TrustRadius Reviews Scraper

Give it TrustRadius product pages or product names and it returns one JSON row per review: rating, title, use case, pros, cons, the reviewer's job role and company size, and the incentive flag. $3.59 per 1,000 reviews on the free plan, and you pay only for the rows you get.

$3.59 per 1,000 reviews on the Free plan, down to $2.24 on higher plans

Why this actor

• Sorting and filtering (stars, company size) are done by TrustRadius itself, and each product is read to its last page.
• Product names work as input: the actor looks the product up for you.
• onlyNewReviews for monitoring: a run returns only reviews it has not delivered before.
• Reviewer names, company names and profile links are never collected. Free error rows with a machine-readable code (not_found, blocked, unavailable...), so an agent knows whether to retry.

Drop-in input

Drop-in input. Input written for zen-studio/trustradius-review-scraper works as it is (see "Coming from zen-studio's TrustRadius scraper?"), at $3.59 instead of $3.99 per 1,000 reviews. 10.6% of that actor's runs failed (Apify Store, 30 days to 2026-10-31).

As stated in the actor’s README. The full list of accepted input names is on the Store page.

What you get

A second output, the key-value store record PRODUCT, holds one entry per product with the overall score, review count and the breakdown of reviewers by company size, industry, department and role.

Sample row (from the README example; long text shortened, lists cut to two items):

{
  "reviewId": "TrustRadius___638fcc80649f691b7696d9c6",
  "platform": "trustradius",
  "productName": "Asana",
  "date": "2022-12-15",
  "title": "Great task management tool",
  "text": "Asana is used to manage all the internal activities at my company...",
  "pros": "Receive requests\nDocument information\nManage tasks across departments",
  "cons": "More free/not-premium features\nSmall navigation bugs\nTask templates",
  "ratingOverall": 5,
  "ratings": {
    "likelihoodToRecommend": 10
  },
  "reviewerRole": null,
  "reviewerCompanySize": null,
  "reviewerTimeUsed": null,
  "incentive": "TrustRadius",
  "incentivized": true,
  "extras": {
    "jobType": "Manager",
    "department": "Marketing",
    "ratingRaw10": 10
  }
}

Price

Live Apify price on 2026-10-31, per 1,000 rows, by Apify plan. You pay only for rows delivered; error and summary rows marked free in the README cost nothing. Plus $0.001 per GB of memory when a run starts.

Use cases

• Competitive intelligence: export a rival's newest reviews every week and see what buyers praise and complain about.
• Win and loss analysis: pull only the 1 and 2 rated reviews, or only reviews from large companies, and look for patterns.
• Due diligence: read a software company's reviews by buyer role and company size before an investment or acquisition.
• Comparison pages: pull pros, cons and ratings for the products you list.

Run it from code or an AI agent

Actor ID arcadium/trustradius-reviews. Set APIFY_TOKEN to your Apify API token. The input below is the actor’s prefilled example; see the guide for every field.

curl -X POST "https://api.apify.com/v2/acts/arcadium~trustradius-reviews/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls":[{"url":"https://www.trustradius.com/products/asana/reviews"}],"maxReviewsPerProduct":20,"sortBy":"date","sortOrder":"desc"}'

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/trustradius-reviews').call({
  "startUrls": [
    {
      "url": "https://www.trustradius.com/products/asana/reviews"
    }
  ],
  "maxReviewsPerProduct": 20,
  "sortBy": "date",
  "sortOrder": "desc"
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/trustradius-reviews").call(run_input={
    "startUrls": [{
        "url": "https://www.trustradius.com/products/asana/reviews",
    }],
    "maxReviewsPerProduct": 20,
    "sortBy": "date",
    "sortOrder": "desc",
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/trustradius-reviews",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}

# pip install langchain-apify   (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("arcadium/trustradius-reviews")
rows = tool.invoke({"run_input": {
    "startUrls": [{
        "url": "https://www.trustradius.com/products/asana/reviews",
    }],
    "maxReviewsPerProduct": 20,
    "sortBy": "date",
    "sortOrder": "desc",
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])

# pip install llama-index-readers-apify
import os
from llama_index.core import Document, VectorStoreIndex
from llama_index.readers.apify import ApifyActor

reader = ApifyActor(os.environ["APIFY_TOKEN"])
documents = reader.load_data(
    actor_id="arcadium/trustradius-reviews",
    run_input={
        "startUrls": [{
            "url": "https://www.trustradius.com/products/asana/reviews",
        }],
        "maxReviewsPerProduct": 20,
        "sortBy": "date",
        "sortOrder": "desc",
    },
    dataset_mapping_function=lambda item: Document(text=str(item.get("text") or ""), metadata={"url": item.get("url")}),
)
index = VectorStoreIndex.from_documents(documents)

# pip install crewai crewai-tools langchain-apify   (reads APIFY_API_TOKEN from the environment)
from crewai import Agent
from crewai_tools import ApifyActorsTool

tool = ApifyActorsTool(actor_name="arcadium/trustradius-reviews")
researcher = Agent(
    role="Research analyst",
    goal="Answer with data collected by the tool",
    backstory="Uses public web data.",
    tools=[tool],
)

{
  "nodes": [
    {
      "name": "Run arcadium/trustradius-reviews",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        0,
        0
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/acts/arcadium~trustradius-reviews/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"startUrls\":[{\"url\":\"https://www.trustradius.com/products/asana/reviews\"}],\"maxReviewsPerProduct\":20,\"sortBy\":\"date\",\"sortOrder\":\"desc\"}",
        "options": {
          "timeout": 300000
        }
      }
    }
  ],
  "connections": {}
}

// Extensions > Apps Script. Store your token once: Project Settings > Script properties > APIFY_TOKEN.
function importLastRun() {
  const token = PropertiesService.getScriptProperties().getProperty('APIFY_TOKEN');
  const url = 'https://api.apify.com/v2/acts/arcadium~trustradius-reviews/runs/last/dataset/items?status=SUCCEEDED&clean=true&format=json';
  const res = UrlFetchApp.fetch(url, { headers: { Authorization: 'Bearer ' + token } });
  const rows = JSON.parse(res.getContentText());
  if (!rows.length) return;
  const keys = Object.keys(rows[0]);
  const values = rows.map((r) => keys.map((k) => (typeof r[k] === 'object' ? JSON.stringify(r[k]) : r[k])));
  const sheet = SpreadsheetApp.getActiveSheet();
  sheet.clearContents();
  sheet.getRange(1, 1, 1, keys.length).setValues([keys]);
  sheet.getRange(2, 1, values.length, keys.length).setValues(values);
}

Limitations

• Public reviews only. Nothing behind a login.
• You get what appears on the product's review list. The long-form extras on each review's own page (alternatives considered, feature ratings, operational benefits) are not included.
• Reviews are in English. TrustRadius has no other languages.
• Reviewer names, company names and photos are not part of the output, by design. Industry is empty for almost all reviews, because TrustRadius rarely fills it in.
• Name lookup picks the closest product that has public reviews. For products with common or similar names, use the URL.
• With the rating sort the dates are not in order, so dateFrom then filters rows but cannot stop early.
• TrustRadius changes its site from time to time. If a run fails for several products at once, try again later or open an issue.

FAQ

How fresh is the data? It is read when you run the actor, so it matches what the site shows at that moment.

Can I get only new reviews since my last run? Yes. Turn on onlyNewReviews and keep the same stateKey between runs. Reviews you already received are skipped and not charged. The state lives in a key-value store in your Apify account. Pick a new stateKey to start over.

Why is the rating out of 5 and not 10? So that TrustRadius lines up with Capterra, Software Advice and Tripadvisor in the same spreadsheet. The original 1 to 10 score is in ratings.likelihoodToRecommend and extras.ratingRaw10.

A product returned no reviews. Why? Check that the URL opens a product page with reviews in your browser. Products without public reviews return a free error row.

Something looks wrong in the output. Who do I tell? Open an issue on the actor page with the run link. We read them all.

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