💼 Glassdoor Scraper

🚀 Pull Glassdoor employee reviews, salaries, and ratings by company. Export structured records for any Glassdoor employer across 18 international domains in minutes. No API key, no login, no manual copy-paste.

🕒 Last updated: 2026-04-21 · 📊 40 fields per review · ⭐ Reviews & salaries · 🏢 Company ratings · 🌍 Multi-locale · 🚫 No auth required

The Glassdoor Scraper collects employee reviews, salary reports, interview experiences, jobs, benefits, office locations, and culture-and-diversity data from any Glassdoor company page. Point it at a Glassdoor employer URL (for example https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm) or search by company name, and get back clean structured JSON.

The scraper understands every regional Glassdoor domain (.com, .co.uk, .fr, .de, .es, .nl, .com.br, .ca, .com.au, and more), supports date filters and multi-language review pulls, and works across any public employer profile. Output works directly in spreadsheets, BI tools, or your data warehouse.

🎯 Target Audience	💡 Primary Use Cases
HR analytics teams, recruiters, talent acquisition, competitive-intelligence analysts, investors, journalists, data scientists	Employer brand tracking, salary benchmarking, sentiment analysis, candidate research, M&A due diligence, competitive hiring intel

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📋 What the Glassdoor Scraper does

Eight structured collection modes in a single run:

• 📝 Reviews. Overall rating, CEO rating, pros, cons, advice, work-life balance, culture, diversity, and employer responses.
• 💰 Salaries. Base pay, total pay, bonuses, stock, profit sharing, and tips by job title and currency.
• 🎤 Interviews. Questions, outcomes, difficulty, experience, offer status, and source per report.
• 💼 Jobs. Open roles with title, location, pay range, easy-apply flag, and optional full job description.
• 🧭 Overview. Headquarters, company size, industry, revenue, founded year, and website.
• 📍 Locations. Office addresses across cities and countries.
• 🎁 Benefits. Benefit categories, ratings, comments, and employee reviews.
• 🌈 Culture & Diversity. Demographic distributions, diversity programs, and culture ratings.

Pick a single mode with the command field (reviews, salaries, interviews, jobs, overview, locations, benefits, cultureDiversity) or pass "all" to sweep everything in one run. Date filters (reviewsStartDate, interviewsStartDate, benefitsStartDate) restrict output to recent records only.

💡 Why it matters: Glassdoor hosts millions of firsthand employee reports across tens of thousands of companies. That corpus is one of the most cited sources for compensation benchmarks, employer-brand sentiment, and hiring competitive intelligence. Building your own collector means handling pagination, language variants, and fragile HTML. This Actor returns clean JSON you can load straight into analysis.

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🎬 Full Demo

🚧 Coming soon: a 3-minute walkthrough from sign-up to a downloaded dataset.

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⚙️ Input

Input	Type	Default	Behavior
startUrls	array	[Google]	Glassdoor company URLs. Any international domain supported.
maxItems	integer	10	Records to return per run. Free plan caps at 100, paid plan at 1,000,000.
companyName	string	""	Alternative to startUrls. Search by employer name (e.g. Google).
command	string	"all"	One of reviews, salaries, interviews, jobs, overview, locations, benefits, cultureDiversity, or all.
sortReviewsBy	string	"RELEVANCE"	Review sort order. Use DATE for newest-first.
includeAllReviews	boolean	false	Include reviews in every language instead of the domain default.
includeAllSalaries	boolean	false	Include salaries across every supported language.
includeCompanyReviewStats	boolean	false	Attach company-level review aggregates (overall rating, CEO approval, distribution).
includeCompanyInterviewStats	boolean	false	Attach interview aggregates (difficulty, experience counts).
includeCompanyBenefitsStats	boolean	false	Attach benefits overview and category statistics.
includeJobDetails	boolean	false	Fetch full job description from each posting page. Slower but richer.
reviewsStartDate	string	null	ISO date (YYYY-MM-DD). Only returns reviews on or after this date.
interviewsStartDate	string	null	ISO date floor for interview records.
benefitsStartDate	string	null	ISO date floor for benefit review records.
proxyConfiguration	object	RESIDENTIAL	Residential Apify proxy. Required for Glassdoor.

Example: 100 most recent Google reviews, newest first.

{
    "startUrls": [
        { "url": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm" }
    ],
    "maxItems": 100,
    "command": "reviews",
    "sortReviewsBy": "DATE"
}

Example: everything Glassdoor has on Apple, stats included.

{
    "startUrls": [
        { "url": "https://www.glassdoor.com/Overview/Working-at-Apple-EI_IE1138.htm" }
    ],
    "maxItems": 500,
    "command": "all",
    "includeCompanyReviewStats": true,
    "includeCompanyInterviewStats": true
}

Example: salary reports for SAP on the German domain.

{
    "startUrls": [
        { "url": "https://www.glassdoor.de/Gehalt/SAP-Gehalter-E10471.htm" }
    ],
    "maxItems": 200,
    "command": "salaries"
}

⚠️ Good to Know: results reflect what is publicly visible on the matching Glassdoor regional domain. Review counts, salary samples, and translated content vary by country and by the reviewer's chosen language. When you need full coverage, enable includeAllReviews and includeAllSalaries.

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📊 Output

Each record carries a dataType discriminator (review, salary, interview, job, overview, location, benefit, cultureDiversity) so you can split the dataset downstream. Download as CSV, Excel, JSON, or XML.

🧾 Review schema (40 fields)

Field	Type	Example
🏢 companyName	string	"Google"
🆔 companyId	number	9079
🔗 companyUrl	string	"https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"
🏷️ dataType	string	"review"
🆔 reviewId	number	81234567
📅 reviewDateTime	ISO 8601	"2026-04-10T12:34:00.000Z"
⭐ ratingOverall	number	4
👔 ratingCeo	string | null	"APPROVE"
📈 ratingBusinessOutlook	string | null	"POSITIVE"
⚖️ ratingWorkLifeBalance	number	4
🎭 ratingCultureAndValues	number	5
🌈 ratingDiversityAndInclusion	number	4
🚀 ratingCareerOpportunities	number	4
🧭 ratingSeniorLeadership	number	3
💵 ratingCompensationAndBenefits	number	5
🤝 ratingRecommendToFriend	string | null	"POSITIVE"
📌 isCurrentJob	boolean	true
⏳ lengthOfEmployment	number	3
💼 employmentStatus	string	"REGULAR"
⭐ featured	boolean	false
🌐 languageId	string	"eng"
🌐 originalLanguageId	string	"eng"
🔁 translationMethod	string | null	null
👍 countHelpful	number	12
👎 countNotHelpful	number	1
💼 jobTitle	object	{ "id": 1, "text": "Software Engineer" }
📍 location	object | null	{ "id": 11527, "name": "Mountain View, CA", "type": "CITY" }
🏢 employer	object	{ "id": 9079, "shortName": "Google", "squareLogoUrl": "..." }
📝 summary	string	"Great place to grow."
📝 summaryOriginal	string	"Great place to grow."
✅ pros	string	"Strong engineering culture, benefits..."
✅ prosOriginal	string	"Strong engineering culture, benefits..."
❌ cons	string	"Large-org politics at times."
❌ consOriginal	string	"Large-org politics at times."
💡 advice	string | null	"Keep protecting 20% time."
💡 adviceOriginal	string | null	"Keep protecting 20% time."
💬 employerResponses	array	[]
📊 companyReviewStats	object | null	see sample (when enabled)
🕒 scrapedAt	ISO 8601	"2026-04-21T08:00:00.000Z"
❗ error	string | null	null

🧾 Salary schema (key fields)

Field	Type	Example
🏢 companyName	string	"Google"
🏷️ dataType	string	"salary"
💼 jobTitle	object	{ "id": 99, "text": "Software Engineer" }
📊 salaryCount	number	8523
💱 currency	object	{ "code": "USD" }
💵 basePayStatistics	object	{ "percentiles": [{ "ident": "P50", "value": 185000 }] }
💰 totalPayStatistics	object	includes P10, P25, P50, P75, P90
🎁 totalAdditionalPayStatistics	object	bonus, stock, profit-sharing roll-ups
💵 cashBonusStatistics	object	cash bonus percentiles
📈 stockBonusStatistics	object	stock percentiles
🕒 scrapedAt	ISO 8601	"2026-04-21T08:00:00.000Z"

Jobs, interviews, benefits, culture, locations, and overview modes expose their own structured payloads with the same shape discipline (see sample records below).

📦 Sample records

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✨ Why choose this Actor

	Capability
🌍	18 domains supported. .com, .co.uk, .de, .fr, .es, .nl, .it, .com.br, .ca, .com.au, and more. Scrape any international Glassdoor profile.
🔄	Eight data modes in one Actor. Reviews, salaries, interviews, jobs, overview, locations, benefits, culture. Use command: "all" to collect everything.
📅	Date filters. Pull only reviews, interviews, or benefits on or after a chosen date for fresh-trend analysis.
🌐	Multi-language coverage. Toggle includeAllReviews or includeAllSalaries to pull every supported language per profile.
📊	Structured JSON. Every record has a stable schema with typed ratings, employer metadata, and timestamps.
🔎	Search by name or URL. Paste a Glassdoor URL or pass companyName and the Actor resolves the employer automatically.
🚫	No authentication. Works with public employer profiles. No login, no API key.

📊 Glassdoor is one of the most quoted sources for employer brand, compensation benchmarks, and candidate sentiment. Clean structured exports enable analytics that a manual review read-through never can.

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📈 How it compares to alternatives

Approach	Cost	Coverage	Refresh	Structured output	Setup
⭐ Glassdoor Scraper (this Actor)	$5 free credit, then pay-per-use	All 18 Glassdoor domains	Live per run	8 data modes, typed fields	⚡ 2 min
Official Glassdoor API	Not available to most use cases	Limited endpoints	Rate-limited	Partial	🐢 Approval-gated
Manual copy-paste	Free	Tiny sample	Whenever you do it	❌ Unstructured	🕒 Hours per company
Generic web crawlers	Varies	Hit-or-miss	Ad hoc	Raw HTML	⏳ Custom engineering

Pick this Actor when you want broad multi-domain coverage, structured fields, and zero scraping engineering on your side.

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🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the Glassdoor Scraper page on the Apify Store.
3. 🎯 Set input. Paste a company URL (or company name), pick a command, set maxItems.
4. 🚀 Run it. Click Start and let the Actor collect your data.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.

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💼 Business use cases

🧑‍💼 Talent & Recruiting Employer-brand tracking per competitor Candidate sentiment dashboards Attrition-signal monitoring (review-volume spikes) Interview-difficulty benchmarks per role	💰 Compensation Analytics Salary benchmarking by title and region Total-comp breakdowns (base, bonus, stock) Pay-equity studies with currency normalization Country-by-country comp ranges
📈 Investors & Analysts Employee sentiment as a leading indicator CEO approval trend tracking Diversity-metric comparisons across peers Culture pulse for M&A due diligence	📰 Researchers & Journalists Large-N review corpora for NLP studies Industry-wide culture comparisons Longitudinal tracking of employer scores Story research on labor trends

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🌟 Beyond business use cases

Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.

🎓 Research and academia Empirical datasets for papers, thesis work, and coursework Longitudinal studies tracking changes across snapshots Reproducible research with cited, versioned data pulls Classroom exercises on data analysis and ethical scraping	🎨 Personal and creative Side projects, portfolio demos, and indie app launches Data visualizations, dashboards, and infographics Content research for bloggers, YouTubers, and podcasters Hobbyist collections and personal trackers
🤝 Non-profit and civic Transparency reporting and accountability projects Advocacy campaigns backed by public-interest data Community-run databases for local issues Investigative journalism on public records	🧪 Experimentation Prototype AI and machine-learning pipelines with real data Validate product-market hypotheses before engineering spend Train small domain-specific models on niche corpora Test dashboard concepts with live input

🤖 Ask an AI assistant about this scraper

Open a ready-to-send prompt about this ParseForge actor in the AI of your choice:

• 💬 ChatGPT
• 🧠 Claude
• 🔍 Perplexity
• 🅒 Copilot

❓ Frequently Asked Questions

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🔌 Automating Glassdoor Scraper

Control the scraper programmatically for scheduled runs and pipeline integrations:

• 🟢 Node.js. Install the apify-client NPM package.
• 🐍 Python. Use the apify-client PyPI package.
• 📚 See the Apify API documentation for full details.

The Apify Schedules feature lets you trigger this Actor on any cron interval. Hourly, daily, or weekly refreshes keep downstream sentiment and comp dashboards in sync automatically.

🔌 Integrate with any app

Glassdoor Scraper connects to any cloud service via Apify integrations:

• Make - Automate multi-step workflows
• Zapier - Connect with 5,000+ apps
• Slack - Get run notifications in your channels
• Airbyte - Pipe review and salary data into your warehouse
• GitHub - Trigger runs from commits and releases
• Google Drive - Export datasets straight to Sheets

You can also use webhooks to trigger downstream actions when a run finishes. Push fresh review or salary data into your product backend, or alert your analytics team in Slack.

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🔗 Recommended Actors

• 💼 Glassdoor Jobs Scraper - Job postings from Glassdoor with salary, location, and JSON-LD schema
• 🔍 Indeed Scraper - Job listings and company pages from Indeed
• 🏢 LinkedIn Company Profiles Scraper - Company size, industry, specialties, and follower counts
• 💼 ZipRecruiter Scraper - Jobs from ZipRecruiter with pay and company metadata
• 🧑‍💻 CareerBuilder Scraper - Job postings from CareerBuilder with salary and location

💡 Pro Tip: browse the complete ParseForge collection for more HR and talent-intel scrapers.

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🆘 Need Help? Open our contact form to request a new scraper, propose a custom data project, or report an issue.

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⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Glassdoor or its parent company. All trademarks mentioned are the property of their respective owners. Only publicly available data visible to any signed-out visitor is collected.