# TeamBlind Reviews Scraper: Tech Employer Ratings (`getascraper/teamblind-reviews-scraper`) Actor Scrape TeamBlind employer reviews with 24 fields per row: 6-axis ratings, full pros/cons, tenure, location, country, company aggregates. Always returns the full review text. No missing data. Drop-in for n8n, Make, Zapier. $2.49 per 1,000 results. - **URL**: https://apify.com/getascraper/teamblind-reviews-scraper.md - **Developed by:** [GetAScraper](https://apify.com/getascraper) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.49 / 1,000 reviews This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## TeamBlind Reviews Scraper: Tech Employer Ratings **Pull clean employer reviews from TeamBlind for any tech company, with 24 fields per row including 6 ratings, full pros and cons, tenure, and location.** Built for HR teams, recruiters, and competitive intelligence analysts who need real employee feedback without manual copy-paste. Drop the data straight into n8n, Make, Zapier, Airtable, or Google Sheets. $2.49 per 1,000 reviews. ### What does TeamBlind Reviews Scraper do? TeamBlind is the anonymous workplace review platform tech employees actually use. Google, Meta, Amazon, Stripe, and thousands of other tech companies have detailed reviews there that you will not find on Glassdoor. This Actor turns those public review pages into clean, structured data you can analyze. Every run gives you two outputs: - A **reviews dataset** with 24 fields per employee review. Six separate ratings (overall, career growth, work-life balance, compensation, culture, management), full pros and cons text, reviewer job title, city, country, tenure, and helpful vote count. - A **companies dataset** with aggregate data per company. Average rating, total review count, employee size, headquarters, founding year, industry, and reviewer distribution by city and country. You can export everything as JSON, CSV, Excel, or HTML and load it into any spreadsheet, dashboard, or workflow tool. ### Why use TeamBlind Reviews Scraper? Real employee feedback is one of the most valuable datasets in HR and recruiting. TeamBlind gives you the unfiltered truth because reviewers stay anonymous. - **Employer brand analysis.** See exactly how engineers rate your company on culture, management, and pay compared to your competitors. Spot where you win and where you lose. - **Recruiting intelligence.** Walk into candidate conversations knowing what current employees love and hate at target companies. Real pros and cons beat any Glassdoor score. - **Compensation benchmarking.** Track compensation ratings across thousands of tech companies in one dataset. Identify which employers pay well and which lag behind. - **Investor due diligence.** Watch employee sentiment trends at portfolio companies. Catch management or turnover warning signs before they hit the news. - **HR analytics at scale.** Pipe clean structured data into Airtable, Excel, Looker, or any BI tool. Schedule recurring runs for automated competitor tracking. ### How to use TeamBlind Reviews Scraper 1. Open the Actor in Apify Console and go to the **Input** tab. 2. Type company names like `Twilio`, `Stripe`, or `Meta` into the company names field. You can also paste TeamBlind review URLs. 3. Set your caps: maximum total reviews and maximum reviews per company. 4. Click **Start** and wait for the results. Most runs finish in under two minutes. 5. Download your data as JSON, CSV, Excel, or HTML. Connect your account to n8n, Make, or Zapier for automated workflows. ### Input | Field | Type | Required | Description | |---|---|---|---| | `startUrls` | array of URLs | No | TeamBlind review listing pages or individual review URLs. | | `companyNames` | array of strings | No | Company names like `Twilio`, `Stripe`, `Meta`. At least one of `startUrls` or `companyNames` is required. | | `maxItems` | integer | Yes | Maximum total reviews across the whole run. Default: 1000. | | `maxReviewsPerCompany` | integer | No | Maximum reviews saved per company before moving to the next. | | `monitoringMode` | boolean | No | Skip reviews you have already saved in earlier runs. Default: false. | | `fetchReviewDetails` | boolean | No | Always grab the full text of every review. Default: false. | | `maxConcurrency` | integer | No | How many pages to grab at the same time. Default: 10. | | `maxRequestRetries` | integer | No | How many times to retry a failed request. Default: 5. | | `proxyConfiguration` | object | No | Optional proxy settings for higher reliability. | ### Output You get two datasets per run. Each review row is structured JSON with 24 fields. Each company row is structured JSON with company metadata. Example review record: ```json { "id": 436627, "urlAlias": "z-eM7ygC89", "sourceUrl": "https://www.teamblind.com/company/Twilio/review/z-eM7ygC89", "rating": 3, "ratingCareer": 3, "ratingBalance": 3, "ratingCompensation": 4, "ratingCulture": 3, "ratingManagement": 3, "pros": "Used to be decent compensation, but now lagging behind. Good WLB though.", "cons": "Terrible product management. Constant reorgs and shifting priorities.", "summary": "Decent pay, mediocre company", "jobTitle": "Software Engineer", "memberLocation": "San Francisco, CA", "memberLocationCountryIsoCode": "US", "memberStart": 2020, "memberEnd": null, "isCurrentEmployee": true, "reviewDate": "2026-04-29T02:32:02.000Z", "helpfulCnt": 0, "companyResponse": null, "nickname": "u*****", "companyName": "Twilio", "companySlug": "Twilio" } ```` Example company record: ```json { "companyName": "Twilio", "companySlug": "Twilio", "logoUrl": "https://static.teamblind.com/img/channel/logo/us/3ee5273a649429.png", "webSiteUrl": "www.twilio.com", "founded": "2008", "employeeSize": "1,001 to 5,000 employees", "hqLocation": "San Francisco, CA", "industryName": "Internet", "rating": "3.5", "reviewCount": 1249, "cityDistribution": [ { "name": "San Francisco, CA", "count": 498 } ], "countryDistribution": [ { "isoCode": "US", "name": "United States", "count": 1004 } ] } ``` ### Data table | Field | Type | Description | |---|---|---| | `id` | integer | Stable TeamBlind review ID. | | `urlAlias` | string | Review permalink slug. | | `sourceUrl` | string | Full review detail page URL. | | `rating` | integer | Overall rating from 1 to 5. | | `ratingCareer` | integer | Career growth sub-rating from 1 to 5. | | `ratingBalance` | integer | Work-life balance sub-rating from 1 to 5. | | `ratingCompensation` | integer | Pay and benefits sub-rating from 1 to 5. | | `ratingCulture` | integer | Company culture sub-rating from 1 to 5. | | `ratingManagement` | integer | Management quality sub-rating from 1 to 5. | | `pros` | string | Full pros text from the reviewer. | | `cons` | string | Full cons text from the reviewer. | | `summary` | string | Review headline or one-line summary. | | `jobTitle` | string | Reviewer job title. | | `memberLocation` | string | Reviewer city, state, or country. | | `memberLocationCountryIsoCode` | string | Two-letter country code (ISO 3166). | | `memberStart` | integer | Year the reviewer started at the company. | | `memberEnd` | integer | Year the reviewer left. Null if still employed. | | `isCurrentEmployee` | boolean | True if the reviewer is a current employee. | | `reviewDate` | string | When the review was posted. | | `helpfulCnt` | integer | Number of helpful votes on the review. | | `companyResponse` | string | Official employer reply text when available. | | `nickname` | string | Anonymized reviewer display name. | | `companyName` | string | Company display name. | | `companySlug` | string | TeamBlind company slug. | ### Pricing You pay only for reviews successfully saved to your dataset. A typical company run with 1,000 reviews (such as Twilio) costs around **$2.49** and finishes in 30 to 90 seconds. Failed or skipped reviews are free. The first 100 rows of every run are free so you can test the data quality before paying. ### Tips - **Start small.** Run a single company with 20 to 50 reviews first to verify the data shape matches your needs. - **Use monitoring mode for recurring runs.** Turn on monitoring mode to only save new reviews since your last run. This cuts cost dramatically for weekly competitor tracking. - **Schedule weekly runs.** Set up a recurring schedule to track sentiment trends at competitor companies over time. - **Combine with Glassdoor data.** Run this Actor alongside a Glassdoor scraper for the broadest possible view of employer reputation. ### FAQ, disclaimers, and support **How is this different from Glassdoor?** TeamBlind is where tech employees post anonymously without fear of employer retaliation. Glassdoor is broader but TeamBlind has deeper coverage of tech companies, especially large public ones like Google, Meta, Amazon, and Stripe. **Does this scrape posts, feeds, or salaries?** No. This Actor focuses on company review pages only. Discussion posts, anonymous feeds, salary data, and login-gated content are out of scope. **Is this compliant with TeamBlind terms?** This Actor extracts publicly accessible review pages that anyone can read in a browser. You are responsible for ensuring your use complies with local laws, regulations, and platform terms of service. **Can I get a custom solution?** Open an issue in the Actor's Issues tab in Apify Console for feature requests, bug reports, or integration help. # Actor input Schema ## `startUrls` (type: `array`): TeamBlind company review listing URLs or individual review URLs. ## `companyNames` (type: `array`): Case-sensitive TeamBlind company names or slugs, e.g. Twilio, Stripe, Meta. ## `maxItems` (type: `integer`): Hard cap on the total number of reviews to save across all companies. ## `maxReviewsPerCompany` (type: `integer`): Optional per-company cap before moving to the next target. ## `fetchReviewDetails` (type: `boolean`): Fetch every review's detail page for redundant full-text extraction. ## `monitoringMode` (type: `boolean`): Skip reviews that were already saved in earlier runs using Key-Value Store deduplication. ## `maxConcurrency` (type: `integer`): Maximum parallel page and detail fetches. ## `maxRequestRetries` (type: `integer`): Number of retries for failed HTTP requests. ## `proxyConfiguration` (type: `object`): Proxy settings for anti-bot protection. Residential proxies are recommended for production. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.teamblind.com/company/Twilio/reviews" } ], "companyNames": [ "Twilio" ], "maxItems": 1000, "fetchReviewDetails": false, "monitoringMode": false, "maxConcurrency": 10, "maxRequestRetries": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `reviews` (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 = { "startUrls": [ { "url": "https://www.teamblind.com/company/Twilio/reviews" } ], "companyNames": [ "Twilio" ], "maxItems": 1000, "fetchReviewDetails": false, "monitoringMode": false, "maxConcurrency": 10, "maxRequestRetries": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("getascraper/teamblind-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 = { "startUrls": [{ "url": "https://www.teamblind.com/company/Twilio/reviews" }], "companyNames": ["Twilio"], "maxItems": 1000, "fetchReviewDetails": False, "monitoringMode": False, "maxConcurrency": 10, "maxRequestRetries": 5, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("getascraper/teamblind-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 '{ "startUrls": [ { "url": "https://www.teamblind.com/company/Twilio/reviews" } ], "companyNames": [ "Twilio" ], "maxItems": 1000, "fetchReviewDetails": false, "monitoringMode": false, "maxConcurrency": 10, "maxRequestRetries": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call getascraper/teamblind-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getascraper/teamblind-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TeamBlind Reviews Scraper: Tech Employer Ratings", "description": "Scrape TeamBlind employer reviews with 24 fields per row: 6-axis ratings, full pros/cons, tenure, location, country, company aggregates. Always returns the full review text. No missing data. Drop-in for n8n, Make, Zapier. $2.49 per 1,000 results.", "version": "0.2", "x-build-id": "kNLbgyMVG9ytaYwRk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getascraper~teamblind-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getascraper-teamblind-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/getascraper~teamblind-reviews-scraper/runs": { "post": { "operationId": "runs-sync-getascraper-teamblind-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/getascraper~teamblind-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-getascraper-teamblind-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", "required": [ "proxyConfiguration" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "TeamBlind company review listing URLs or individual review URLs.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "companyNames": { "title": "Company Names", "type": "array", "description": "Case-sensitive TeamBlind company names or slugs, e.g. Twilio, Stripe, Meta.", "default": [] }, "maxItems": { "title": "Max Reviews", "minimum": 1, "type": "integer", "description": "Hard cap on the total number of reviews to save across all companies.", "default": 1000 }, "maxReviewsPerCompany": { "title": "Max Reviews Per Company", "minimum": 1, "type": "integer", "description": "Optional per-company cap before moving to the next target." }, "fetchReviewDetails": { "title": "Fetch Review Details", "type": "boolean", "description": "Fetch every review's detail page for redundant full-text extraction.", "default": false }, "monitoringMode": { "title": "Monitoring Mode", "type": "boolean", "description": "Skip reviews that were already saved in earlier runs using Key-Value Store deduplication.", "default": false }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum parallel page and detail fetches.", "default": 10 }, "maxRequestRetries": { "title": "Max Retries", "minimum": 0, "type": "integer", "description": "Number of retries for failed HTTP requests.", "default": 5 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for anti-bot protection. Residential proxies are recommended for production.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```