Glassdoor has become the go-to platform for millions of job seekers and employers to research companies, read employee reviews, compare salaries, and more. With over 110 million reviews and insights for more than 2 million companies worldwide, Glassdoor is a goldmine of valuable data on the labor market and employer branding.
However, manually searching for and collecting large amounts of Glassdoor data can be extremely time-consuming and tedious. That‘s where web scraping comes in – it allows you to automatically extract data from Glassdoor and compile it in a structured format for analysis.
In this comprehensive guide, we‘ll walk you through everything you need to know about scraping data from Glassdoor, including the benefits, legality, tools, step-by-step process, best practices, and more. Whether you‘re a job seeker, recruiter, HR professional, or data analyst, you‘ll learn how to leverage the power of Glassdoor data to make informed decisions and gain a competitive edge. Let‘s dive in!
What Data Can You Scrape from Glassdoor?
Glassdoor provides a wealth of information beyond just company reviews and ratings. Here are some of the key data points you can extract from Glassdoor:
- Company information: name, website, headquarters, size, founded date, industry, revenue, competitors
- Job listings: job title, location, job description, qualifications, employment type, posted date
- Salary data: job title, base pay, total pay, bonuses, location, years of experience
- Reviews and ratings: overall rating, recommend to a friend, CEO approval, pros, cons, advice to management
- Interview reviews: interview type, process, questions, difficulty rating, experience, offer status
- Benefits reviews: health insurance, 401K, vacation policy, parental leave, perks
- Photos: office photos, employee photos
- Diversity, equity, inclusion ratings
- COVID-19 updates and reviews
Having access to this comprehensive data allows you to gain valuable insights into employee satisfaction, company culture, hiring trends, salary benchmarks, and more.
Why Scrape Glassdoor Data?
Now that you know what data is available on Glassdoor, let‘s look at some of the key benefits and use cases of scraping it:
For Job Seekers
– Research companies you‘re interested in working for
– Compare salaries for your role and location to ensure fair compensation
– Get insight into the interview process and questions to prepare effectively
– Evaluate the pros and cons of working at a company based on employee reviews
– Identify top-rated employers in your industry
For Recruiters and HR
– Understand the perception and reputation of your company on Glassdoor
– Benchmark salaries for roles you‘re hiring for to stay competitive
– Identify areas for improvement in your interview process based on candidate reviews
– Monitor employee satisfaction and engagement through reviews and ratings over time
– Analyze diversity and inclusion metrics and perception
For Employers and Managers
– Track your company‘s rating and reviews on Glassdoor
– Identify strengths and weaknesses in your employee experience and company culture
– Compare your employer brand to competitors
– Monitor mentions of your company across reviews
– Understand reasons for employee turnover and attrition
For Market Research and Analysis
– Analyze hiring demand and trends across industries, companies, and locations
– Model and predict salaries based on various factors like job title, company, location, etc.
– Conduct sentiment analysis on reviews to gauge employee and candidate perception
– Map competitor and industry landscape for salaries, job openings, and more
As you can see, Glassdoor data has versatile applications for a variety of stakeholders. Scraping allows you to efficiently collect and harness this data at scale to derive actionable insights.
Is It Legal to Scrape Glassdoor?
Before you start scraping Glassdoor, it‘s important to understand the legality and terms of service around it. In general, scraping publicly available web data is legal in many jurisdictions.
However, Glassdoor‘s terms prohibit unauthorized scraping, crawling, or using automation to access the site in ways that exceed normal usage. Their terms also disallow use of their data to compete with or replicate their services.
The safest way to get Glassdoor data is through their official API partnerships and feeds. But for most individuals and companies, scraping remains a viable option if done responsibly and in moderation. Here are some best practices to stay compliant:
- Respect robots.txt instructions
- Limit your request rate to avoid overloading servers
- Don‘t modify or conceal your scraper‘s user agent and headers
- Only scrape data that‘s publicly available without needing to log in
- Use scraped data only for personal, educational, or internal business purposes
- Don‘t share, sell, or publish scraped data or derivative works publicly
- Consult legal counsel for your specific use case and jurisdiction
With appropriate precautions in place, scraping Glassdoor can be an effective and efficient way to gather valuable business intelligence and labor market insights.
How to Scrape Glassdoor Data Without Coding
While Glassdoor offers APIs to some approved partners, most people don‘t have access to those official channels. Luckily, you don‘t need to be a programmer to scrape data from Glassdoor. There are many user-friendly, no-code web scraping tools that allow you to easily extract Glassdoor data in a few clicks.
One of the most popular and powerful tools for Glassdoor scraping is Octoparse. It‘s an intuitive point-and-click desktop app for Windows and Mac that can scrape websites, convert data into structured formats, and automate extraction on the cloud.
Here‘s a step-by-step guide on using Octoparse to scrape data from any Glassdoor page in minutes, no coding required:
Step 1: Install Octoparse
First, download and install the Octoparse app on your computer. Launch the app and sign in with your credentials.
Step 2: Enter the Glassdoor URL
In the Octoparse app, paste the URL of the Glassdoor page you want to scrape, such as a company profile, job listings, salary page, or reviews section. Click "Start" to load the page in the built-in browser.
Step 3: Select Data Fields
Once the page loads, click "Auto-detect web page data" in the Octoparse wizard panel. It will scan the page and highlight different data fields it finds, like text, images, and links.
You can then select the specific data points you want to scrape. For example, if scraping reviews, you may want the review title, text, date, helpful vote count, and pros/cons. Rename the data fields and configure the settings as needed.
Step 4: Handle Pagination
Many Glassdoor pages have multiple pages of results that you‘ll need to navigate through to scrape completely. In the Octoparse workflow editor, you can add a "Loop click next page" action and configure it to scroll through all the pages and extract data from each one.
Step 5: Run the Scraper
After setting up your workflow and testing it on a few pages, you‘re ready to run the scraper on the full dataset. Octoparse provides two options:
- Run on your own computer, which is suitable for small scraping jobs
- Run on cloud servers, which can handle large jobs 24/7 in the background
Running on the cloud is recommended for scraping a high volume of Glassdoor pages to avoid delays and reliance on your computer.
Step 6: Export the Data
When the scraping run is finished, you can export the data from Octoparse in CSV, Excel, JSON, or other formats. You can also set up automatic exports to Google Sheets or databases for seamless integration with your existing data pipelines and analysis tools.
And that‘s it! With Octoparse, you can scrape thousands of Glassdoor pages and data points in hours instead of weeks of painstaking manual work.
Scraping Glassdoor Data Like a Pro
For the best results when scraping Glassdoor, here are some pro tips:
- Use strong, rotating proxies and IP addresses to avoid rate limiting
- Randomize scraping patterns and intervals to mimic human behavior
- Implement error and exception handling for failed requests and edge cases
- Monitor and maintain your scrapers to adapt to any site changes over time
- Combine different scraping tools and methods like Selenium, Scrapy, APIs, and more
- Structure, clean, and consolidate your scraped data properly before analysis
- Complement Glassdoor data with other sources like LinkedIn, Indeed, Crunchbase, etc.
Following these best practices will help you maximize the quality, reliability, and usefulness of your scraped Glassdoor data for your specific needs.
Conclusion
Glassdoor is an invaluable resource for anyone interested in company insights, employee sentiment, salary data, and hiring trends. By leveraging web scraping, you can unlock the full potential of Glassdoor‘s huge dataset for competitive intelligence, labor market research, employer branding, and job search.
As we‘ve seen, you don‘t need to be a coder to scrape Glassdoor. No-code tools like Octoparse make it easy for professionals in HR, recruiting, consulting, finance, and more to access web data.
However, always be mindful of legal and ethical scraping practices. Avoid abusive scraping that violates terms of service or harms Glassdoor. Focus on extracting only what you need and using it responsibly to inform your decisions.
Ready to start scraping Glassdoor data the smart way? Try out Octoparse and other scrapers featured here to experience the power of web data for yourself. The competitive advantages you‘ll uncover will be well worth the effort!