---

⭐ Glassdoor Scraper — Reviews, Jobs, Salaries, Interviews & AI Employer Intelligence

---

Glassdoor Scraper — extract 100% genuine employee reviews, job postings, salary estimates, interview experiences, benefits feedback, company overviews, culture ratings, office locations, and AI Employer Intelligence (pain-point analysis, attrition risk, quick wins) at scale. No login required. Built for recruiters, HR teams, investors, market researchers, and AI training datasets.

If you searched for glassdoor scraper, glassdoor reviews scraper, glassdoor salary scraper, glassdoor jobs scraper, glassdoor interview questions API, glassdoor company reviews extractor, employer intelligence tool, AI HR analytics, company culture ratings, attrition risk analyzer, or a no-login glassdoor data extractor — this is the actor you're looking for. ✅

---

💡 What is the Glassdoor Scraper?

Glassdoor is the world's #1 platform for employee reviews, salaries, interview experiences, and employer insights — covering 1M+ companies and 100M+ data points. This Glassdoor scraper turns that data into a structured, ready-to-use dataset.

Just feed it a company URL (Google, Amazon, Microsoft, Meta, Apple, Reliance, or any employer), and the actor returns everything including:

• ⭐ Employee Reviews (8 sub-ratings, pros, cons, advice, employer responses)
• 💼 Active Job Postings (with salary bands & resume keyword matching)
• 💰 Salary Estimates (P10/P25/P50/P75/P90 across base, bonus, stock, total)
• 🎤 Interview Questions, difficulty, process & outcomes
• 🏥 Benefits Reviews (category, comments, ratings)
• 🏢 Company Overview (funding, revenue, headquarters, CEO, industry)
• 🌍 Culture & Diversity Ratings (gender, race, LGBTQ+, veteran)
• 📍 Office Locations (with coordinates)
• 🧠 AI Employer Intelligence — pain point analysis, severity, attrition risk, quick wins

All data is 100% real. No fabricated entries.

---

🔥 SEO Keywords (Why This Glassdoor Scraper Ranks)

This actor ranks for glassdoor scraper, glassdoor reviews scraper, glassdoor salary scraper, glassdoor jobs scraper, glassdoor interview questions, glassdoor company data, glassdoor API alternative, employer intelligence, employee review extractor, salary benchmark API, interview difficulty data, company culture ratings, diversity and inclusion ratings, attrition risk analyzer, AI HR analytics, employer brand monitoring, recruiting intelligence, compensation benchmarking, no login glassdoor scraper, apify glassdoor actor, glassdoor data API, HR data scraper.

---

🚀 Key Features

Feature	Description
8 Scrape Commands	reviews, jobs, salaries, interviews, benefits, overview, culture, locations, painPointAnalysis.
Zero Login Required	No Glassdoor account, no cookie, no API key.
Keyword Job Search	Search jobs by keyword + location across all Glassdoor employers.
Resume Keyword Matching	Auto-calculates match score per job against your skills list.
Full Reviews with 8 Sub-Ratings	Overall, WLB, culture, D&I, career, comp, leadership, CEO approval, business outlook.
Salary Percentiles	P10/P25/P50/P75/P90 across base, cash bonus, stock, and total comp.
Interview Deep Dive	Difficulty, experience, outcome, full process description, sample questions.
Benefits Ratings	Verified employee comments + benefit category breakdowns.
Company Enrichment	Funding, investors, employee count, LinkedIn, revenue, industry.
Culture & Diversity	Gender, race/ethnicity, LGBTQ+, veteran demographic ratings.
AI Employer Intelligence	Complaint themes, severity scoring, attrition risks, and quick wins.
Monitoring Mode	Tracks seen IDs across runs so scheduled runs return only new items.
Multi-URL Support	Scrape multiple companies in one run with fair budget distribution.
Pay-Per-Event Pricing	Only charged for successfully delivered items.

---

📥 Input Parameters

Parameter	Type	Required	Default	Description
command	string	Yes	"reviews"	reviews, jobs, salaries, interviews, benefits, overview, culture, locations, painPointAnalysis.
startUrls	array	No	Google Reviews	Company URLs like https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm.
searchJobsByKeyword	boolean	No	false	Enable keyword job search mode.
searchKeyword	string	No	""	Job keyword (e.g. "software engineer").
searchLocation	string	No	""	Location (e.g. "Remote" or "San Francisco, CA").
jobType	string	No	"all"	full-time, part-time, contract, internship.
remoteWorkType	string	No	"all"	remote, hybrid, onsite.
resumeKeywords	array	No	[]	Skills for auto match-score per job.
includeAllReviews	boolean	No	true	Fetch all reviews up to maxItems.
sortReviewsBy	string	No	"DATE"	DATE, RATING, HELPFUL.
includes	array	No	[]	Keyword filters on review text.
reviewsStartDate	string	No	""	Earliest review date (YYYY-MM-DD).
painPointAnalysis	boolean	No	false	Auto-run AI Employer Intelligence on reviews.
monitoringModeForReviews	boolean	No	false	Skip previously seen reviews across runs.
includeCompanyReviewStats	boolean	No	true	Include rating distribution block.
includeAllSalaries	boolean	No	true	Fetch all salary estimates.
includeCompanyInterviewStats	boolean	No	true	Include interview difficulty distribution.
includeCompanyBenefitsStats	boolean	No	true	Include benefits category stats.
maxItems	integer	No	100	Max total items to return.
maxConcurrency	integer	No	5	Parallel workers.
proxy	object	No	–	Apify proxy config. Residential recommended.

---

📤 Output Schemas (All Commands)

1. command: "reviews" — Employee Review

{
  "__typename": "EmployerReviewRG",
  "reviewId": 140610000,
  "summary": "Great culture, smart peers, excellent benefits",
  "ratingOverall": 5,
  "ratingWorkLifeBalance": 4,
  "ratingCultureAndValues": 5,
  "ratingDiversityAndInclusion": 5,
  "ratingCareerOpportunities": 4,
  "ratingCompensationAndBenefits": 5,
  "ratingSeniorLeadership": 4,
  "ratingCeo": "APPROVE",
  "ratingBusinessOutlook": "POSITIVE",
  "ratingRecommendToFriend": "POSITIVE",
  "pros": "The colleagues here are incredibly talented, kind, and supportive...",
  "cons": "Decision-making has slowed down in recent years...",
  "advice": "Empower ICs to make architectural decisions faster...",
  "jobTitleText": "Senior Software Engineer",
  "locationName": "Mountain View, CA",
  "employmentStatus": "FORMER",
  "lengthOfEmployment": 4,
  "shortName": "Google",
  "reviewDateTime": "2026-10-15T04:08:59.000"
}

2. command: "jobs" — Job Posting

{
  "__typename": "JobViewHeader",
  "jobListingId": "1009000000001",
  "jobTitleText": "Senior Software Engineer",
  "locationName": "San Francisco, CA",
  "needsCommission": false,
  "payCurrency": "USD",
  "payPeriod": "ANNUAL",
  "payPeriodAdjustedPay": {
    "p10": 175000.0,
    "p90": 240000.0
  },
  "salarySource": "EMPLOYER_PROVIDED",
  "easyApply": true,
  "seoJobLink": "https://www.glassdoor.com/job-listing/...",
  "matchScore": 87.5,
  "matchedSkills": ["python", "aws"],
  "missingSkills": ["kubernetes"]
}

3. command: "salaries" — Salary Estimate

{
  "__typename": "AggregatedSalaryEstimatesResult",
  "jobTitle": { "text": "Senior Software Engineer" },
  "currency": { "code": "USD", "symbol": "$" },
  "payPeriod": "ANNUAL",
  "salaryCount": 980,
  "basePayStatistics": {
    "mean": 195000.0,
    "percentiles": [
      { "ident": "P10", "value": 145200.0 },
      { "ident": "P25", "value": 165000.0 },
      { "ident": "P50", "value": 195000.0 },
      { "ident": "P75", "value": 220000.0 },
      { "ident": "P90", "value": 245000.0 }
    ]
  },
  "cashBonusStatistics": { "mean": 25000.0 },
  "stockBonusStatistics": { "mean": 50000.0 },
  "totalPayStatistics": {
    "mean": 270000.0,
    "percentiles": [
      { "ident": "P25", "value": 215000.0 },
      { "ident": "P50", "value": 270000.0 },
      { "ident": "P90", "value": 375000.0 }
    ]
  }
}

4. command: "interviews" — Interview Experience

{
  "__typename": "InterviewIG",
  "id": 90000001,
  "difficulty": "DIFFICULT",
  "experience": "POSITIVE",
  "outcome": "OFFER_ACCEPTED",
  "jobTitle": { "text": "Software Engineer" },
  "processDescription": "Initial recruiter screen, technical phone screen on CoderPad...",
  "userQuestions": [
    {
      "question": "Design a distributed rate limiter that handles 100,000 requests per second...",
      "answerCount": 4
    }
  ],
  "reviewDateTime": "2026-10-10T04:08:59.000"
}

5. command: "benefits" — Benefits Review

{
  "__typename": "BenefitReview",
  "id": 10500001,
  "rating": 5,
  "currentJob": true,
  "userEnteredJobTitle": "Software Engineer",
  "city": { "name": "Mountain View, CA" },
  "benefitComments": [
    {
      "comment": "Comprehensive medical, dental, and vision with 100% employer-paid premiums...",
      "helpfulVotes": 3
    }
  ],
  "companyBenefitStats": {
    "overallBenefitRating": 4.5,
    "totalBenefitReviews": 42
  }
}

6. command: "overview" — Company Overview

{
  "__typename": "Employer",
  "id": 9079,
  "shortName": "Google",
  "name": "Google",
  "website": "https://about.google/",
  "headquarters": "Mountain View, CA",
  "size": "10000+ Employees",
  "yearFounded": 1998,
  "type": "Company - Public",
  "revenue": "$10+ billion (USD)",
  "primaryIndustry": {
    "industryId": 200063,
    "industryName": "Internet & Web Services"
  },
  "ratings": { "overallRating": 4.3, "ceoRating": 0.79 },
  "counts": { "reviewCount": 48200, "salaryCount": 115000 },
  "overview": {
    "mission": "To organize the world's information and make it universally accessible and useful."
  }
}

7. command: "culture" — Diversity Ratings

{
  "__typename": "DemographicRatings",
  "category": "gender",
  "categoryRatings": [
    {
      "categoryValue": "woman",
      "ratings": { "overallRating": 4.1, "reviewCount": 1420 }
    }
  ]
}

8. command: "locations" — Office Location

{
  "__typename": "EmployerOfficeAddressEG",
  "id": 109079,
  "cityName": "Mountain View",
  "administrativeAreaName1": "CA",
  "countryName": "US",
  "latitude": 37.422,
  "longitude": -122.084
}

9. command: "painPointAnalysis" — AI Employer Intelligence

{
  "__typename": "PainPointAnalysis",
  "employerId": 9079,
  "employerName": "Google",
  "totalReviewsAnalyzed": 50,
  "overallSentiment": "POSITIVE",
  "overallRating": 4.3,
  "painPoints": [
    {
      "theme": "Bureaucracy & Layers of Middle Management",
      "severity": 4,
      "frequencyPercent": 24.5,
      "sampleQuote": "Decision-making has slowed down significantly; simple product approvals now require navigating multiple layers of VP reviews.",
      "department": "Engineering & Product"
    },
    {
      "theme": "Promotion Rubrics & Calibration Frustration",
      "severity": 4,
      "frequencyPercent": 21.0,
      "sampleQuote": "Perf calibration feels increasingly political and disconnected from everyday engineering contributions.",
      "department": "Engineering"
    }
  ],
  "standoutStrengths": [
    "World-class, humble, and exceptionally talented peer group",
    "Top-tier compensation packages, equity liquidity, and retirement matching",
    "Exceptional internal technical infrastructure and compute resources"
  ],
  "attritionRiskSignals": [
    {
      "signal": "Senior technical talent voicing burnout over organizational friction rather than technical challenges",
      "riskLevel": "HIGH",
      "affectedRoles": ["Staff Software Engineer", "Senior Product Manager"]
    }
  ],
  "quickWins": [
    "Flatten cross-org approval committees for feature launches under a defined threshold",
    "Publish transparent promotion calibration rubrics with explicit manager accountability"
  ],
  "analyzedAt": "2026-10-16T00:00:00Z"
}

---

📚 Full Input & Output Examples

🔹 Example 1 — Scrape Google Reviews

Input:

{
  "command": "reviews",
  "startUrls": [
    { "url": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm" }
  ],
  "maxItems": 50,
  "sortReviewsBy": "DATE",
  "includeCompanyReviewStats": true
}

Output: Array of EmployerReviewRG records as shown above.

---

🔹 Example 2 — Keyword Job Search

Input:

{
  "command": "jobs",
  "searchJobsByKeyword": true,
  "searchKeyword": "software engineer",
  "searchLocation": "Remote",
  "jobType": "full-time",
  "remoteWorkType": "remote",
  "maxItems": 100,
  "resumeKeywords": [
    { "keyword": "python" },
    { "keyword": "aws" },
    { "keyword": "kubernetes" }
  ]
}

Output: Array of JobViewHeader records with matchScore, matchedSkills, and missingSkills per job.

---

🔹 Example 3 — Salary Benchmark

Input:

{
  "command": "salaries",
  "startUrls": [
    { "url": "https://www.glassdoor.com/Salary/Amazon-Salaries-E6036.htm" }
  ],
  "maxItems": 30
}

Output: Array of AggregatedSalaryEstimatesResult records with base/bonus/stock/total percentiles.

---

🔹 Example 4 — Interview Intelligence

Input:

{
  "command": "interviews",
  "startUrls": [
    { "url": "https://www.glassdoor.com/Interview/Meta-Interview-Questions-E40772.htm" }
  ],
  "maxItems": 20
}

Output: Array of InterviewIG records with questions, difficulty, process, and outcome.

---

🔹 Example 5 — Benefits & Culture

Input:

{
  "command": "benefits",
  "startUrls": [
    { "url": "https://www.glassdoor.com/Benefits/Apple-US-Benefits-EI_IE1138.0,5_IL.6,8_IN1.htm" }
  ],
  "maxItems": 20
}

Output: Array of BenefitReview records with verified comments.

---

🔹 Example 6 — AI Employer Intelligence

Input:

{
  "command": "painPointAnalysis",
  "startUrls": [
    { "url": "https://www.glassdoor.com/Reviews/Amazon-Reviews-E6036.htm" }
  ],
  "painPointAnalysis": true
}

Output: A single PainPointAnalysis object with themes, severity scores, attrition risk, and quick wins.

---

🔹 Example 7 — Multi-Company Batch Scrape

Input:

{
  "command": "overview",
  "startUrls": [
    { "url": "https://www.glassdoor.com/Overview/Working-at-Google-EI_IE9079.htm" },
    { "url": "https://www.glassdoor.com/Overview/Working-at-Microsoft-EI_IE1651.htm" },
    { "url": "https://www.glassdoor.com/Overview/Working-at-Meta-EI_IE40772.htm" }
  ],
  "maxItems": 10
}

Output: Array of Employer overview records with rich metadata.

---

🔹 Example 8 — Monitoring Mode for New Reviews

Input:

{
  "command": "reviews",
  "startUrls": [
    { "url": "https://www.glassdoor.com/Reviews/Apple-Reviews-E1138.htm" }
  ],
  "monitoringModeForReviews": true,
  "maxItems": 100
}

Only new reviews (not seen in previous runs) are pushed.

---

💰 Pricing (Pay-Per-Event)

Only charged for successfully delivered items. Empty runs are $0 (except actor start).

Event	Event Name	Price / 1K	When Charged
Employee Review	review-scraped	$2.00 / 1,000	Per review delivered.
Job Posting	job-scraped	$2.00 / 1,000	Per job delivered.
Salary Estimate	salary-scraped	$3.00 / 1,000	Per salary record delivered.
Interview Experience	interview-scraped	$3.00 / 1,000	Per interview delivered.
Benefits Review	benefit-scraped	$2.00 / 1,000	Per benefits record delivered.
Company Overview	overview-scraped	$10.00 / 1,000	Per overview delivered.
AI Employer Intelligence	pain-point-analyzed	$35.00 / 1,000	Per AI analysis delivered.
Actor Start	apify-actor-start	$0.005 / run	One-time startup fee.

Example costs:

• 100 reviews = 100 × $0.002 = $0.20 + $0.005 start = $0.205
• 500 jobs = 500 × $0.002 = $1.00 + $0.005 start = $1.005
• 50 salaries = 50 × $0.003 = $0.15 + $0.005 start = $0.155
• 1 AI pain-point analysis = $0.035 + $0.005 start = $0.04

---

🛠 How to Use This Glassdoor Scraper on Apify

1. Create a task with this actor.
2. Choose your command (reviews, jobs, salaries, interviews, benefits, overview, culture, locations, painPointAnalysis).
3. Paste your company URLs or enable keyword job search.
4. Set maxItems to control the total volume.
5. Enable residential proxies — recommended for high-volume runs.
6. Run — data lands in the Dataset.
7. Export — download as JSON, CSV, or Excel.

Running via API

curl -X POST "https://api.apify.com/v2/acts/your-username~glassdoor-scraper/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "command": "reviews",
    "startUrls": [{"url": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"}],
    "maxItems": 50
  }'

---

🎯 Use Cases (Who Uses This Glassdoor Scraper)

• Recruiters & HR teams — benchmark employer ratings and culture.
• Investors & analysts — monitor attrition risk and sentiment shifts.
• Compensation consultants — extract percentile-based salary data.
• Job boards & aggregators — sync Glassdoor jobs into your platform.
• AI/ML teams — build labeled corpora from reviews and interviews.
• Employer branding — track sentiment and respond to pain points.
• Career coaches — guide clients using interview difficulty data.
• Academic researchers — study workplace culture, D&I, and compensation trends.
• Startup founders — research competitor hiring pace and team size.
• DEI consultants — analyze demographic ratings across companies.

---

❓ Frequently Asked Questions

1. Do I need a Glassdoor account?
No. The actor works anonymously — no login, no cookie, no API key.

2. Can I search jobs by keyword?
Yes. Set searchJobsByKeyword: true and provide a searchKeyword + searchLocation.

3. What is painPointAnalysis?
AI Employer Intelligence: clusters reviews into complaint themes, scores severity, identifies attrition risks, and proposes quick wins. Perfect for HR dashboards.

4. What's the difference between reviews and culture?
reviews returns individual employee reviews. culture returns aggregate demographic ratings (gender, race, LGBTQ+, veteran).

5. Does monitoring mode really skip duplicate reviews?
Yes. Seen review IDs are stored in the actor's Key-Value Store so scheduled runs return only new items.

6. What currencies are supported?
Salaries are returned in USD by default. Native currency is preserved when shown by Glassdoor.

7. How accurate is the AI pain-point analysis?
It clusters real review text (pros/cons/summary) into ranked themes with severity and frequency. 100% based on genuine reviews.

8. Can I filter reviews by keyword?
Yes. Use includes array. Only reviews matching at least one keyword will be returned.

9. What's the difference between includeAllReviews and maxItems?
includeAllReviews: true fetches all available reviews (subject to maxItems). Setting it false returns only featured reviews.

10. Do I need a proxy?
Not for small runs. For 500+ items per run, use Apify residential proxies.

11. Can I run this on a schedule?
Yes. Combine with Apify Scheduler and enable monitoringModeForReviews: true to build a live employer intelligence feed.

12. What if I get 0 results?
Empty runs cost $0 (no charge for PPE). Only the actor start fee ($0.005) applies.

---

📝 Technical Notes

• Built with a production-grade HTTP pipeline optimized for Glassdoor's modern React SSR pages.
• Handles anonymous access, optional proxy configuration, and payload integrity automatically.
• Runs entirely server-side on Apify — no local setup required.
• Empty runs (0 results) are always free (no PPE charges). You only pay for successfully delivered records.
• Robust error handling: a single item failure never stops the run. Failures are logged and skipped.
• Duplicate protection: review IDs are deduplicated automatically within and across runs.
• Monitoring state and per-run summaries are stored in Apify Key-Value Store for scheduled monitoring.
• Multi-URL support with fair budget distribution across all provided targets.
• All records are validated for JSON-serializable output and sanitized for special characters.

---

🔗 Related Actors

• HiringCafe Scraper — Real-Time Jobs & Salaries
• RedNote Scraper — Xiaohongshu Posts, Comments, Profiles & Video
• LinkedIn Jobs Scraper — Ratings, Pros & Cons
• Weibo Scraper — Posts, Comments, Hot Search & Black Cat

---

📄 License

---

---

Start scraping Glassdoor today — reviews, jobs, salaries, interviews, AI employer intelligence. Zero login required.