Glassdoor Dataset – Reviews, Salaries & HR Data

Reputation intelligence
Salary market visibility
Hiring risk insights

One review is an opinion. One salary is a number. A Glassdoor Dataset from DataOx connects critical information for HR use. It collects reviews, salaries, glassdoor companies data, and roles. Also locations, dates, source links, and quality checks. So HR teams can see what keeps repeating across the market.

Discuss your needs

Know who stands out

Compare employer reputation across companies, roles, and markets.

See salary gaps

Use salary data with role, location, and company context.

Catch hiring risks

Find repeated complaints, weak signals, and talent-market shifts faster.

Glassdoor Data That Stays Current

Glassdoor data changes. Your team does not have to chase it. DataOx keeps your Glassdoor Dataset refreshed with glassdoor reviews data and glassdoor salaries data. Due to this HR, research, and recruiting teams always work with current data, not outdated exports.

Company Signals

Company name
Industry
Company rating
Employer profile URL
Company size, if available

Glassdoor Reviews Data

Review title
Employee rating
Review date
Role or department, if available
Repeated themes and issues

Glassdoor Salaries Data

Job title
Salary range
Pay type
Location
Currency
Salary source context

Interview Insights

Interview questions
Interview difficulty
Candidate experience
Offer outcome, if available
Interview date

Jobs & Roles

Department
Employment type
Company hiring activity
Role category

Dataset Metadata

Source URL
Data refresh date
Record ID
Raw text, if needed
Data checks
Delivery format

use cases

Employer Reputation Tracking

When a candidate reads Glassdoor, they see not your career page, but what people write about the company. Glassdoor Dataset helps collect Glassdoor reviews data, ratings, roles, locations, and dates into one hr dataset. Then the HR team can see how employer reputation changes over time. This is important because online employer reputation affects the labor market.

Salary Benchmarking

A pure salary amount isn’t enough. Without a role, city, and company explains almost nothing. DataOx can collect glassdoor salaries data together with other important things. Primarily they are job titles, locations, company names, and source context. As a result, the HR team does not compare “everyone with everyone,” but sees real salary ranges for the needed roles and markets. Such a Glassdoor Dataset is useful for compensation research, hiring plans, and salary transparency projects.

Competitor Hiring Research

Sometimes competitors talk about themselves not in press releases, but through jobs, salaries, reviews, and interview experience. Glassdoor Dataset can combine important job data. It checks Glassdoor companies data, reviews, salaries, roles, and company profiles. Thanks to this the team can see not only whom competitors are hiring, but also which roles are active, which salary expectations appear, and where the talent market is moving faster.

Interview Experience Monitoring

A bad hiring process can scare candidates away even before the offer. DataOx can collect interview feedback, job titles. Also dates, locations, and company context. With this data it builds an HR dataset. The dataset helps the recruiting team see where candidate experience looks difficult, delayed, or inconsistent. Glassdoor itself highlights interview questions and reviews as a separate data block for candidates.

Fresh HR Data Feed

A one-time export gets old quickly. New reviews appear, salary data changes, company profiles are updated. DataOx can maintain Glassdoor Dataset as a regular data feed. The feed will include glassdoor reviews data, glassdoor companies data, glassdoor salaries data. Also roles, dates, and source links. HR, research, and recruiting teams can work with current data without manual monitoring.

Businesses we serve

Small agencies Medium-sized companies Enterprises

Delivery schedule

Real-time Daily Weekly Monthly Custom On demand

Glassdoor Shows a More Realistic Picture

It is no secret that candidates often study company reviews, reputation, opportunities, and limitations before sending a resume or accepting an offer. Glassdoor is one of the places where they can find this kind of information. People leave reviews about interviews, salary expectations, company culture, roles, and work experience. DataOx collects these scattered signals into a Glassdoor Dataset, so HR teams can work with current HR data without manually checking pages.

Discuss my needs

Data Delivery Formats

Glassdoor Data for Your Workflow

DataOx delivers your Glassdoor dataset in a format and structure that fit your team’s existing tools and workflows.

CSV

Excel (XLSX) / Google Sheets

Excel

JSON

API Integration

API

Database Direct

Database

Custom

Python web scraping – Web scraping with Python for pricing and inventor

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Let’s talk

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Let’s talk

Why choose DataOx

Data you can rely on

Custom Solutions

DataOx builds the process and dataset around your task instead of making you adapt to a ready-made product.

Change Management

When sources, fields, or your requirements change, DataOx updates the process without interrupting operations.

Cost Efficiency

You pay for the data volume and work you need, not for features you do not use.

Security

Project data and requirements are protected by NDAs, restricted access, and agreed working rules.

Unlock market insights with our Glassdoor dataset

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what our clients say about us

I’ve worked with Vladislav and DataOx twice now and have been impressed both times. They don’t just do everything they committed to do — on time and on budget — but they go above and beyond. On this second project, they showed initiative and added something they suspected I would want. They were right. I cannot recommend him and them any more enthusiastically. I’m a big fan.

jeff leitner

March 13, 2026

We worked with the DataOx team on a complex internal project that involved building a custom software solution with Slack Bot integration, sophisticated server-side logic, and automated API workflows. The system needed to fetch, process, and store data in an intermediate database, and—only if specific conditions were met—push that data through additional APIs to our target software. It was no small task.
So far, everything is running flawlessly, and we couldn’t be more satisfied. Their communication was consistently sharp, fast, and proactive—so fast, in fact, we sometimes had to catch up with them! Whether it was refining a feature, squashing a bug, or adjusting requirements on the fly, the team was always on it.

What really stood out was the professionalism: we had a dedicated, experienced project manager who kept everything aligned and moving smoothly. DataOx truly listens, understands your needs, and delivers high-quality work with precision.

If we could give 10 stars, we would. Highly recommend this outstanding team—and we’re definitely looking forward to working with them again!

ilia sokolovskiy

March 13, 2026

We’re a UK based operation, and have worked on a couple of projects with DataOX over the last two years. I’ve been impressed with every project, as they’ve been delivered to the spec I’ve requested, alongside all the changes I asked for along the way.

I was initially concerned about whether there would be a language barrier, but the developers, business leads and representatives of the company communicate in excellent English.

We’ll continue to work with DataOX on projects in the future, and I’d highly recommend them to anybody reading this!

andrew napier

March 13, 2026

Prompt. Got Job Done exactly how we wanted. Communicated clearly with the team about expectations and deadlines.

mike goetsch

March 13, 2026

High Quality, fast data scraping from the team at DataOx. Very communicative and always proactive in understanding requirements before starting the work. Used multiple times, and will be using in the future!

andrew haynes

March 13, 2026

Both the quality and the speed of delivery were awesome, and the communication along the way with our project manager and sales leader was perfect. They were both good at eliminating ambiguity in our requirements which resulted in a delivery we are very happy with.

josh albrechtsen

March 13, 2026

I worked with DataOx on a data scraping. everything was done on time and with high quality. Vladislav and his team showed a high level of professionalism and attention to detail. I recommend DataOx to anyone looking for reliable specialists in web scraping!

olim rakhmatov

March 13, 2026

These guys are simply the greatest. They are timely and accurate in their work, they communicate quickly, and I feel they genuinely understand and care for our needs. Whatever we have asked for, they have delivered. They made us a web scraper and automated many processes for our webshop. We started working together with Andrew and Bogdan in November 2022, and they are a delight to work with. Bogdan as our project leader, has been great! We will continue to work with DataOx for our projects.

petter trønsdal

March 13, 2026

FAQ: common questions about DataOx Glassdoor datasets

Why should a Glassdoor Dataset work as a live data flow, not as a one-time file?

A one-time file gets old quickly: new reviews appear, company profiles are updated, salaries, roles, and locations change. DataOx can maintain a Glassdoor Dataset as a regular hr dataset, so the team does not return to manual Glassdoor checking every time current data is needed. This gives a simple result: HR, research, and recruiting teams work with fresher records, not with an export that no longer describes the market.

How does a Glassdoor Dataset help avoid mistakes in salary comparison?

Salary data on its own can easily be confusing. Even the same position can be paid differently depending on the city, company, currency, or salary type. DataOx keeps glassdoor salaries data together with the job title, location, company, date, and source URL, so the team understands which records can be compared with each other. This gives a convenient base for compensation research, salary benchmarking, and hiring planning.

What does the team gain when reviews, salaries, and company data are collected into one structure?

One review, one salary, or one company profile does not give the full picture. DataOx turns scattered Glassdoor data into one convenient Glassdoor Dataset for work. The team does not need to open dozens of tabs, copy data manually, and then bring everything together in spreadsheets — the needed information is already collected in one place.

Why is it important to keep source links, dates, and metadata?

Data is easier to work with when it is clear where it came from and when it was updated. DataOx can keep a source URL, collection date, update date, role, location, and company ID next to each record. This way, the team can quickly check the record and understand whether it is still relevant. This is useful for HR reports, internal databases, audit-friendly workflows, and long-term research.

What happens if Glassdoor pages change?

Glassdoor pages can change: today the data is in one format, and tomorrow the source may look different (for example, the needed field may have a different name, a different format, or may temporarily not be shown). To keep the dataset from losing quality after the first delivery, DataOx can set up checks for key fields and the source URL. If the source structure changes or part of the data becomes unavailable, the checks help notice the problem faster and update the collection process. This way, the Glassdoor Dataset remains more stable and more useful for work over time. Learn more about checks: Data Validation Services.

Why does “more Glassdoor data” not always mean “better”?

A larger dataset does not always bring value. More often, it brings confusion. Duplicates, incomplete records, unnecessary companies, and different formats of positions and salaries can get mixed in one file. To prevent this, DataOx first agrees on the project scope. The team finds out which companies, countries, positions, industries, and update frequency the client needs. This way, the client receives a Glassdoor dataset that matches a specific workflow, not just a file with a huge amount of data.

Can we get raw data and prepared records at the same time?

If you need raw Glassdoor data, DataOx can deliver it. Our team stays flexible and adapts the dataset to your goals, whether you need raw records, prepared data, or both. The main goal is simple: to help you get the data you need in the form that works best for your workflow.

How does a Glassdoor Dataset get into the team’s work after delivery?

DataOx delivers the Glassdoor Dataset in the required format: CSV, JSON, Parquet, Google Sheets, a database, API, S3, or your internal system. The team receives the data where it already works, without extra files and manual transfer. Delivery options: Data Delivery Services.