# Glassdoor Reviews Scraper (`knotless_cadence/glassdoor-reviews-scraper`) Actor Scrape Glassdoor company reviews — ratings, pros, cons, salaries. Employer brand monitoring and talent intelligence. JSON/CSV export. Custom tool in 48h, $100 pilot. Email: spinov001@gmail.com • Tips: t.me/scraping\_ai - **URL**: https://apify.com/knotless\_cadence/glassdoor-reviews-scraper.md - **Developed by:** [Alex](https://apify.com/knotless_cadence) (community) - **Categories:** Business, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Glassdoor Reviews Scraper — Employee Reviews & Ratings Extract employee reviews from Glassdoor including ratings, pros, cons, job titles, and review dates. Search by company name or provide direct Glassdoor URLs. Supports pagination to collect large review datasets. Built for employer brand analysis, HR research, and competitive intelligence. ### Features - **Review Details** — Extract review title, overall rating, pros, cons, and full review text - **Company Search** — Find companies by name and automatically navigate to their review pages - **Direct URL Support** — Provide Glassdoor company review page URLs for precise targeting - **Multi-Method Parsing** — Extracts data from JSON-LD, HTML review cards, and embedded JSON state - **Auto-Pagination** — Navigates through multiple review pages to reach your collection limit - **Author Info** — Capture reviewer job title and employment details when available - **Date Tracking** — Review publication dates for temporal analysis of company sentiment - **Configurable Sorting** — Sort reviews by date or relevance ### Output Example ```json { "companyName": "Google", "title": "Great culture but work-life balance varies by team", "rating": 4.0, "pros": "Amazing benefits, free food, smart colleagues, cutting-edge projects, strong engineering culture", "cons": "Work-life balance depends heavily on your team and manager. Some teams have intense on-call rotations.", "text": "Amazing benefits, free food, smart colleagues... Work-life balance depends heavily on your team...", "author": "Senior Software Engineer - Current Employee", "datePublished": "2026-02-15", "scrapedAt": "2026-03-18T14:30:00.000Z" } ```` ### Use Cases - **Employer Brand Analysis** — Monitor how employees perceive your company vs competitors - **HR Research** — Identify recurring workplace issues and improvement areas from review patterns - **Competitive Intelligence** — Understand competitor company culture, benefits, and pain points - **Job Seeker Research** — Aggregate reviews to make informed career decisions at scale - **Sentiment Tracking** — Analyze how employee sentiment changes over time for specific companies - **Compensation Research** — Cross-reference review data with reported salary and benefits information ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | companyUrls | array | \[] | Glassdoor company review page URLs | | searchQueries | array | \[] | Company names to search (e.g., "Google", "Microsoft") | | maxReviewsPerCompany | integer | 30 | Maximum reviews to extract per company (1-500) | | sortBy | string | "date" | Sort reviews by "date" or "relevance" | ### How It Works The scraper uses CheerioCrawler with User-Agent rotation to navigate Glassdoor pages. For company searches, it first finds employer profiles from search results and converts overview URLs to review page URLs. Reviews are extracted using three methods in priority order: JSON-LD structured data, HTML review card selectors, and embedded JavaScript state parsing. Pagination increments the page number in the URL to collect additional reviews. ### Limitations - Glassdoor may require CAPTCHA verification or login for some pages; using Apify Proxy with residential IPs is recommended - Review data availability depends on Glassdoor's anti-scraping measures, which may limit results in some cases # Actor input Schema ## `companyUrls` (type: `array`): Glassdoor company review page URLs ## `searchQueries` (type: `array`): Search Glassdoor for companies by name (e.g., 'Google', 'Microsoft') ## `maxReviewsPerCompany` (type: `integer`): Maximum number of employee reviews to extract per company ## `sortBy` (type: `string`): Sort reviews by date or relevance ## Actor input object example ```json { "companyUrls": [], "searchQueries": [], "maxReviewsPerCompany": 30, "sortBy": "date" } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("knotless_cadence/glassdoor-reviews-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 = {} # Run the Actor and wait for it to finish run = client.actor("knotless_cadence/glassdoor-reviews-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 '{}' | apify call knotless_cadence/glassdoor-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=knotless_cadence/glassdoor-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Glassdoor Reviews Scraper", "description": "Scrape Glassdoor company reviews — ratings, pros, cons, salaries. Employer brand monitoring and talent intelligence. JSON/CSV export. Custom tool in 48h, $100 pilot. Email: spinov001@gmail.com • Tips: t.me/scraping_ai", "version": "1.0", "x-build-id": "YkctgSWwXbdcWgzhi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/knotless_cadence~glassdoor-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-knotless_cadence-glassdoor-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/knotless_cadence~glassdoor-reviews-scraper/runs": { "post": { "operationId": "runs-sync-knotless_cadence-glassdoor-reviews-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/knotless_cadence~glassdoor-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-knotless_cadence-glassdoor-reviews-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", "properties": { "companyUrls": { "title": "Company URLs", "type": "array", "description": "Glassdoor company review page URLs", "default": [], "items": { "type": "string" } }, "searchQueries": { "title": "Search Companies", "type": "array", "description": "Search Glassdoor for companies by name (e.g., 'Google', 'Microsoft')", "default": [], "items": { "type": "string" } }, "maxReviewsPerCompany": { "title": "Max Reviews Per Company", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of employee reviews to extract per company", "default": 30 }, "sortBy": { "title": "Sort By", "enum": [ "date", "relevance" ], "type": "string", "description": "Sort reviews by date or relevance", "default": "date" } } }, "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 } } } } } } } } } } ```