The best (and worst) tools for salary benchmarking

Salary benchmarking is foundational to any compensation strategy. 

It gives an understanding of what fair and market competitive pay looks like for different job roles, seniorities, and employee locations, and is the foundation for other key building blocks such as creating a salary band structure or analysing internal pay equity.

Access to accurate and up-to-date salary benchmarking data is, therefore, crucial for any company’s compensation approach. 

In the past, annual salary surveys from consultants like Radford were the default data provider for salary benchmarking – but their manual nature makes them very painful to use, not to mention the inaccuracies due to outdated and error-prone datasets. 

Some teams even rely on user-reported salary data from sources like Glassdoor or Michael Page – but this user-reported data is highly unreliable, making it unusable for any company that relies on competitive pay to attract and retain talent.

This is where salary benchmarking tools come in.

Salary benchmarking tools (like Ravio) are specifically designed to solve these problems, with reliable, relevant, real-time compensation data, hosted in a user-friendly platform. 

In this blog we’ll explore the pros and cons for each of these popular salary benchmarking data options –  as well as taking a closer look at the best salary benchmarking software options on the market today.

How to access salary benchmarking data

There are four main data sources that People and Reward Leaders rely on for salary benchmarking, and some are (much) more reliable than others:

1. Salary surveys
2. Employee-reported data
3. Job adverts
4. Real-time salary benchmarking tools.

Here’s a brief overview of how these sources compare – keep reading for a more detailed breakdown of each factor.

Option 1: Real-time salary benchmarking tools

Salary benchmarking software should be the only option on the table when evaluating which source to use for salary data today.

As we’ve seen, it’s crucial that salary benchmarking data is up-to-date to ensure that employee pay stays fair and competitive in a fast-changing talent market.
Tools like Ravio gather employee salary data directly from the source by integrating with company HRIS systems, automatically updating to reflect any changes made to ensure that the salary benchmarks provided are always reflective of market trends, in real-time.

The benefits of real-time salary benchmarking tools

The up-to-date nature of the salary benchmarks are just one of the benefits of using a salary benchmarking tool like Ravio. 

Here’s the full list:

• Up-to-date data. HRIS integrations mean that any new hires or salary adjustments  flow automatically into our benchmarks, keeping them up-to-date.
• Accurate data. The HRIS integrations also eliminate any manual data submissions from the benchmarking process, removing the risk of human error. 
• Relevant data pool. Salary benchmarking tools include functionality for filtering the salary data to ensure it is as relevant as possible for your company – with typical filters including location, industry type, headcount, and company stage. Different providers have different filters and relevancy is important for accurate benchmarking, so this is definitely one to check before committing to a tool. 
• Comparison of external benchmarks with internal employee data. Salary benchmarking software typically combines external market benchmarking data, with salary data for your own employees. This makes it easy to compare existing salary bands or individual employees to real-time market data, and make adjustments in platform too.
• Automatic job matching. Most salary benchmarking software providers automatically line up your employees with the relevant job role and level used in the platform, ensuring consistent and like-for-like comparisons every time a benchmark is used. Different providers do this in different ways, so it’s always worth checking how this works when you’re evaluating different salary benchmarking tools. 
• Quick access to benchmarks. With salary benchmarking software there’s no need to wait for months for salary data to be delivered, because onboarding is quick (typically days) and once onboarded the data is accessible anytime through the platform – and it’s typically possible to add additional users so that they have access too, such as hiring managers.
• User-friendly platform. For a long time the default way to manage compensation was through highly complex spreadsheets. Salary benchmarking software offers an intuitive interface for People Teams to view, analyse, and share benchmarking data.
• Additional compensation management tools. Salary benchmarking tools often include additional compensation features to make it easier to use the salary data effectively – such as building salary bands, analysing pay equity, or running a compensation review.

Option 2: Salary survey data

Several HR consultancies run large-scale salary surveys. Employee salaries are gathered from companies via salary submissions, and this data is then aggregated and sold on for benchmarking purposes by the consultancy.

Salary survey data providers include:

• Radford
• Mercer
• Willis Towers Watson
• Korn Ferry
• Culpepper
• Salary.com
• Empsight
• Altura

The pros of salary survey data for benchmarking

Historically salary surveys were the only way to access salary benchmarking data. These consultancies, therefore, are well known in the HR space and are typically seen as trusted, credible salary data providers – which can make it easier to get buy-in on budget from senior leadership. 

They’ve also been running salary surveys for a long time, so they’ve amassed a significant number of survey participants, which means there’s a large data pool to rely on.

The cons of salary survey data for benchmarking

However, there are many issues with relying on salary surveys for benchmarking data, with the top disadvantages being: 

• Outdated salary data. Up-to-date benchmarking data is a must to stay on top of the fast-moving talent market and ensure fair and competitive pay for new hires and existing employees. Salary surveys are run once or twice per year. It takes several months for the consultancy to gather survey submissions, aggregate the data, and deliver requested datasets. Therefore, salary survey data always reflects a one-off point-in-time from months in the past – and it will be months before it’s refreshed.
• Error-prone salary data due to manual submissions. Salary surveys rely on companies submitting employee compensation data through manual survey submissions. Not only is this a time-consuming process for People Teams, it also exposes the data to human error, reducing accuracy. 
• Difficult to identify relevant data. Salary surveys tend to have a broad data pool, which can be a positive in terms of data confidence, but can also make it hard to compare to the peers that you actually compete with for talent. The typical participant in salary surveys is a global large enterprise company, often in a legacy industry e.g. manufacturing, oil and gas – so much of the data is irrelevant for other company types e.g. high-growth tech scale ups. It’s usually possible to purchase an industry-specific (or specific peer group) cut of the data at additional costs, but there will be a much smaller data pool so lower reliability.
• Spreadsheet hell. Salary survey datasets are typically provided as large spreadsheets which are incredibly complex to interpret. Some providers do now have the option to access data online (e.g. through The Radford Data & Analytics Platform) but these are consultancies not software companies, so there is very limited functionality.
• Comparison to internal employee salary data is not included. Salary survey data gives you external benchmarking data but, unlike modern salary benchmarking tools, it doesn't give you the means to compare and analyse those benchmarks against your internal employee salaries – without conducting that analysis manually yourself (often in highly complex spreadsheets).
• Inaccurate job mapping. Each participating company submits salary data aligned with the provider’s job role and level descriptors (e.g. Mercer’s job library). The manual nature of submissions means that errors and inconsistencies are inevitable. Further, there are usually a huge number of different job roles and levels due to the type of companies who submit data – which People Teams are left to painstakingly try and accurately map to their internal job architecture and levelling framework.

Option 3: User-reported salary data

Some companies use user-reported data for salary benchmarking with two key varieties:

1. Employee-reported salaries via sites like Glassdoor
2. Salary ranges included on job adverts by other companies.

Salary benchmarking with Glassdoor

Glassdoor crowdsources salary data from employee users of the site, who anonymously submit their salary as well as information on their role, location, industry, and so on. This user-submitted data is then aggregated to produce the Glassdoor salary index, which provides a salary range per role. 

There are other niche sources of employee-reported salary data, often for particular job functions. For instance, content marketing community Superpath publishes an annual content marketing salary report which shares insights based on survey submissions.

The primary use case for this salary data is for job hunters and employees to compare their pay to others in similar roles, helping them evaluate whether they are being paid fairly or how to approach salary negotiations for a new role. 

However, it’s also surprisingly common for companies to use sources like Glassdoor for salary benchmarking.

Salary benchmarking with job adverts e.g. LinkedIn, Indeed

Companies often include the expected salary range in the job advert when hiring for a new role – and this will soon be a necessity for many companies with new pay transparency requirements for job applicants in the EU Pay Transparency Directive.

Some companies will use this information as indicative data for salary benchmarking roles in their own company, through browsing job adverts on job boards like LinkedIn or Indeed.

Some job boards also offer salary calculators, aggregating the data from job adverts to provide ‘salary benchmarking data’ i.e. an average salary per role.

Examples include:

• Michael Page’s salary benchmarking tool
• Indeed’s salary checker
• Reed’s salary checker

The pros of user-reported salary benchmarking data

These data sources have one major advantage: they’re free and easy to access, all you need to do is set up an account.

It’s often difficult to get buy-in from stakeholders on the importance of salary benchmarking, which can leave People Teams with no budget for benchmarking data – so it’s understandable that this might make a source like Glassdoor or LinkedIn appealing.

The cons of user-reported salary benchmarking data

However, user-reported data is never fit-for-purpose for salary benchmarking.

The data is unverified and unreliable.

In terms of using Glassdoor for salary benchmarking, the main issues are:

• Inaccurate self-reported data. There’s no guarantee that employees submit accurate information (especially as Glassdoor often asks employees to submit salary data in return for access to company reviews). There’s also no way to check and verify the data that is submitted. Even when employees do submit accurate data, there may be inconsistencies in how this is reported e.g. some sales executives might submit their base salary and others their OTE. This variance is clear from the broad nature of the salary range given, as you can see in the Software Engineering example in the image below.
• Salaries averaged per role. Glassdoor’s salary checker tool gives a range for each job role, calculated by taking a simple average of all salaries submitted to the platform for that role. Taking an average is not considered best practice in salary benchmarking, because the average can be significantly skewed by outliers (i.e. unusually high or low salaries for that role). Instead, the median salary (50th percentile) should be used, with quartiles to show the data distribution.
• Salaries averaged for all time. Glassdoor’s salary data reflects the average of all salaries ever submitted to the platform for that role, with no time parameters. It does not reflect the current, up-to-date market rate, but rather shows an average of all historic salaries ever offered for that role.
• Impossible to identify relevant data. Glassdoor is a popular site for all kinds of companies, meaning it’s a very broad data pool. There’s no way to filter Glassdoor’s salary data to understand how salaries vary across different industries, locations, company sizes, etc, meaning the data can never give a like-for-like comparison with your specific company – vital for accurate salary benchmarking.

And for job adverts:

• Small sample size. Data confidence is crucial in accurate salary benchmarking, and typically teams will manually identify just a handful of job adverts that fit the roles they’re looking to benchmark. This leaves a tiny sample size which means the salary ranges identified are never going to be representative of the full market.
• High data variance. Different companies do compensation in different ways, so you’re going to find a large amount of variance in the salaries that companies are advertising.
• Large salary range. It’s also typical to see companies designate a large range in the salary advertised for the role – it’s even common for roles to be advertised that could be filled by candidates in several different job levels. Therefore, it does not reflect actual market benchmarks for the role.
• Lack of context. For job advert salary ranges to be valuable, you would need to have a close understanding of how the company at hand approaches compensation. How do they balance base salary, equity compensation, variable pay, employee benefits? What percentile are they targeting? Who do they compete with for talent? How long have they had this job advert live? And so much more. Without that context, the salary range is meaningless.

The best salary benchmarking tools for 2025

It’s clear from the analysis above that salary benchmarking tools are the best data source for accurate and up-to-date salary data.

However, there are several providers of salary benchmarking software on the market today: 

• Ravio (global salary data, strongest for Europe)
• Pave (global salary data, strongest for US/Canada)
• Compa (new hire offer data only)
• CompUp (India only)
• Figures.hr (Europe only)
• Carta (US VC-backed companies only)
• Assemble (Biotech only)
• Compensation IQ by Qlearsite (Europe only, mostly public sector and charity).

There are also other HR platforms which offer third-party compensation benchmarking data too, such as:

• Lattice
• HiBob
• Leapsome
• Barley
• Comprehensive
• Zendesk

With all these options, how do you decide which is right for your company?

What makes the best salary benchmarking tool?

When evaluating the right salary benchmarking software for your company, the most important criteria are as follows: 

• Up-to-date benchmarks. HR platforms that offer third-party salary data often do so through partnerships with salary survey consultancy partners, usually Mercer (all of those listed above offer third-party data from Mercer – Lattice, HiBob, etc). The data is, therefore, not up-to-date. The best option is always software that owns its own compensation database and gathers data through integrations with HR systems. 
• Accurate benchmarks. Again, a provider who sources data through HRIS integrations is the best option for accuracy. It’s also important to ask how the provider is checking and verifying data, as well as how they aggregate it to produce the benchmarks you see in the platform, and how they deal with data gaps e.g. AI modelling or location differentials.
• Comparison of benchmarking data with internal salary data. The real value of salary benchmarking software is that it enables a comparison between market benchmarking data and your current employee salaries or salary bands. This makes analysis straightforward, to identify issues like salary band outliers, salary compression, or pay inequity. It also makes it easy to make adjustments to ensure employee compensation stays in line with market competitive rates at all times.
• Robust data security measures. The best salary benchmarking software integrates with your HR systems (HRIS, cap table) to pull employee compensation data direct from source. This is key for accurate benchmarking, but it does mean that the tool has access to sensitive employee salary data. It’s therefore vital that they have strong data security in place. They should have SOC 2 Type 2 certification and must also have GDPR policies in place for European data.
• A relevant data pool. It’s important for the benchmarking data you use to reflect the companies that you compete for talent with, as this is the only way to stay competitive when attracting and retaining talent. Different providers have different location and industry focus so always check this. Ravio and Pave, for instance, both offer global salary benchmarking data, but whereas Ravio is strongest in Europe, Pave is strongest in the US and Canada. Make sure that the tool also includes filtering functionalities to further ensure comparison with companies in the same industry, with the same HQ location, or at a similar stage of growth. 
• Total rewards benchmarks. For most companies, a view of total compensation is important when benchmarking – base salary, variable pay, equity compensation, and employee benefits. This isn’t always a given. Figures, for instance, offers benchmarks only for base salary and variable pay – whereas Ravio has benchmarks for salary, variable, equity, and benefits.
• Accurate and straightforward job matching. Ensuring a like-for-like comparison between your internal job roles and levels and the salary benchmarks is vital for accurate benchmarking. Ideally you want a benchmarking tool that includes automatic mapping during the onboarding process to make this comparison simple and always consistent. 
• Intuitive and easy-to-use platform. Salary benchmarking software should offer a great user experience, with intuitive functionality for analysing and using benchmarking data. Explore their website for product videos or book a demo to see the platform in action, and check G2 reviews too to see how other users find it. Some tools also offer free trials so you can test it out yourself (like Ravio’s 3 free benchmarks offer).
• Flexible user permissions. Whilst People Teams own the compensation benchmarking process, line managers are typically heavily involved when it comes to new hire salary offers and salary increases, so it’s important that these users can easily gain access to the data when needed. It may also be important for you that employees can view their total rewards package in the platform too, depending on your employee communication and pay transparency approach. 
• Additional compensation management features. Once you have salary benchmarking data, you’ll then want to use that data for other purposes, such as to build (or update) salary bands, complete compensation reviews, or run gender pay gap reporting. It’s ideal if your salary benchmarking tool also offers the additional uses that are relevant for your company, to keep the number of platforms to a minimum and avoid needing to export the data to use elsewhere.

Why Ravio is the best salary benchmarking tool on the market

Ravio ticks all of the tickboxes for what makes a great salary benchmarking tool.

Here’s the full details on Ravio as a salary benchmarking tool – and if you'd like to see the platform in more detail, get in touch:

• Up-to-date benchmarks. Secure integrations with over 100 HRIS tools makes onboarding quick and easy, and ensures Ravio’s compensation benchmarking database is always accurate and up-to-date.
• Accurate benchmarks. All data is checked and verified by Ravio’s team of data scientists and benchmarking experts to ensure a high degree of accuracy and consistency in terms of how data is labelled and interpreted across companies.
• Comparison of benchmarking data with internal salary data. Ravio's platform enables you to view compensation benchmarking data as standalone data – but it also makes it easy to compare those benchmarks with existing employee compensation to see where they fall against the market. Plus, Ravio's salary bands tool also enables you to build salary bands using the benchmarking data, or refresh existing salary bands to bring them in line with the market.

• Robust security measures. Employee data is fully anonymised, and is kept safe and secure at all times through rigorous privacy and security protocols – including GDPR compliance and SOC 2 Type 2 certification. Ravio’s data is hosted in Europe.
• Relevant data pool. Over 1,000 companies (300,000+ employees) contribute to Ravio’s compensation database, with benchmarks available for over 50 countries and over 100 roles, ensuring high data confidence for all benchmarks. Plus, filters are always available for location, industry, headcount, company size, and funding stage, to ensure a relevant data pool to compare against.
• Total rewards benchmarks. Ravio’s total compensation benchmarking data covers base salary, variable pay, equity compensation, and employee benefits.

• Accurate and straightforward job matching. Ravio automatically matches your internal job levels with the Ravio level framework to ensure a like-for-like comparison – and if you don’t have levels yet, Ravio’s team will map your individual employees to the Ravio level framework. 

• Intuitive and easy-to-use platform. Ravio has a G2 rating of 4.7, and users regularly comment that the platform is ‘user friendly’ and ‘intuitive’. 
• Flexible user permissions. Ravio includes the ability to add users to your Ravio account with varying levels of permissions. Plus, you can also share benchmarks and salary bands outside of the platform to help with stakeholder management and employee communication.
• Additional compensation management features. Ravio isn’t just a salary benchmarking tool, it’s an end-to-end compensation management platform – with the ability to use the benchmarking data as the foundation for building salary bands, analysing pay equity, running compensation reviews, and more.