Glassdoor Reviews & Interviews Scraper

Get Glassdoor employee reviews, interview reports and company ratings as clean JSON or CSV, by company name, Glassdoor URL or employer id. The actor reads Glassdoor's mobile app data source, so it reaches the full review history (not just the first ~200 reviews the website shows), needs no login and no browser, and returns 100 reviews per request.

• Employee reviews with title, pros, cons, advice to management, job title, location, current or former employee, tenure, overall rating and six sub-ratings, recommend / CEO approval / business outlook, helpful votes and the employer's reply.
• Interview reports with job title, outcome (offer accepted, declined, no offer), difficulty, experience, the process in the candidate's words and the questions they were asked.
• Company profile with website, headquarters, size, revenue, industry, founding year, description and category ratings.
• Monitor mode. Schedule the actor with Only new since last run and each run returns only reviews and interviews it has not delivered before.

Built for HR and employer-branding teams watching their own and competitors' reviews, recruiters and candidates preparing interviews, investors using employee sentiment as alternative data, and researchers building labour-market datasets.

What you get

Every row has a type (review, interview or company) and the employer_id and employer_name, so many companies and all three row types fit in one dataset. The Output tab has a separate table view for each type.

Reviews (type: review)

Field	Description
id, date	Glassdoor review id and post date (UTC)
title, pros, cons, advice_to_management	The review text
job_title, location	Reviewer's role and office
is_current_employee, years_employed	Current or former employee and tenure
rating_overall	1 to 5 stars
rating_work_life_balance, rating_culture_values, rating_diversity_inclusion, rating_career_opportunities, rating_compensation_benefits, rating_senior_leadership	Sub-ratings (null when the reviewer skipped them)
recommends_to_friend, ceo_approval, business_outlook	POSITIVE / NEGATIVE / APPROVE / DISAPPROVE and similar
helpful_count, is_featured	Helpful votes and Glassdoor's featured flag
employer_response, employer_response_date	The company's public reply, if any
employer_reviews_url	The company's Glassdoor reviews page

Interviews (type: interview)

Field	Description
id, date	Interview report id and post date
job_title	Position interviewed for
outcome	ACCEPT_OFFER, DECLINE_OFFER or NO_OFFER
difficulty	VERY_EASY to VERY_DIFFICULT
experience	POSITIVE, NEUTRAL or NEGATIVE
process	How the process went, in the candidate's words
questions	Interview questions the candidate listed
source, helpful_count, employer_response	How they applied, helpful votes, the company's reply

Companies (type: company)

website, headquarters, size, revenue, company_type, year_founded, industry, description, mission, logo_url, rating_overall and the six category ratings, review_count (Glassdoor's total), reviews_available and interviews_available (what this run could page through), and the Glassdoor overview, reviews and interviews URLs.

Use cases

• Employer branding. Track new reviews of your company and three competitors every week in monitor mode; push them to Slack or a sheet and answer the critical ones.
• Complaint mining. Set maxRating: 2 and reviewsSort: newest to collect every recent 1- and 2-star review with its cons and advice, then summarise themes with an LLM.
• Interview preparation. Pull the last 200 interview reports for a role at a target company, filtered to DIFFICULT and ACCEPT_OFFER, and read the process and questions.
• Alternative data. Build monthly time series of ratings, CEO approval and business outlook across a list of public companies.
• Research. Export tens of thousands of reviews with sub-ratings for culture, pay or leadership studies.

Input

Parameter	Type	Default	Description
companies	array	–	Names (Salesforce), Glassdoor URLs (any page with E12345 or EI_IE12345) or employer ids.
includeReviews	boolean	true	Employee reviews.
includeInterviews	boolean	false	Interview reports.
includeCompanyProfile	boolean	true	One company row with profile and ratings.
reviewsSort	enum	newest	newest, relevance, highest_rating, lowest_rating
maxReviewsPerCompany	integer	100	Reviews per company after filters.
onlyCurrentEmployees	boolean	false	Only reviews by current employees.
minRating, maxRating	integer	1, 5	Overall-rating range.
postedAfter	date	–	Only reviews and interviews posted on or after this date, e.g. 2026-09-01.
interviewsSort	enum	newest	newest or relevance
maxInterviewsPerCompany	integer	50	Interview reports per company.
interviewOutcomes	array	all	ACCEPT_OFFER, DECLINE_OFFER, NO_OFFER
interviewDifficulties	array	all	VERY_EASY, EASY, AVERAGE, DIFFICULT, VERY_DIFFICULT
onlyNewSinceLastRun	boolean	false	Monitor mode: skip items delivered by earlier runs with the same input.
maxItems	integer	1000	Total rows for the run.
proxyConfiguration	object	RESIDENTIAL	Fallback only: the actor connects directly and switches to this proxy if Glassdoor refuses the connection.

Example input

{
  "companies": ["Salesforce", "https://www.glassdoor.com/Reviews/Stripe-Reviews-E671932.htm"],
  "includeReviews": true,
  "includeInterviews": true,
  "reviewsSort": "newest",
  "maxReviewsPerCompany": 30,
  "maxInterviewsPerCompany": 10,
  "maxItems": 100
}

Example output

A review:

{
  "type": "review",
  "id": 105831865,
  "employer_reviews_url": "https://www.glassdoor.com/Reviews/Walmart-Reviews-E715.htm",
  "employer_id": 715,
  "employer_name": "Walmart Inc.",
  "date": "2026-10-02T20:20:44Z",
  "title": "Family-friendly scheduling but pay could be better",
  "pros": "Great family forgiving scheduling opportunity",
  "cons": "Not so high on pay scale",
  "advice_to_management": "Yes!",
  "job_title": "Remodel Associate",
  "location": "Rochelle, IL",
  "is_current_employee": false,
  "years_employed": 2,
  "rating_overall": 5.0,
  "rating_work_life_balance": 5.0,
  "rating_culture_values": 5.0,
  "rating_diversity_inclusion": 5.0,
  "rating_career_opportunities": 5.0,
  "rating_compensation_benefits": 4.0,
  "rating_senior_leadership": 3.0,
  "recommends_to_friend": "POSITIVE",
  "ceo_approval": "APPROVE",
  "business_outlook": "POSITIVE",
  "helpful_count": 0,
  "is_featured": false,
  "employer_response": null,
  "employer_response_date": null
}

An interview report:

{
  "type": "interview",
  "id": 105838591,
  "employer_interviews_url": "https://www.glassdoor.com/Interview/Walmart-Interview-Questions-E715.htm",
  "employer_id": 715,
  "employer_name": "Walmart Inc.",
  "date": "2026-10-04T03:21:23Z",
  "job_title": "Cashier",
  "outcome": "ACCEPT_OFFER",
  "difficulty": "EASY",
  "experience": "NEUTRAL",
  "process": "Basic questions consisting of why are you interested in the company. How many hours could you work a week? Etc…",
  "questions": [],
  "source": null,
  "helpful_count": 0,
  "is_featured": false,
  "employer_response": null,
  "employer_response_date": null
}

A company row (shortened):

{
  "type": "company",
  "id": 715,
  "url": "https://www.glassdoor.com/Overview/Working-at-Walmart-EI_IE715.11,18.htm",
  "employer_id": 715,
  "employer_name": "Walmart Inc.",
  "website": "https://careers.walmart.com/",
  "headquarters": "Bentonville, AR",
  "size": "10000+ Employees",
  "revenue": "$10+ billion (USD)",
  "company_type": "Company - Public",
  "year_founded": 1962,
  "industry": "General Merchandise & Superstores",
  "description": "The  work you do here reaches millions of people every day.\n\nWe started as a small discount retailer in Rogers…",
  "mission": "\"To save people money so they can live better.”",
  "logo_url": "https://media.glassdoor.com/sqls/715/walmart-squareLogo-1768329737595.png",
  "rating_overall": 3.4
}

Speed

One request returns up to 100 reviews or interviews. A run of 1,000 reviews for one company takes well under a minute; the date cut-off and monitor mode stop paging as soon as they reach reviews delivered or dated earlier.

Scheduling and integrations

Create a schedule in Apify (daily or weekly), turn on monitor mode, and connect a webhook or an integration (Slack, Google Sheets, Make, Zapier, n8n). Every run then delivers only new reviews and interviews. Results download as JSON, CSV, Excel or XML, or can be read through the Apify API.

Use with AI assistants

Call the actor from an agent through the Apify API or the Apify MCP server, for example: "get the last 100 Glassdoor reviews of Stripe rated 2 stars or lower and list the top complaints". Pros, cons and advice arrive as separate fields, so the model can summarise without parsing pages.

FAQ

Do I need a Glassdoor account? No. Everything returned is public on Glassdoor without logging in.

Is the review history complete? Yes. Pagination goes through the company's full review history, not only the first pages shown on the website. Glassdoor's own default criteria apply, so totals can differ slightly from the number on the company page.

Why is a company not found? Names are matched against Glassdoor's company search. If a name is ambiguous or spelled differently on Glassdoor, pass the company's Glassdoor URL or employer id instead.

Why are some sub-ratings or interview questions empty? Reviewers can skip sub-ratings and candidates can skip questions; the actor returns null or an empty list rather than guessing.

Does it need a proxy? Usually not. If Glassdoor refuses the connection, the actor switches to the configured Apify Proxy (RESIDENTIAL by default) and continues.

Is this legal? The actor collects publicly visible reviews and company data. You are responsible for using the data in line with Glassdoor's terms and the laws that apply to you, including privacy law for any personal data in review text.