Glassdoor Company Reviews Scraper

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🎯 What this scrapes

For each company you request, this Actor visits Glassdoor's public company Overview page and its Reviews pages and emits two kinds of rows into one dataset:

1. company_summary — one row per company: overall rating, CEO approval, business outlook, and recommend-to-friend percentage.
2. review — one row per individual review: overall + sub-category ratings (work-life balance, culture, career opportunities, compensation, senior management, diversity), pros, cons, advice to management, job title, employment status, review date, and helpful-vote counts.

No login, no account, no reviewer de-anonymization — only what Glassdoor's public pages show anonymously.

🔥 Features

• We clear the bot defenses guarding Glassdoor's review pages — a hardened browser layer with a proven navigation sequence gets through where a plain HTTP request gets turned away.
• We rotate proxy sessions on every retry — a fresh exit IP and session whenever a company's fetch fails.
• Per-company fault isolation — one company that fails to resolve or parse never fails the whole run; it's logged and skipped, and every other company still completes.
• Pydantic v2 input + output validation — every row is a typed, schema-enforced record; fields Glassdoor doesn't expose come back null, never guessed.
• Pay-Per-Event pricing — you're charged per row actually written to your dataset, not per request attempted.
• Honest throughput — Glassdoor's own anonymous-access limits cap full review text at a few reviews per page load; maxReviewsPerCompany and pricing reflect that reality rather than promising cheap bulk collection we can't deliver without a login we refuse to use.

💡 Use cases

• Employer-brand monitoring — track how your own company's reviews and ratings trend over time.
• Recruiting intelligence — pull culture and compensation signals for target companies before an outreach campaign.
• Competitive talent research — compare rating breakdowns and CEO approval across a peer set.
• Investment due diligence — culture and leadership signals as a qualitative input alongside financials.

⚙️ How to use it

1. Click Try for free at the top of the page.
2. Enter one or more companyNames — or, if you already know Glassdoor's internal employerId for a company, pass employerIds positionally alongside it to skip resolution entirely.
3. Set maxReviewsPerCompany to the depth you need (higher costs more — see Pricing).
4. Click Start. Output streams into the run's dataset.
5. Export from Storage → Dataset as JSON, CSV, or Excel — or fetch via the API.

📥 Input

Field	Type	Required	Default	Notes
companyNames	array	yes	—	Company names to scrape, e.g. ["Google", "Meta"].
employerIds	array	no	—	Known Glassdoor employerId values, paired positionally with companyNames. Skips resolution — the most reliable path.
maxReviewsPerCompany	integer	no	30	3-500. Anonymous access renders ~3 full reviews per page load; higher values cost proportionally more.
includeCompanySummary	boolean	no	true	Emit one company_summary row per company — no extra request.
countryCode	string	no	"US"	2-letter ISO — pinned proxy exit country.
proxyConfiguration	object	no	{"useApifyProxy": true}	Apify Proxy editor.

Example input

{
  "companyNames": ["Google"],
  "employerIds": [9079],
  "maxReviewsPerCompany": 30,
  "includeCompanySummary": true,
  "countryCode": "US"
}

📤 Output

Every row is one dataset item — a review or a company_summary, distinguished by row_type.

Field	Type	Notes
row_type	string	"review" or "company_summary".
company_name / employer_id	string / integer	Requested company and resolved Glassdoor id.
review_id	string | null	Null for company_summary rows.
review_date	string | null	ISO-8601.
job_title / employment_status	string | null	Reviewer's stated role and status.
overall_rating + 6 sub-ratings	float | null	Work-life balance, culture, career, compensation, senior management, diversity.
pros / cons / advice_to_management / summary	string | null	Review text fields.
recommend_to_friend / ceo_approval_response	boolean | null	Per-review signals, when the reviewer set them.
count_helpful / count_not_helpful	integer | null	Helpful-vote counts.
company_overall_rating, company_ceo_approval_pct, company_rating_business_outlook, company_recommend_to_friend_pct	float | null	company_summary aggregate fields; null on review rows.
source_url / scraped_at	string	Fetched page URL, ISO-8601 timestamp.

Example output

{
  "row_type": "review",
  "company_name": "Google",
  "employer_id": 9079,
  "review_id": "105125064",
  "review_date": "2026-08-09T23:03:51.940",
  "job_title": "Hair Transplant Technician",
  "employment_status": "Current Employee, 2 year(s)",
  "overall_rating": 3,
  "pros": "Good learning experience and flexible working environment.",
  "cons": "Long working hours and sometimes limited career growth.",
  "advice_to_management": "Provide better training opportunities.",
  "count_helpful": 0,
  "count_not_helpful": 0,
  "source_url": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm",
  "scraped_at": "2026-08-12T09:00:00+00:00"
}

💰 Pricing

Pay-Per-Event — you pay only when these events fire:

Event	USD	What it is
actor-start	$0.02	One-off warm-up charge per run.
review-row	$0.01	Per review row written to your dataset.
company-summary-row	$0.01	Per company-summary row written (when includeCompanySummary=true).

Example: 1 000 review rows ≈ $10.00. This sits at the top of our usual $1-10/1,000 range on purpose — Glassdoor renders full review text only a few rows per page load without a login, and we refuse to use one, so collecting real volume costs real browser-navigation compute. No subscription, no minimum, no card to start.

🚧 Limitations

Anonymous access only — no login, ever. Glassdoor renders roughly 3 full reviews per page load for unauthenticated visitors, so maxReviewsPerCompany above a few hundred means real added runtime and cost, not a cheap bulk export. Company-name-to-employerId resolution is still being hardened — pass employerIds directly for the most reliable results today. Some review sub-fields (recommend-to-friend, CEO-approval vote) are only present when a reviewer chose to set them and come back null otherwise.

❓ FAQ

Is this legal?

We only fetch content Glassdoor makes publicly available on its company and review pages, anonymously — no login, no reviewer de-anonymization. Respect Glassdoor's terms of service before using output commercially.

Why is a field null?

Either Glassdoor didn't collect that field for a given review (recommend-to-friend and CEO-approval votes are optional for reviewers), or resolution for that company failed and it was skipped — check the run's status message for a breakdown.

Do I need my own proxy?

No — a proxy is wired in by default; proxyConfiguration is optional if you want to bring your own.

Why did I get fewer reviews than maxReviewsPerCompany?

Glassdoor stops rendering full review text past a point for anonymous visitors on some companies; the Actor stops cleanly and reports how many rows it actually collected rather than erroring out.

💬 Your feedback

Spotted a bug, hit a weird edge case, or need a new field? Open an issue on the Actor's Issues tab on Apify Console — we ship fixes weekly and we read every report.

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