Glassdoor Scraper

Glassdoor Scraper

Scrape Glassdoor reviews, salaries, interviews, jobs, and company data from any company URL or search, up to a million rows per run. Every row comes with ratings, dates, and full text. No login or API key. Export to CSV, JSON, Excel, or XML.

Glassdoor's official API is limited and requires partnership approval. This reads the public company pages directly, filtered by date, language, and section, and returns each match in one fixed schema. Get employee reviews, salary reports, interview experiences, job listings, benefits, and diversity data for any company on Glassdoor.

Who uses it	What they scrape Glassdoor for
Market researchers	Which companies in a sector have the best employee sentiment
Recruiters	What candidates say about a company's interview process
Job seekers	Which employers offer the pay and benefits they want
HR analysts	How a company's ratings trend over time
Data journalists	Which industries have the most reported salary gaps

What it does

This Actor collects Glassdoor data by company URL or company name search, and returns each item as a flat row.

• 📋 Company search or direct URLs: feed a company name like Google or a full Glassdoor URL, including international domains.
• 🗂️ Eight data sections: reviews, salaries, interviews, jobs, overview, locations, benefits, and culture & diversity, or scrape all at once.
• 📅 Date filters: set a start date for reviews, interviews, and benefits to get only recent data.
• 🌐 Language controls: include reviews and salaries in all languages or only the country's default.
• 📊 Company-level stats: optionally add review, interview, and benefits statistics for each company.
• 💼 Full job descriptions: optionally fetch complete job details from each listing.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with Glassdoor data

📈 Track employer reputation.

A market researcher scrapes reviews for the top 50 tech companies each month and charts rating trends to spot reputational shifts.

💰 Benchmark salaries.

An HR analyst scrapes salary reports for a set of competitors and compares pay ranges by role and location.

🎤 Prepare for interviews.

A job seeker scrapes interview experiences for a target company and reviews common questions and difficulty ratings.

🌍 Compare global offices.

A recruiter scrapes reviews and benefits for the same company across different country domains to advise candidates.

📰 Investigate workplace culture.

A data journalist scrapes culture and diversity data across an industry and reports on inclusion trends.

Why choose this scraper

	What you get
No API key	Scrape public Glassdoor pages without registration or rate limits
All sections	Reviews, salaries, interviews, jobs, benefits, and more in one run
International	Works with glassdoor.com, .co.uk, .fr, .de, and other domains
Flat output	Every item is a clean row ready for CSV, JSON, Excel, or XML

How it compares

No other Store actor targets Glassdoor the same way, so the honest comparison is with the alternatives teams actually weigh.

	Glassdoor Scraper	Build it in-house	By hand
Setup	Run it now, zero config	Days of engineering	None, but hours per pull
When Glassdoor changes	Maintained for you	You fix it	You re-learn the page
Proxies, retries, anti-bot	Built in	Your problem	Browser only
Output	Fixed JSON schema, CSV/Excel export	Whatever you build	Copy-paste
Cost	Pay per result	Engineering time	Analyst hours

Configure the run

Drive the Actor from company names or direct Glassdoor URLs, alone or together, and filters run as each item is read so only matches reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
  "startUrls": [
    {
      "url": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"
    }
  ],
  "maxItems": 10,
  "command": "reviews"
}

A larger pull:

{
  "startUrls": [
    {
      "url": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"
    }
  ],
  "maxItems": 200,
  "command": "reviews"
}

Pricing

Pay-per-result: $0.03199 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$3.20
1,000 results	$31.99
10,000 results	$319.90

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the Glassdoor Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to Glassdoor through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/glassdoor-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check that your company name or URL is correct and that the company has data for the selected section. Also verify your date filters are not too restrictive.

Why is the run slow?

Scraping all sections or enabling includeJobDetails visits more pages. Try selecting only the section you need, or reduce maxItems.

Why are some reviews missing?

Glassdoor may hide some reviews behind login or language settings. Enable includeAllReviews to get reviews in all languages, and check your date filter.

Can I scrape a company that has no reviews?

Yes, but you will get an empty dataset for the reviews section. Try another section like overview or jobs.

Why do I get an error when using both companyName and startUrls?

These fields are mutually exclusive. Use either companyName for a search or startUrls for direct URLs, not both.

FAQ

Question	Answer
Do I need a Glassdoor account or API key?	No. The Actor reads public Glassdoor pages directly. No login, API key, or partnership approval is required.
Can I scrape multiple companies in one run?	Yes. Provide multiple company names or URLs in the startUrls field, or use companyName for a single search. The Actor will process each one.
What data sections can I scrape?	You can choose reviews, salaries, interviews, jobs, overview, locations, benefits, culture & diversity, or all of them. Each section returns a different row shape.
Does it work with international Glassdoor domains?	Yes. You can provide URLs from glassdoor.com, glassdoor.co.uk, glassdoor.fr, glassdoor.de, and other country domains.
Can I filter reviews by date?	Yes. Use reviewsStartDate, interviewsStartDate, or benefitsStartDate to include only items from a specific date onwards, in YYYY-MM-DD format.
Can I include reviews in all languages?	Yes. Set includeAllReviews to true to get reviews in all languages, or leave it false to get only the country's default language.
How do I get full job descriptions?	Set includeJobDetails to true. The Actor will visit each job detail page and return the full description and employment type. This is slower but more complete.
What is the maximum number of items I can scrape?	You can set maxItems up to 1,000,000 per run. The Actor will stop after collecting that many items.
Can I get company-level statistics?	Yes. Enable includeCompanyReviewStats, includeCompanyInterviewStats, or includeCompanyBenefitsStats to add overall ratings, CEO approval, difficulty, and benefits overview to your dataset.
What output formats are supported?	You can export your results to CSV, JSON, Excel, or XML directly from the Apify platform.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Glassdoor, Inc. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.