Glassdoor shows a signed-out visitor employer ratings, the newest reviews, pay ranges and the whole job search. Our Glassdoor scraper collects that public layer. We never log in.
Plans from €169/month · Free project assessment · Reply within 1 business day
The request is usually a list: employers by name or Glassdoor address, a set of job titles and cities, or an industry in one country. We resolve each employer to its numeric employer ID, build crawlers for the profile tabs you need - About, Reviews, Pay and benefits, Jobs, Interviews - and run them on your schedule.
Two things are fixed. We work only from what Glassdoor shows without an account: no sign-in, no member-only archives. And the site screens automated visitors closely, so pacing, proxy rotation, rendering and CAPTCHA handling are included, together with repairs when page layouts change. A free project assessment tells you which of your fields are public before you commit, and a sample can be ordered for a handful of employers.
Every employer on Glassdoor has a numeric employer ID that appears in the address of each of its tabs. It is the key that joins the tables below.
Review authors are anonymous on Glassdoor and stay so in the data: there are no names to collect, and we do not try to link reviews to people.
Beyond the main tabs, an employer profile branches into pages that are easy to miss and useful to have.
What Glassdoor keeps for signed-in members - the deeper review archive, individual interview write-ups, the full salary table - stays outside the dataset.
Glassdoor is a workplace review site and a job board in one. Current and former employees post anonymous company reviews, salary reports, benefit reviews and interview accounts; employers claim a profile and post jobs. The brand belongs to Indeed, Inc., and the two sites share a login.
The main navigation leads with Community, Jobs, Companies and Salaries, and an employer profile sits under Companies with its About, Reviews, Pay and benefits, Jobs and Interviews tabs. Glassdoor rounds each score to one decimal and attaches a label to it, from Excellent through Positive and Average to Slightly Negative and Negative. Its help pages say that recent reviews weigh more in the overall rating, and that CEO approval and workplace factor ratings are optional answers, so they rest on fewer responses than the review count suggests.
Glassdoor runs country sites - glassdoor.co.uk, glassdoor.ca, glassdoor.co.in, glassdoor.com.au, glassdoor.de, glassdoor.fr and more, with two language editions each for Canada, Switzerland and Belgium. The domain matters. Reviews are displayed in the language of the site, and an employer with a localised profile shows a rating built from reviews in that country, so a German and a US rating for one company can differ. We record the site every row came from.
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€199 / one-time
setup fee - included
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →Candidates check an employer on Glassdoor before they answer a recruiter, and its numbers are specific enough to manage against.
Teams that scrape Glassdoor data themselves usually stall on upkeep - employer IDs to resolve, country sites to keep apart, tabs whose layout changes; a managed feed removes that work.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed data collection service: we write the crawlers, run them, fix them and send you the result. On job and employer sites we hold two lines - we never log in or go behind a paywall, and we do not build profiles of individuals; personal data is handled under GDPR. You receive employer-level and listing-level data with a documented schema, as CSV, Excel, JSON or JSONLines, sent to SFTP, Amazon S3, Google Cloud Storage or your database.
Yes. The ScrapeIt Glassdoor API returns employer ID, overall rating, recommend to a friend share, CEO approval, the reviews shown publicly with Pros and Cons, and salary ranges by job title as JSON through an endpoint that we host and refresh on your schedule. The same records are also delivered as CSV or XLSX files, a JSON feed or a direct load into your database.
Yes. Employer snapshots, rating percentages, the reviews shown to signed-out visitors, pay ranges by job title and job listings are open to anyone on Glassdoor without an account. We collect only publicly available data - everything a visitor can see on Glassdoor - and we collect it legally.
We collect the reviews Glassdoor displays to a signed-out visitor on an employer's review pages, including the separate pages per job title and per location, with rating, date, role, employment status, Pros and Cons. The deeper archive is for signed-in members, and we never log in. The summary figures - overall rating, recommend share, CEO approval, business outlook - cover all reviews and are always included.
Each row carries job title, employer, employer rating, location, the salary range and whether it is employer provided or a Glassdoor estimate, the Easy Apply flag, skills, the full description and the listing ID. Searches are set by title, city and country site, and the result count is stored with each of them.
Glassdoor says an overall rating takes about seven business days to reflect new reviews, so daily runs add little for ratings. Weekly or monthly runs suit rating, review and salary tracking. Job listings move faster, and daily runs are usual when they serve as a hiring signal.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Glassdoor data from €169/month. Free project assessment, reply within 1 business day.
Scrapeit Sp. z o.o.
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