TrustRadius Reviews Scraper

Scrape every TrustRadius review of any B2B software product into clean, analysis-ready JSON. Give it a product URL (https://www.trustradius.com/products/hubspot-crm/reviews), a bare slug (hubspot-crm) or just a keyword, and it returns each review with its 10-point rating, title, use case, pros, cons, likelihood to recommend (with the reviewer's explanation), return on investment, alternatives considered, other software used, per-feature ratings, and the reviewer's role, department, industry, company size and country. No browser, no login, no API key.

What you get from a single run:

• The full review, not a snippet. Every published question-and-answer of the review form is returned: the headline fields as their own columns, plus a sections list and a ready-to-use fullText for LLM pipelines.
• The whole review history. Pagination goes all the way: 1,000 reviews take about 25 seconds. Set maxReviewsPerProduct above the product's review count to get every review.
• B2B buyer context on every row: reviewer job level, department, industry, company size band and country — the segmentation that makes TrustRadius data valuable — with no reviewer names.
• Trust signals: review source (vendor-invited, TrustRadius outreach, community), incentive, trusted-source flag, work-email verification and TrustRadius' own A/B/C quality grade, so you can weight or filter reviews.
• Product context: product name, vendor, category, TrScore and total review count on every row, and a per-product summary (rating breakdowns, feature averages) in the key-value store.
• Find products by keyword when you don't have the URLs: searchQuery: "zendesk" resolves the best-matching products that have reviews.

Example output item

A real review, unedited except that the featureRatings (27 entries), sections and fullText arrays are shortened here:

{
    "reviewId": "6a9acd7749470e91003cfdfc",
    "reviewUrl": "https://www.trustradius.com/reviews/hubspot-crm-2026-09-04-08-53-58",
    "productId": "552826bca2f0781500fa6c87",
    "productSlug": "hubspot-crm",
    "productName": "HubSpot CRM",
    "productUrl": "https://www.trustradius.com/products/hubspot-crm/reviews",
    "vendorName": "HubSpot",
    "productCategory": "Customer Relationship Management (CRM)",
    "productTrScore": 8.4,
    "productReviewCount": 1762,
    "title": "You can't miss HubSpot if you are considering a CRM",
    "rating": 8,
    "likelihoodToRecommend": 8,
    "likelihoodToRenew": null,
    "usabilityRating": 9,
    "supportRating": null,
    "implementationRating": null,
    "ratings": [
        { "name": "Likelihood to Recommend", "value": 8 },
        { "name": "Usability", "value": 9 }
    ],
    "useCases": "I used HubSpot and deployed it in my previous company as there was no CRM in place. HubSpot seemed to be the easiest and most powerful CRM amongst all the potential candidates. The integration abilities of HubSpot were particularly important for the company and HubSpot answered this requirement thanks to its vast marketplace.",
    "pros": [
        "Simple UI",
        "Integration abilities",
        "Easy configuration and customisation"
    ],
    "cons": [
        "Pricing can be adapted to smaller companies",
        "Rights management can be tricky to master",
        "Marketing module should be more powerful in standard"
    ],
    "recommendationContext": "HubSpot can work for companies of many sizes, that is the beauty of it. Whether you're a small company or a large one, you can adapt easily the solution to your needs. With a bit of time invested to understand all the configuration options, you can really craft a tailor-made CRM answering the needs of your business and teams.",
    "returnOnInvestment": [
        "Greater visibility on business opportunities helped the sales team to manage in a better way the business and improve the accuracy of the pipeline and the win rate",
        "Having all the contacts, companies and interactions saved heaps of time and improve the communication quality for the whole business",
        "The marketing module in Pro version was too expensive to buy despite all the benefits if could bring. We had to juggle between HubSpot and another tool for our emailing campaigns"
    ],
    "alternativesConsidered": ["Freshsales"],
    "alternativesComment": "HubSpot was more turnkey and easy to deploy rather than Freshsales. The cost of Freshdesk was cheaper but when you look for a CRM, price shouldn't be the only parameter to consider when making your choice. Freshsales was a great solution too but the integration capabilities were more limited than HubSpot and we wanted something to integrate almost from scratch.",
    "otherSoftwareUsed": ["Freshdesk", "Brevo", "PaperCut"],
    "featureRatings": [
        { "feature": "Customer data management / contact management", "featureId": "54bffd712e5757a94cb16deb", "rating": 8 },
        { "feature": "Workflow management", "featureId": "54bffd712e5757a94cb16dec", "rating": 8 },
        { "feature": "Opportunity management", "featureId": "54bffd712e5757a94cb16dee", "rating": 8 }
    ],
    "sections": [
        {
            "section": "Overall Satisfaction",
            "question": "Pros",
            "answer": "Simple UI\nIntegration abilities\nEasy configuration and customisation",
            "comment": null
        }
    ],
    "fullText": "Use Cases and Deployment Scope:\nI used HubSpot and deployed it in my previous company as there was no CRM in place. ...",
    "publishedAt": "2026-09-09T15:50:19.121Z",
    "updatedAt": "2026-09-06T10:41:24.837Z",
    "reviewerJobType": "C-Level Executive",
    "reviewerDepartment": "Information Technology",
    "companyIndustry": "Computer Software",
    "companySize": "11-50 employees",
    "reviewerCountry": "FRA",
    "yearsOfExperience": 3,
    "usageStatus": "recent",
    "reviewSource": "RaaS",
    "incentive": "TrustRadius",
    "incentivized": true,
    "trustedSource": true,
    "workEmailVerified": false,
    "qualityGrade": "B",
    "scrapedAt": "2026-10-12T16:00:15.596Z"
}

How to scrape TrustRadius reviews

1. Put one or more products in Products — a product URL (any sub-page of it works), a bare slug, a review permalink, or a product id.
2. Or type a Search query (a product or vendor name works best) and choose how many matching products to take.
3. Set Max reviews per product. The Actor reads 100 reviews per request, so 1,000 reviews = 10 requests.
4. Optionally pick a Sort order and a reviewsSince date filter.
5. Press Start. Reviews land in the dataset and export as JSON, CSV or Excel, or sync to Google Sheets, webhooks, Zapier, Make or the Apify API.

Input examples

All reviews of three competitors:

{
    "products": [
        "https://www.trustradius.com/products/zendesk-support-suite/reviews",
        "https://www.trustradius.com/products/hubspot-crm/reviews",
        "asana"
    ],
    "maxReviewsPerProduct": 100000
}

Weekly monitoring — only what was published in the last 7 days:

{
    "products": ["hubspot-crm", "zoho-crm"],
    "sortBy": "newest",
    "reviewsSince": "7 days",
    "maxReviewsPerProduct": 500
}

Find products by keyword and pull their most critical reviews:

{
    "searchQuery": "zendesk",
    "maxSearchResults": 3,
    "sortBy": "lowestRated",
    "maxReviewsPerProduct": 50
}

Input	Description
products	One product per line: https://www.trustradius.com/products/<slug>/reviews (any sub-page), <slug>, a review permalink https://www.trustradius.com/reviews/<slug>-<date>, or the 24-character product id. Renamed products keep working with their old slug. Duplicates are collapsed.
searchQuery	Optional keyword. Takes the best-matching products that have reviews: products whose name contains every word come first, ordered by review count. Product and vendor names work best (zendesk, hubspot, asana).
maxSearchResults	How many products to take from the search (default 3).
maxReviewsPerProduct	Cap per product (default 50). Use 100000 for everything.
sortBy	newest (default), oldest, highestRated, lowestRated.
reviewsSince	2026-01-01, or relative: 30 days, 6 months, 1 year. With newest the Actor stops as soon as it reaches older reviews.
proxyConfiguration	Not needed — see FAQ.

Output fields

Field	Type	Description
reviewId	string	TrustRadius review id, stable across runs — use it to dedupe and diff
reviewUrl	string	Review permalink
productId, productSlug, productName, productUrl	string	The product reviewed
vendorName	string	Vendor of the product
productCategory	string	Primary TrustRadius category
productTrScore	number	Product's overall TrScore (0–10) at scrape time
productReviewCount	number	Product's published review count at scrape time
title	string	Review headline
rating	number	Overall rating, 1–10
likelihoodToRecommend	number	1–10
likelihoodToRenew, usabilityRating, supportRating, implementationRating	number | null	Sub-ratings (1–10), only when the reviewer answered them
ratings	array	Every numeric rating in the review as {name, value}
useCases	string	"Use Cases and Deployment Scope" answer
pros, cons	string[]	Bullet lists, one item per bullet
recommendationContext	string	Where the product is well suited / less appropriate
returnOnInvestment	string[]	ROI bullets
alternativesConsidered	string[]	Competing products evaluated
alternativesComment	string	Why this product was chosen over them
otherSoftwareUsed	string[]	Other tools in the reviewer's stack
featureRatings	array	{feature, featureId, rating} per rated feature (N/A answers dropped)
sections	array	Every published answer: {section, question, answer, comment} — includes any custom questions
fullText	string	All answers as one text block, ready for an LLM
publishedAt, updatedAt	string	ISO 8601 timestamps
reviewerJobType	string	Job level / role, e.g. Manager, Director, C-Level Executive, Account Manager
reviewerDepartment	string	e.g. Marketing, Information Technology, Sales
companyIndustry	string	Reviewer's company industry
companySize	string	Size band, e.g. 51-200 employees
reviewerCountry	string	ISO 3166 alpha-3 country code, e.g. USA, GBR
yearsOfExperience	number	Years using the product
usageStatus	string	current, recent or older user
reviewSource	string	How the review was collected: VendorSourced, RaaS, DirectOutreach, CommunityInvite, CommunityInbound
incentive, incentivized	string, boolean	Who offered the reviewer an incentive (TrustRadius, Vendor, No)
trustedSource	boolean	TrustRadius' trusted-source flag
workEmailVerified	boolean | null	Work-email check, when TrustRadius ran one
qualityGrade	string	TrustRadius' review quality grade, A–C
scrapedAt	string	When this item was scraped

Product summaries. The run's key-value store has a PRODUCTS record with one entry per product: TrScore, rating count, review count, average of every rating question (likelihood to recommend, usability, support…), the average of every feature, categories, homepage, logo, free version / trial flags and deployment types. A SUMMARY record lists products resolved, reviews per product, requests and any errors. Both are free.

Pricing

Pay per result — you only pay for reviews delivered.

Event	When it is charged
Review (review-result)	Per review saved
Actor start	Once per run (a fraction of a cent)
Product summaries, search, run summary	free

1,000 reviews cost US$3 on the Apify Free plan, and the same per-review price applies on paid plans — see the Pricing tab for the current rate. Typical costs at that rate: 50 reviews ≈ US$0.15, all 1,762 reviews of HubSpot CRM ≈ US$5.30. Set a maximum charge on the run and the Actor stops cleanly when it is reached.

Performance & limits

• Speed: about 1,000 reviews in 25 seconds (measured on the Apify platform with 1 GB; the default is now 512 MB, well above the ~110 MB the Actor needs). No proxy is needed.
• Sub-ratings are sparse by nature. The current review form asks for likelihood to recommend and usability; support, implementation and renewal ratings appear mostly in older, longer-form reviews. Missing answers are null, never invented.
• Reviewer identity is not collected. TrustRadius shows some reviewers' names; this Actor never reads or outputs them — only role, department, industry, company size and country.
• Order: the dataset follows sortBy exactly; reviews with the same rating are ordered newest first.
• Keyword search is fuzzy. For exact targeting use product URLs or slugs.

What can you do with TrustRadius review data?

• Competitive intelligence: pull every review of your top three competitors and cluster their cons — that's your roadmap and your sales battlecard.
• Win/loss insight: alternativesConsidered + alternativesComment tell you who you are compared against and why buyers chose one product over another.
• ICP and segmentation: split ratings by companySize, companyIndustry, reviewerDepartment and reviewerJobType to see where a product delights and where it struggles.
• Feature gap analysis: average featureRatings across products to see which capability each one is weak at.
• Voice-of-customer for marketing: 9–10 ratings give you buyer language for copy; recommendationContext says exactly which use case a product fits.
• Monitoring: schedule weekly with sortBy: "newest" and reviewsSince: "7 days", dedupe on reviewId, and alert on new negative reviews.
• LLM / RAG: fullText plus product and segment metadata is a ready-made corpus for summarization and Q&A over B2B software feedback.

Integrations

Every Apify dataset exports to CSV, Excel, JSON, XML or HTML and syncs to Google Sheets. Run the Actor through the Apify API or the JavaScript and Python clients, trigger follow-ups with webhooks, or schedule weekly runs in Apify Console. It plugs into n8n, Make and Zapier, and into LangChain and LlamaIndex through their Apify integrations. AI agents in Claude, ChatGPT, Cursor and other MCP clients can find and run it through Apify's MCP server. From Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("fabrikit/trustradius-reviews-scraper").call(run_input={
    "products": ["https://www.trustradius.com/products/hubspot-crm/reviews"],
    "maxReviewsPerProduct": 500,
    "sortBy": "newest",
})
for review in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(review["rating"], review["companySize"], review["title"])

FAQ

Do I need a TrustRadius account, an API key or a proxy? No. The Actor reads the same public data the review pages show. It runs without a proxy; if TrustRadius ever starts blocking a run, it switches to Apify Proxy automatically (datacenter first, then US residential) and says so in the log.

What rating scale does TrustRadius use? 1 to 10 for every rating, including the overall rating and featureRatings. productTrScore is TrustRadius' weighted product score on the same 0–10 scale.

Why do some reviews have alternativesConsidered or supportRating empty? Because the reviewer didn't answer that question. The review form is long and most questions are optional.

Why does productReviewCount differ slightly from the number of reviews I got? TrustRadius updates its counters periodically, so a review published in the last hours may already be returned while the counter still shows the previous number.

Can I get only new reviews since my last run? Yes: sortBy: "newest" with reviewsSince (for example "7 days"), and dedupe on reviewId.

Is scraping TrustRadius legal? See Is it legal to scrape TrustRadius? below.

Something broke? TrustRadius' internal API is undocumented. The Actor validates every response and fails with a clear message (instead of silently returning nothing) if the format changes. Open an issue on the Actor page and it will be fixed quickly.

Is it legal to scrape TrustRadius?

The Actor collects publicly visible review content and aggregate reviewer attributes, without logging in, and deliberately skips reviewer names. Role, department, industry, company size and country can still make a reviewer identifiable in combination, so data-protection laws such as the EU GDPR, Chile's Ley 21.719 or the California CCPA may apply to how you store and use the data; you are responsible for a lawful purpose and for keeping only what you need. Use the data in line with TrustRadius' terms — for example, for analysis rather than republishing reviews wholesale, since review texts belong to their authors. This is general information, not legal advice.

Use with AI agents

Use this actor to get every public TrustRadius review of a B2B software product (by URL, slug or keyword), with 1–10 ratings, pros, cons, alternatives considered and the reviewer's role, industry and company size (never names).

{ "products": ["hubspot-crm"], "sortBy": "newest", "maxReviewsPerProduct": 50 }

Main output fields: productName, title, rating, likelihoodToRecommend, pros, cons, alternativesConsidered, featureRatings, fullText, publishedAt, reviewerJobType, companyIndustry, companySize. It is pay-per-event: an agent pays a small start fee plus a fixed price per review saved, not for compute time.

Related actors

• App Reviews Scraper — App Store and Google Play reviews of mobile apps in one run.
• Shopify App Store Reviews Scraper — reviews of Shopify apps.
• Chrome Web Store Reviews Scraper — reviews of browser extensions, including many SaaS companions.
• Chrome Web Store Scraper — extension listings with users, ratings and developer details.
• ATS Jobs Scraper — see what a software vendor is hiring for.

Ready-made examples

• CRM software reviews from TrustRadius

Changelog

• 2026-10-16 — README: legal notes, integrations, AI-agent usage, related actors and example task added.
• 2026-10-15 — Published on the Apify Store. Default memory lowered from 1,024 to 512 MB.
• 2026-10-12 — Builds 0.1.1–0.1.2: initial release with product URLs, slugs, permalinks and keyword search; full review form, buyer context and trust signals; per-product summaries in the key-value store.

En español

TrustRadius Reviews Scraper extrae todas las reseñas de cualquier software B2B publicado en TrustRadius: calificación de 1 a 10, título, casos de uso, pros, contras, probabilidad de recomendar (con la explicación del revisor), retorno de inversión, alternativas evaluadas, otro software usado y calificación por funcionalidad, más el cargo, área, industria, tamaño de empresa y país del revisor (nunca su nombre). Acepta la URL del producto, el slug o una búsqueda por palabra clave; recorre el historial completo de reseñas, filtra por fecha y ordena por más recientes o por calificación. No requiere cuenta, API key ni proxy. Precio: US$3 por cada 1.000 reseñas; los resúmenes por producto son gratis.