# Gartner Peer Insights Scraper (`jungle_synthesizer/gartner-peer-insights-scraper`) Actor Scrape enterprise-grade B2B software reviews from Gartner Peer Insights — verified-reviewer ratings, pros/cons, use case, reviewer role, industry, company size, and vendor responses. - **URL**: https://apify.com/jungle\_synthesizer/gartner-peer-insights-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Lead generation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ## Gartner Peer Insights Scraper Extract verified B2B software reviews from [Gartner Peer Insights](https://www.gartner.com/reviews). Gartner is the world's leading IT research and advisory company; its Peer Insights platform hosts hundreds of thousands of verified reviews across enterprise software categories including CRM, ERP, cloud infrastructure, security, and more. ### What This Actor Does - Accepts one or more Gartner Peer Insights product review URLs or market category URLs as input - Scrapes verified reviewer data: role, company size, industry, star rating, review headline, and summary text - Paginates automatically through all available review pages (5 reviews per page) - Respects `maxItems` and `maxReviewsPerProduct` caps to control run cost ### Use Cases - **Competitive intelligence**: Aggregate user sentiment across competing products in a category - **Market research**: Understand adoption patterns by industry and company size - **Product benchmarking**: Track star ratings and review themes over time - **Sales enablement**: Surface buyer personas and pain points from verified enterprise reviewers ### Input | Field | Type | Description | |-------|------|-------------| | `startUrls` | Array | Required. One or more Gartner Peer Insights URLs (product review pages or market category pages) | | `maxItems` | Integer | Maximum total reviews to collect across all products (0 = unlimited) | | `maxReviewsPerProduct` | Integer | Maximum reviews per product URL (0 = unlimited, default 10) | #### Accepted URL formats ```` ## Product review listing page (recommended) https://www.gartner.com/reviews/market//vendor//product//reviews ## Product overview page (actor converts to /reviews automatically) https://www.gartner.com/reviews/market//vendor//product/ ## Market category page (actor discovers all products on the page) https://www.gartner.com/reviews/market/ ```` #### Example Input ```json { "startUrls": [ { "url": "https://www.gartner.com/reviews/product/salesforce-sales-cloud" } ], "maxItems": 50, "maxReviewsPerProduct": 25 } ```` ### Output Each item in the dataset represents a single verified review: | Field | Type | Description | |-------|------|-------------| | `productName` | String | Product name (from page heading) | | `vendorName` | String | Vendor / company name | | `categoryName` | String | Market category (from URL slug) | | `productUrl` | String | URL of the product review listing | | `reviewId` | String | Stable review identifier (product URL path + page index) | | `reviewTitle` | String | Review headline | | `overallRating` | Number | Star rating (1.0–5.0) | | `ratingsBreakdown` | null | Per-dimension ratings (not available on listing pages) | | `pros` | null | Pros text (not available on listing pages) | | `cons` | null | Cons text (not available on listing pages) | | `useCaseSummary` | String | Main review body / use-case summary | | `vendorResponse` | null | Vendor response (not available on listing pages) | | `reviewerTitle` | null | Reviewer job title | | `reviewerRole` | String | Reviewer job function / role | | `reviewerIndustry` | String | Reviewer's industry | | `reviewerCompanySize` | String | Reviewer's company revenue tier | | `reviewDate` | String | Date of the review | | `verifiedReviewer` | Boolean | Always `true` — Gartner requires reviewer verification | | `reviewUrl` | String | URL of the product review page | | `scrapedAt` | String | ISO 8601 timestamp when the record was scraped | #### Example Output ```json { "productName": "Salesforce Sales Cloud", "vendorName": "Salesforce", "categoryName": "Crm Customer Engagement Center", "productUrl": "https://www.gartner.com/reviews/product/salesforce-sales-cloud", "reviewId": "/reviews/product/salesforce-sales-cloud#p1-0", "reviewTitle": "A robust CRM with deep customization", "overallRating": 4.5, "ratingsBreakdown": null, "pros": null, "cons": null, "useCaseSummary": "We use Sales Cloud for pipeline management across our enterprise sales team...", "vendorResponse": null, "reviewerTitle": null, "reviewerRole": "Sales", "reviewerIndustry": "Finance", "reviewerCompanySize": "$1B - $3B", "reviewDate": "January 2025", "verifiedReviewer": true, "reviewUrl": "https://www.gartner.com/reviews/product/salesforce-sales-cloud", "scrapedAt": "2025-01-15T10:30:00.000Z" } ``` ### Technical Notes - **Anti-bot**: Gartner Peer Insights is protected by Cloudflare Turnstile. This actor uses CapSolver to obtain a CF clearance cookie, then fetches all review pages using that session. - **Proxy**: Uses residential proxies (DataImpulse) to maintain a stable IP session throughout the crawl. - **Extraction**: Reviews are server-side rendered (Next.js SSR) — no JavaScript execution required; all data is in the initial HTML. - **Rate**: One product is processed at a time; each page fetch reuses the same CF-cleared session. ### Limitations - Pros/cons and per-dimension rating breakdowns are only available on individual review detail pages (not scraped by this actor — listing page data only) - Reviewer job title is not exposed on listing pages - Review ID is positional (page index), not a Gartner-native stable ID # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `startUrls` (type: `array`): Gartner Peer Insights product or market category URLs to scrape. Each URL should be a gartner.com/reviews product or market page. ## `maxItems` (type: `integer`): Maximum number of reviews to scrape (0 = unlimited) ## `maxReviewsPerProduct` (type: `integer`): Maximum number of reviews to collect per product page (0 = all pages) ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [ { "url": "https://www.gartner.com/reviews/product/salesforce-sales-cloud" } ], "maxItems": 10, "maxReviewsPerProduct": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [ { "url": "https://www.gartner.com/reviews/product/salesforce-sales-cloud" } ], "maxItems": 10, "maxReviewsPerProduct": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/gartner-peer-insights-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [{ "url": "https://www.gartner.com/reviews/product/salesforce-sales-cloud" }], "maxItems": 10, "maxReviewsPerProduct": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/gartner-peer-insights-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [ { "url": "https://www.gartner.com/reviews/product/salesforce-sales-cloud" } ], "maxItems": 10, "maxReviewsPerProduct": 10 }' | apify call jungle_synthesizer/gartner-peer-insights-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/gartner-peer-insights-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gartner Peer Insights Scraper", "description": "Scrape enterprise-grade B2B software reviews from Gartner Peer Insights — verified-reviewer ratings, pros/cons, use case, reviewer role, industry, company size, and vendor responses.", "version": "0.1", "x-build-id": "mRFPE0agDVYwzD48d" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~gartner-peer-insights-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-gartner-peer-insights-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~gartner-peer-insights-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-gartner-peer-insights-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~gartner-peer-insights-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-gartner-peer-insights-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "startUrls": { "title": "Start URLs", "type": "array", "description": "Gartner Peer Insights product or market category URLs to scrape. Each URL should be a gartner.com/reviews product or market page.", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of reviews to scrape (0 = unlimited)" }, "maxReviewsPerProduct": { "title": "Max Reviews Per Product", "type": "integer", "description": "Maximum number of reviews to collect per product page (0 = all pages)" } } }, "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 } } } } } } } } } } ```