Use our Glassdoor dataset to find market trends and business information on companies as well as how current and past employees perceive and rate them. You may purchase the entire dataset or a customized subset depending on your needs. Popular use cases: competitive business intelligence, location-based marketing, geotargeting, B2B data enrichment, and more. The Glassdoor companies information dataset, one of the largest jobs and recruiting sites, offers a complete company overview with reviews and FAQs that provide insights about jobs and companies. The dataset includes all major data points: Location, Founding date, Revenue range, Size,Management, Company rating, CE outlook, Reviews, and FAQ as added by employees, Rating CEO approvalm and more.

Use our Glassdoor Companies Reviews dataset to gain insights into employee reviews, ratings, and feedback on company culture. Popular use cases include employer branding, talent attraction, and analyzing workplace satisfaction trends. The dataset includes all major data points: overview ID, review ID & URL, rating date, number of responses, and more.

lallantop/glassdoor dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset provides comprehensive real-time data from Glassdoor. It includes detailed company information, employee reviews, salary data, interview data, and more for employers worldwide. The data covers company attributes like ratings, reviews, salaries, benefits, and workplace culture details. Users can leverage this dataset for employer research, job market analysis, and workplace intelligence. The API enables real-time access to Glassdoor's vast employer database and review data, helping businesses make data-driven decisions about recruitment, employer branding, and workplace culture. Whether you're conducting market analysis, tracking employer reputation, or building HR tools, this dataset provides current and reliable Glassdoor data. The dataset is delivered in a JSON format via REST API.

The OpenWeb Ninja Glassdoor Data API provides real-time access to extensive company data and employer reviews data from Glassdoor.

Key company data points included in the dataset: Name, Rating, Website, Salary and Job counts, Company size, Revenue, Stock, Competitors, Awards won, and 30+ more data points.

Key employer review data points included in the dataset: Review summary, Pros / Cons, Employee status, Location, Work-Life balance, CEO rating, and 20+ more data points.

OpenWeb Ninja's Glassdoor Data API Stats & Capabilities: - 2M+ Companies/Employers - 80M+ Employee Reviews - 30+ company data points - 20+ review data points - Company search capability

OpenWeb Ninja's Glassdoor Data API common use cases: - Investors and Market Analysts - Market and Industry Trends - Competitive Analysis - Company Insights

Glassdoor Companies Overview dataset to gain insights into company reviews, employee satisfaction, salaries, and corporate culture. Popular use cases include employer branding, talent acquisition, and workforce analysis to improve recruitment strategies and organizational development.

Use our Glassdoor Companies Overview Information dataset to gain valuable insights into company culture, employee reviews, salary data, and overall business performance. This dataset provides key information on company ratings, leadership reviews, work-life balance, and compensation trends, tailored for HR professionals, recruiters, job seekers, and market analysts.

By leveraging the Glassdoor Companies dataset, you can evaluate company reputations, benchmark salaries, and understand employee satisfaction to support strategic hiring, organizational development, and competitive analysis. Enhance your recruitment strategies and make informed decisions by understanding the workplace dynamics and employer branding across different industries.

Dataset Features

• id: Unique identifier for each company.
• company: Name of the company.
• ratings_overall: Overall company rating based on employee reviews.
• details_size: The size of the company (e.g., number of employees).
• details_founded: Year the company was founded.
• details_type: Company structure (e.g., Private, Nonprofit).
• country_code: Country where the company is based.
• company_type: Type of company (e.g., nonprofit, private).
• url_jobs: Link to job listings.
• url_overview: Link to company overview on Glassdoor.
• url_reviews: Link to company reviews on Glassdoor.
• benefits_url: Link to company benefits page.
• details_headquarters: Location of company headquarters.
• region: Geographic region (e.g., NA, EU).
• details_industry: Industry category (e.g., Legal Services).
• details_revenue: Revenue details (if available).
• details_website: Official company website.
• interviews_url: Link to company interview experiences.
• photos_url: Link to company photos.
• ratings_career_opportunities: Rating for career advancement opportunities.
• ratings_ceo_approval: CEO approval rating.
• ratings_ceo_approval_count: Number of reviews used for CEO approval rating.
• ratings_compensation_benefits: Rating for compensation and benefits.
• ratings_culture_values: Rating for company culture and values.
• diversity_inclusion_score: Diversity and inclusion score.
• Diversity_inclusion_count: Diversity and inclusion count.
• ratings_senior_management: Rating for senior management.
• ratings_work_life_balance: Rating for work-life balance.
• ratings_business_outlook: Rating for business outlook.
• ratings_recommend_to_friend: Rating on whether employees would recommend the company to a friend.
• ratings_rated_ceo: Rating of the CEO by employees.
• competitors: Competitors in the same industry.
• salaries_url: Link to company salaries page.
• salaries_count: Number of salary reviews.
• career_opportunities_distribution: Distribution of career opportunities.
• url_faq: Link to frequently asked questions page.
• interview_difficulty: Difficulty level of interviews at the company.
• interviews_count: Number of interview reviews.
• benefits_count: Number of benefit reviews.
• jobs_count: Number of job listings.
• photos: A collection of photos related to the company.
• photos_count: Number of photos available.
• faq: Frequently asked questions related to the company.
• reviews_count: Number of reviews.
• interviews_experience: Experience of employees with the company’s interview process.
• Url: The webpage address for the company.
• Industry: The sector in which the company operates.
• Additional_information: Any other relevant details about the company.
• Stock_symbol: The ticker symbol for the company's stock.

Distribution

• Data Format: CSV
• Data Volume: 49 columns and 2.46 M rows

Usage

• Company Analysis: To understand employee sentiment and business performance.
• Market Research: To analyze trends in job satisfaction, compensation, and employee experiences.
• HR Analytics: To assess company culture and opportunities for improving employee retention and satisfaction.

Coverage

• Geographic Coverage: Global.

License

CUSTOM

Please review the respective licenses below:

1. Data Provider's License
   • Bright Data Master Service Agreement

Who Can Use It

• Data Scientists: For sentiment analysis, recommendation systems, and NLP applications.
• Researchers: For labor market, HR analytics, or business culture studies.
• Businesses: To monitor brand percep

Glassdoor Jobs Data Analysis

Jobs data from Glassdoor.com for a self learning project

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About Glassdoor

Glassdoor is a website where current and former employees anonymously review companies. Glassdoor also allows users to anonymously submit and view salaries as well as search and apply for jobs on its platform.

In 2018, the company was acquired by the Japanese firm, Recruit Holdings, for US$1.2 billion. The company is headquartered in Mill Valley, California, with additional offices in Chicago, Dublin, London, and São Paulo. wikipedia

Content

1. There are 10 columns in the data they are as follows:
2. Job Title : The title of the job which you are applying to.
3. Salary Estimate : Salary estimated of the job posting.
4. Job Description : The job description included skills, requirements, etc.
5. Rating : Rating of the companies job posting is listed.
6. Company Name : Company name.
7. Location : The location the companies job posting is listed.
8. Size : The size of the company's employment.
9. Founded : The company founded year
10. Type of ownership : Type of ownership in which the company.

11. Industry : The industry in which the company works.

12. All the data collected is about 150 job listings for Data Scientist and it's related roles. The job listings are scraped from Glassdoor.com locate in Indonesia on 10 October 2020.

GitHub's Link

Here is my GitHub link: https://github.com/Deff-ux/Scrapping-Glassdoor-Job-Posting-

Introduction

Glassdoor Statistics: Glassdoor has indubitably become the chief place for job seekers, employees, and employers to connect and share information among themselves for possible career decisions. The platform keeps growing in popularity in 2024, and it looks more likely to affect job hunting, salary comparisons, and understanding of workplace culture.

In 2025, Glassdoor remains a leading platform for job seekers, employees, and employers to access transparent employer reviews, salary information, and workplace insights. Monthly unique visitors number approximately 55 million, generating over 180 million reviews and salary submissions, while profiling 2.5 million employers globally .

Founded in 2007 and based in Mill Valley, California, it operates under parent company Recruit Holdings following a USD 1.2 billion acquisition in 2018  With more than 40 million total reviews, salaries, and company insights available, Glassdoor continues to be a critical tool for evaluating organizations, comparing compensation in USD, and understanding workplace culture through first-hand employee feedback .

This is an extensive look at Glassdoor statistics in 2025, analyzing user behavior, salary trends, company reviews, and some other notable insights.

Glassdoor Data with U.S. salary insights, executive compensation, and company-level benchmarks. This structured Glassdoor Data powers HR analytics, payroll benchmarking, and financial modeling across startups, growth-stage firms, and enterprise organizations.

Fast and reliable real-time API access to Glassdoor data with 2M+ companies and 80M+ employer reviews from around the world.

Job Title -: Job profile eg. Data Scientist, Data Analyst, Data Engineer etc. Salary Estimate -: Estimated Salary for job profile Job description -: Description about the job profile Rating -: Rating of Company Company Name -: Name of the Indian Company Location -: Location where it is situated. Size -: Employees Size in the Company Founded -: Company Established in which year Type of Ownership -: Company is Private, Public, etc. Industry -: Company belongs to which Industry Sector -: Company belongs to which sector Revenue -: Revenue of the Company till now.

Traffic analytics, rankings, and competitive metrics for glassdoor.com as of May 2025

About Dataset Context Want to know the base pay for different job roles, then this data set will be useful.

About the data set: The data set has been taken from glassdoor and focuses on income for various job titles based on gender. As there have been many studies showcasing that women are paid less than men for the same job titles, this data set will be helpful in identifying the depth of the gender-based pay gap. The features of the data set are: Job Title Gender Age PerfEval Education Dept Seniority Base Pay, and Bonus

Acknowledgements The data set has been taken from the website of Glassdoor. The license was not mentioned on the source.

Inspiration To find out the pay gap between the gender for the same job title.

The dataset consists of data from relevant companies and industries' job postings. The dataset includes unique job and company-level attributes and identifiers, such as job title, full job description, job URL, company name, location, job type (full-time/ part-time), salary, and more. The data can be provided hourly, daily, weekly, bi-weekly, monthly, or one-time, depending on the client's requirements.

A. Usecase/Applications possible with the data:

• Build a fuller picture of companies' strategic moves.
• Provide almost real-time data about job postings.
• Enable a data-driven decision-making strategy for hiring.
• Building a talent pool.

How it works?

• Analyze sample data
• Customize parameters to suit your needs
• Add to your projects
• Contact support for further customization

Based on https://www.kaggle.com/datasets/davidgauthier/glassdoor-job-reviews/data Filtered by 30 top firms Addes columns with lemmatized and tokenized texts

The global market for company review and rating solutions is experiencing robust growth, driven by a confluence of factors. The increasing reliance on online platforms for job searching and employer branding necessitates transparent and readily available company feedback. Employees are increasingly vocal about their workplace experiences, demanding better working conditions and more ethical practices. This trend, coupled with the rise of remote work and the gig economy, fuels the demand for comprehensive company review platforms that provide insights into company culture, work-life balance, compensation, and management styles. The market's expansion is further fueled by technological advancements, with platforms continuously improving their analytical capabilities and incorporating features like AI-powered sentiment analysis and predictive analytics to provide more comprehensive and insightful data. This allows businesses to proactively identify and address potential issues, enhancing their employer branding and attracting top talent. Competitive landscape is varied, with established players like Glassdoor and Indeed competing with niche platforms catering to specific demographics or industries. This competition spurs innovation and ensures continuous improvement in the quality and comprehensiveness of the reviews and ratings available to users. The market segmentation reveals significant opportunities across different applications (employer and employee) and types of reviews (company reviews and ratings). Employer use focuses on leveraging feedback to improve internal processes and enhance recruitment strategies, while employee use concentrates on researching potential employers and making informed career decisions. The geographical distribution of the market is extensive, with significant penetration in North America and Europe, followed by a steady growth in the Asia-Pacific region. This growth is likely to be propelled by increasing internet penetration and smartphone adoption in these regions. While regulations concerning data privacy and online reviews represent a potential constraint, the overall market outlook remains positive, fueled by persistent demand for transparent and reliable employer information, fostering a more informed and equitable job market. We project continued, albeit potentially moderated, growth over the next decade, reflecting both market maturation and the cyclical nature of employment trends.

303 Global import shipment records of Glassdoor with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Dataset

This dataset was created by Neha Tiwari

Contents

This statistic presents the web traffic to Glassdoor.com from the United States as of April 2018. During the measured 30 days, the online employer review platform had 51.8 million views from mobile connections.