spam, harassment, or any unlawful purpose. Be mindful of personal data — consider disabling reviewer firmographics for use cases where reviewer identity is not needed.