# TrustRadius Review Scraper (`scraped/trustradius-review-scraper`) Actor Scrapes reviews for specified product on TrustRadius - **URL**: https://apify.com/scraped/trustradius-review-scraper.md - **Developed by:** [scraped](https://apify.com/scraped) (community) - **Categories:** Automation, Developer tools, Integrations - **Stats:** 30 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $20.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## TrustRadius Review Scraper This scraper reviews from [OpenTable](https://trustradius.com/) ### Sample Output Here's an example of the data the scraper will output: ```json { "Review ID": "684ad99ca63f3e54e1f7ee76", "Title": "AlphaSense 2025-06-12 08:43:56", "Heading": "Reliable and efficient platform with strong customer support", "Synopsis": "", "Rating": 10, "Grade": "C", "Grade Numeric": 3, "Status": "published", "Show Public": false, "Show Public Numeric": 0, "Submitted Date": "2025-06-12T13:55:12.014Z", "Published Date": "2025-06-25T22:06:50.435Z", "Modified": "2025-06-25T23:41:45.546Z", "Last Updated": "2025-06-25T22:06:50.435Z", "Read Count": 1, "Points": 40, "Reviewer Name": null, "Reviewer First Name": null, "Reviewer Last Name": null, "Reviewer Job Title": null, "Reviewer Job Type": "Strategist", "Reviewer Department": "Corporate", "Reviewer Years Experience": 2, "Reviewer Roles": "user, support", "Reviewer Picture": null, "Reviewer LinkedIn": null, "Company Name": null, "Company Size": "10,001+ employees", "Company Size Group": "large", "Company Size Minimum": 10001, "Company Industry": "Electrical & Electronic Manufacturing", "Company Industry Code": "112", "Product Name": "AlphaSense", "Product Slug": "alphasense", "Product ID": "622644384cc864002b34badf", "Product Logo": "https://media.trustradius.com/product-logos/yr/4c/ZUGPJ6J7IXSO-180x180.JPEG", "Vendor Name": "AlphaSense", "Vendor Slug": "alphasense", "Vendor ID": "622643e8033b1d0046148db2", "Categories": "Market Intelligence, Enterprise Search, Competitive Intelligence, Text Analysis, Financial Research, AI Chatbot", "Other Products": "FactSet Workstation, AlphaSense", "product-usage_question": "Use Cases and Deployment Scope", "product-usage_answer": "AlphaSense is frequently used for market insights and earnings highlights. Very efficient in gathering needed financial and investor relations information to inform executive decisions.", "product-usage_values": [ "AlphaSense is frequently used for market insights and earnings highlights. Very efficient in gathering needed financial and investor relations information to inform executive decisions. " ], "product-usage_followup": null, "things-done-well,pros-and-cons_question": "Pros", "things-done-well,pros-and-cons_answer": "Timely earnings transcript\nStreamlined interface\nEmbedded AI tool", "things-done-well,pros-and-cons_values": [ "Timely earnings transcript", "Streamlined interface", "Embedded AI tool" ], "things-done-well,pros-and-cons_followup": null, "things-done-poorly,pros-and-cons_question": "Cons", "things-done-poorly,pros-and-cons_answer": "Perhaps integration with some other tools", "things-done-poorly,pros-and-cons_values": [ "Perhaps integration with some other tools" ], "things-done-poorly,pros-and-cons_followup": null, "likelihood-to-recommend_question": "Likelihood to Recommend", "likelihood-to-recommend_answer": "10", "likelihood-to-recommend_values": [ 10 ], "likelihood-to-recommend_followup": "It's efficient for gathering investor relations and earnings insights. The embedded AI tool is quite functional in giving additional information and summaries that contain critical information that the human eyes might easily miss.", "feature-ratings_question": "AlphaSense Feature Ratings", "feature-ratings_answer": "", "feature-ratings_values": [ { "featureId": "63ebe54484305f180fd9bff5", "value": 10, "na": false }, { "featureId": "63ebe588b9e4cb4421475d3a", "value": 7, "na": false }, { "featureId": "63ebe5cc93f9060195cd0787", "value": 10, "na": false }, { "featureId": "63ebe60084305f6931d9cfd4", "value": 10, "na": false }, { "featureId": "63ebe62254ae9517c9b69426", "value": 10, "na": false }, { "featureId": "63ebe641b9e4cbaa67476bdd", "value": 10, "na": false }, { "featureId": "63ebe66c420979d86830d983", "value": 10, "na": false }, { "featureId": "63ebe69a5731434055eeec11", "value": 10, "na": false }, { "featureId": "63ebe6e14b5815452aabcf45", "value": 10, "na": false }, { "featureId": "63ebe703b9e4cb840f4777cb", "value": 10, "na": false }, { "featureId": "63ebe71f56bdec54a3315d91", "value": 10, "na": false } ], "feature-ratings_followup": null, "operational-benefits_question": "Return on Investment", "operational-benefits_answer": "Efficiency in gathering latest information\nAI empowered summaries\nAdded confidence from information from multiple sources", "operational-benefits_values": [ "Efficiency in gathering latest information", "AI empowered summaries", "Added confidence from information from multiple sources" ], "operational-benefits_followup": null, "product-usability_question": "Usability", "product-usability_answer": "10", "product-usability_values": [ 10 ], "product-usability_followup": "Very easy to use. Customer support is strong and responsive for any questions", "alphasense-market-intelligence_question": "AlphaSense Market Intelligence", "alphasense-market-intelligence_answer": "Yes, AlphaSense provides very timely information and updates that people will likely otherwise miss out. The multiple sources it depends on are a key feature that similar platforms may not already have.", "alphasense-market-intelligence_values": [ "Yes, AlphaSense provides very timely information and updates that people will likely otherwise miss out. The multiple sources it depends on are a key feature that similar platforms may not already have. " ], "alphasense-market-intelligence_followup": null, "alternatives-evaluated_question": "Alternatives Considered", "alternatives-evaluated_answer": "FactSet Workstation", "alternatives-evaluated_values": [ "FactSet Workstation" ], "alternatives-evaluated_followup": "Actually have both AlphaSense and FactSet. Each has its uniqueness but all depends on nature of the task or project at hand.", "other-software-used_question": "Other Software Used", "other-software-used_answer": "FactSet Workstation", "other-software-used_values": [ { "productId": "59dfcbee43b83500100f5c74", "productName": "FactSet Workstation", "value": 10, "submitted": true } ], "other-software-used_followup": null, "feature_public-company-data_rating": 10, "feature_private-company-data_rating": 7, "feature_industry-and-sector-research_rating": 10, "feature_industry-specific-information_rating": 10, "feature_independent-research-access_rating": 10, "feature_m-a-analysis_rating": 10, "feature_supply-chain-data_rating": 10, "feature_esg-data_rating": 10, "feature_credit-ratings-reports_rating": 10, "feature_macroeconomic-news_rating": 10, "feature_search-tools_rating": 10 }, ```` ### Support Please email scraperhelp@gmail.com if you need any additional support. # Actor input Schema ## `url` (type: `string`): The URL of website you want to get the data from. ## Actor input object example ```json { "url": "https://www.trustradius.com/products/alphasense/" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "url": "https://www.trustradius.com/products/alphasense/" }; // Run the Actor and wait for it to finish const run = await client.actor("scraped/trustradius-review-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "url": "https://www.trustradius.com/products/alphasense/" } # Run the Actor and wait for it to finish run = client.actor("scraped/trustradius-review-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "url": "https://www.trustradius.com/products/alphasense/" }' | apify call scraped/trustradius-review-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraped/trustradius-review-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TrustRadius Review Scraper", "description": "Scrapes reviews for specified product on TrustRadius", "version": "0.0", "x-build-id": "FOTbUhJPbYZ755qMa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraped~trustradius-review-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraped-trustradius-review-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraped~trustradius-review-scraper/runs": { "post": { "operationId": "runs-sync-scraped-trustradius-review-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraped~trustradius-review-scraper/run-sync": { "post": { "operationId": "run-sync-scraped-trustradius-review-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "url" ], "properties": { "url": { "title": "URL of the page", "type": "string", "description": "The URL of website you want to get the data from." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```