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:

{
  "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:

{
  "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.