TeamBlind Reviews Scraper: Tech Employer Ratings

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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

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

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.