Last updated: 2 October 2026
Originally published: 16 January 2026
The best free salary data sources help People and Rewards teams build market awareness – not full compensation strategies – by offering high-level insights into pay across roles, locations, and industries.
They’re an accessible starting point for when you have no budget or buy-in to invest in dedicated salary benchmarking tools.
But free salary data varies widely in accuracy and is rarely reliable for up-to-date, accurate total compensation insights based on a consistent, representative sample.
The result? Teams often end up working with outdated averages, inconsistent role definitions, or partial views of compensation that don’t reflect how salary, equity, and benefits actually come together.
To use free salary data more deliberately, it’s worth understanding both the available sources and the limits of what they can support.
To that end, this guide walks you through:
You’ll leave knowing how to interpret free salary data and its limitations before applying it to compensation decisions.
One thing before we start: we're a compensation benchmarking provider, and Ravio's free benchmarks are included in the list below. We've tried to be straight about where each source is useful and where it isn't – Ravio included.
There are two kinds of free salary data.
Free salary benchmarking tools give you salary benchmarks for free – either as a free tier from a compensation benchmarking platform, or as a free tool from a global employment (EOR) or payroll provider.
These (should) come with a robust methodology for how the benchmarks are produced, so you can feel confident they actually reflect market rates for your context.
If you’re an HR or Reward Leader looking to understand market competive compensation, expert benchmarking providers are what you should be looking at.
Free salary data sources are freely available pay figures from job boards, crowdsourced sites, recruiters, industry reports, and governments – useful for a sense-check, but not reliable enough for pay decisions.
If you’re just needing to sense-check your thinking, or if you’re an employee curious about how others in your position are paid, these free salary data sources can be handy – but just know that they aren’t an accurate, verified source, so they aren’t robust enough to rely on.
In the rest of this guide, we’ll take a look at 16 free salary data sources, split into these two kinds, and with all the details you need to make your decision.
For now, here’s a quick rundown of those sources:
Source | Type | Data source | What's free | Best for |
|---|---|---|---|---|
Ravio | Benchmarking platform with free tier | HRIS integrations | Three benchmarks for roles of your choice from Ravio’s benchmarking dataset, strongest for global tech companies | Reliable total rewards data for tech roles, trying out Ravio as your compensation vendor before committing |
Pave | Benchmarking platform with free tier | HRIS integrations | Base salary and new-hire equity benchmarks for the US plus one market, for companies with 1-200 employees | US startups |
Playroll x Ravio | Free tool from an EOR provider | Ravio HRIS data, plus Playroll employer cost data | Salary benchmarks and fully loaded hiring costs in 40+ regions | Pricing an international hire |
Salary Insights by Deel | Free tool from an EOR provider | Deel payroll data | Base salary data for 120+ countries | Spot-checking pay in new markets |
Free, partly verified data source | Employee-reported, partly verified | Total compensation by company and level | Big-tech pay and equity | |
Glassdoor | Free but unverified data source | Employee-reported | Salary ranges, after you contribute | Rough ranges for common roles |
Indeed | Free but unverified data source | Job ads and employee reports | Estimated salary ranges | Market-level ranges |
ZipRecruiter | Free but unverified data source | Job postings on its platform | Average salaries by job title and location | US advertised pay |
LinkedIn job ads | Free but unverified data source | Employer job postings | Advertised ranges, where disclosed | Live hiring signals |
Free consumer tool from a benchmarking provider | Employer reports and surveys | Base salary ranges with percentiles | Structured US role ranges | |
Payscale | Free consumer tool from a benchmarking provider | Employee-reported salary survey | A personal salary report, plus salary pages by job title | Individual market-worth checks |
Salary Expert | Free but unverified data source | Surveys and statistical modelling | Average salary estimates | Relocation and cost-of-living comparisons |
WageIndicator | Free but unverified data source | Surveys and national data | Wage data by country | Macro-level wage comparisons |
Robert Half | Free but unverified data source | Placement data and job postings | Starting salary ranges by role | Professional roles in the US and UK |
Government sources | Free but unverified data source | National statistics | Median and mean earnings | Big-picture trends |
Industry reports | Free but unverified data source | Community surveys | Salary ranges for a specific function or region | Context for a niche function |
These tools give you salary benchmarks for free, but they come in two kinds.
Ravio and Pave are compensation benchmarking platforms offering a free tier of the same benchmarks their paying customers use – the closest you'll get to robust benchmarks for free.
Playroll and Deel are employer of record (EOR) and global payroll providers offering free tools to help you price a hire in a new country. They're handy for quick, one-off checks, but they're lighter than a full benchmarking platform.
Ravio is a specialised compensation data provider that integrates with HRIS systems to give high-growth tech companies total rewards data in real-time.
It gives you three free benchmarks for three roles of your choice (no credit card required) to assess how relevant the salary data is for you.
Unlike most free sources, Ravio's free benchmarks are actual benchmarks – the same reliable, relevant data paying customers use, pulled from the HR systems of 1,600+ companies and validated by a team of data scientists before it's published.
As Clara Nicolas at PayFit puts it: "Sometimes a job can be super niche. I go through Ravio to find it because the variety of jobs is higher than in other providers, especially in tech."
Pros | Cons |
|---|---|
Real-time, global total compensation data with particularly strong coverage in Europe. | Data less relevant for organisations with few tech roles. |
Data verification process with data scientists reviewing data for accuracy and consistency across industries and roles. | Three free benchmarks are a way to test the data – ongoing benchmarking needs a paid plan. |
Advanced filters for location, industry headcount, company size, and funding stage to support relevant salary benchmarking. |
Pave is a US-based compensation benchmarking company that gives you real-time pay data via HRIS integrations.
It comes with a free tier plan for startups (companies with 1-200 employees) called Market Data Lite that offers compensation data in the US and one additional market of your choice.
Pros | Cons |
|---|---|
Real-time compensation data, strongest in the US and Canada. | Thinner total compensation data outside North America. |
Real-time hiring trends data via Pave's integration with ATS systems. | The free tier only covers the US and one other market – wider coverage and custom peer groups need the paid Market Data Pro plan. |
Poor global data coverage for fast-growing teams that hire outside the US, often reliant on US-based differentials for Europe. |
Playroll, an employer of record (EOR) and global payroll provider, offers a free salary benchmarking tool built in partnership with Ravio.
It pairs Ravio's salary benchmarks with Playroll's data on the fully loaded cost of employing someone in each country – so you can see both what a role pays and what the hire will actually cost.
Because the salary data comes from Ravio, the benchmarks themselves are validated in the same way. But the tool is built for pricing individual hires, not for ongoing benchmarking across your team.
Pros | Cons |
|---|---|
Benchmarks come from real payroll data, not job ads or self-reported figures. | Salary only – no equity, variable pay, or benefits benchmarks. |
Shows the total cost to hire, not just the salary. | Limited to 40+ regions, with usage limits on the free tool. |
Only shows a benchmark when there's enough data behind it. | Built for one-off checks, with no tools for salary bands or analysis. |
Salary Insights is a free salary data tool by Deel, a global payroll and compliance platform. It provides market-level salary data across multiple roles and geographies.
Salary Insights sources real-time data from Deel’s platform activity, covering payroll and contractor engagement data across global workers.
As a free tool from an EOR and payroll provider, it's built to help you spot-check pay in new hiring markets rather than to provide robust benchmarks.
Deel does offer a paid compensation module, Deel Compensation, which includes its full 150+ country dataset – see more on that here.
Pros | Cons |
|---|---|
Real-time salary data from up-to-date platform activity. | No insights into benefits, equity, bonuses, and structured pay bands – all essential for competitive compensation planning. |
Global coverage with data for 120+ countries in the free tool (the full 150+ country dataset comes with the paid Deel Compensation product). | Limited transparency on the data verification process, with no publicly available details on how data is cleaned or weighed. |
Filters available to find data by role level, seniority level, and location. | Data may be biased toward Deel’s remote, contractor-heavy user base, limiting its representativeness across industry-specific markets and roles. |
Salary.com is a compensation data website offering market estimates, with free online salary tools, including a salary calculator.
It collects free pay data from a mix of employer-reported insights, salary surveys, and third-party sources, with limited public detail on data collection and verification methodology for free insights.
Salary.com is also a compensation benchmarking provider – its paid CompAnalyst platform offers employer-grade benchmarks, with a 14-day free trial. But its free salary tools are built for individuals, and aren't the same as the benchmarks in CompAnalyst. We cover CompAnalyst in our guide to salary benchmarking tools.
Pros | Cons |
|---|---|
More structured role definitions than crowdsourced platforms. | Free data is high-level and lacks customisation. |
Clear percentile framing for salary ranges. | Limited transparency around data verification methodology for its free tool. |
Limited to no data on fast-changing or niche roles. |
Payscale is a compensation software and data company. Its free salary data is aimed at individuals: you complete its online salary survey and get a free report on your market worth, and it also publishes free salary pages by job title.
The free data comes from Payscale's crowdsourced salary survey, which holds over 60 million employee-reported pay profiles.
Payscale is also a compensation benchmarking provider – its paid Payfactors and Marketpay products combine survey, employer, and crowdsourced data for employers. But its free salary reports are built for individuals checking their own pay, not for setting pay across a team. We cover its paid products in our guide to salary benchmarking tools.
Pros | Cons |
|---|---|
A very large crowdsourced dataset, with broad role coverage. | Employee-reported data, with no employer verification. |
Useful context on how experience and skills affect pay. | Built for individuals checking their own pay, not for setting pay across a team. |
Strongest for the US, with thinner international coverage. |
Other free options from paid tools: several benchmarking providers offer free plans or trials too.
OpenComp has a free version, Comprehensive.io publishes free salary ranges from US tech job postings, CompAnalyst by Salary.com offers a 14-day free trial, Payscale offers a limited free trial of Payfactors, and Compensation IQ offers a seven-day free trial. We compare them all in our guide to salary benchmarking tools.
These sources are free to access, but they aren’t from benchmarking experts and so the data isn't built as robust benchmarks that you can rely on for confident, defensible comp decisions.
They're useful for a directional sense-check only.
Glassdoor is an employer review and job marketplace that collects self-reported salary data from employees and former employees who anonymously submit their job title, salary, location, and other details.
The data is then aggregated to produce the Glassdoor salary index that provides a salary range per role.
Because Glassdoor is based on a give-to-get model, you can only access the data by submitting yours.
Pros | Cons |
|---|---|
Large volume of salary data for common roles. | Unverified data, as it's crowdsourced from website users with no checks to make sure the submitted data is accurate. |
Outdated salary averages with displayed ranges based on the average of all salaries ever submitted for that role, with no outliers taken into account. | |
No way to identify up-to-date shifts in the salary based on market trends. | |
No filters by company type or size – making it challenging to make accurate, like-for-like pay comparisons with your peers. |
Indeed is a global job search engine that aggregates salary data via job postings with disclosed pay, employee self-reported submissions, and the platform's statistical estimates.
You can search it for free via Indeed Salaries.
Pros | Cons |
|---|---|
Easy to access by simply setting up a free account. | Data variance as different companies calculate compensation in different ways. |
Broad role and geography coverage. | Inconsistent transparency around how data is weighed between sources. |
Useful for understanding market-level salary ranges. | Data isn’t designed for fair and competitive compensation planning. |
Easy to access by simply setting up a free account. | Data variance as different companies calculate compensation in different ways. |
ZipRecruiter is a US online job marketplace that publishes free salary data by job title and location, built from job postings on its platform and third-party data sources.
One thing to watch: since 2023, ZipRecruiter adds its own salary estimate to job ads where the employer doesn't list one – so not every figure reflects what an employer actually advertised.
Pros | Cons |
|---|---|
Data comes from live job postings, so it reflects current hiring activity. | Advertised pay, not actual pay – and some figures are ZipRecruiter's own estimates. |
Broad coverage of US roles and locations. | US-focused, with limited value for international hiring. |
No filtering by company size, stage, or industry. |
LinkedIn job adverts are job postings that employers publish, sometimes including salary ranges due to company policy or regional pay transparency laws such as the EU Pay Transparency Directive.
You can manually review these listings on LinkedIn to gauge market rates.
Pros | Cons |
|---|---|
Real-time reflection of hiring market signals. | Unreliable data as employer-submitted information is not standardised and lacks context around the company’s compensation philosophy and target percentile – making it hard to understand what a salary range actually reflects. |
Direct employer intent rather than retrospective reporting | Small sample size with manual sourcing, which makes the data statistically unrepresentative of the market. |
Data is based on the interpretations you make of the job role and level to understand whether it’s for the same role and level you’re looking for. | |
Equity and variable compensation insights are usually high-level or omitted. |
Levels.fyi is a compensation data platform focused primarily on tech roles across multiple regions and industries like retail, accounting, investment banking, gaming, and more.
It offers pay breakdowns (salary ranges and median pay) at large technology companies – including salary range heatmaps and charts.
Levels.fyi sources free data from self-reported employee submissions.
Pros | Cons |
|---|---|
Compensation data updates in real-time, giving you fresh insights. | Not every submission is verified. Levels.fyi verifies some via work email and proof documents like offer letters, and weights unverified data differently. |
Detailed levelling and role context for major tech companies. | Salary data leans heavily toward big tech and venture-backed startups. |
Limited usefulness for non-technical or non-US roles. |
Salary Expert is a compensation comparison site powered by the Economic Research Institute's (ERI) Assessor Platform that provides salary estimates across roles, locations, and seniority levels.
It aggregates data via a combination of salary surveys, employer reports, and statistical modelling, with methodology summaries provided at a high level.
Pros | Cons |
|---|---|
Useful salary insights for international or relocation comparisons. | Free data lacks the granularity needed for compensation decisions – making it less effective for company-level benchmarking. |
Salary insights backed by geographic and cost-of-living context. | Limited visibility into sample size for specific roles. |
Unreliable data freshness with most data sources updating infrequently rather than in real-time. |
WageIndicator is a non-profit organisation that collects wage data and labour market information across multiple countries to support labour market transparency.
It aggregates pay insights from national websites and databases, field research, and online surveys it conducts to assess salaries and working conditions.
Pros | Cons |
|---|---|
Provides insights into gig worker pay. | Data is refreshed annually – if there’s no research to back the updates, WageIndicator adjusts data according to annual inflation. |
Open access with broad international coverage. | Survey participation varies significantly by country, making the data highly variable across locations. |
Useful for macro-level wage comparisons. | Limited relevance for company-specific benchmarking – with data suited for policy analysis rather than compensation planning. |
Robert Half is a global staffing and recruitment firm that publishes annual salary guides and offers salary calculators – including a US calculator covering 425+ roles in seven professional fields, and a UK calculator covering 24 cities.
Robert Half sources the salary data from its own talent staffing activity and third-party job postings – using AI to analyse the compiled data against key market conditions, and current and projected talent supply and demand.
Pros | Cons |
|---|---|
Partly employer-informed data rather than purely crowdsourced inputs. | Limited transparency into sample sizes. |
Data is reported in three levels: low, mid, and high to account for pay variability based on employee skills, experience, and organisational factors like industry, company size, and revenue. | Compensation data is limited to salary insights and a handful of professional fields, including legal, tech, and creative. |
Data typically refreshes annually as new survey results come in. |
Government pay data sources are official, publicly funded datasets produced by national statistics offices and labour departments.
They’re designed to track labour market trends and wage levels – collecting data via large-scale employer surveys and mandatory statistical reporting, often combined with census data to drive official statistical estimates.
Some examples of governmental salary data sources include:
Pros | Cons |
|---|---|
Data collection methods are standardised and methodologically rigorous, making the data credible. | Salary data isn’t fresh often since surveys typically run annually and are published months after collection. |
Large sample sizes and national coverage. | Role definitions are broad and slow to adapt to niche or emerging job roles. |
Useful for big picture salary and trend analysis. | No job levelling granularity, making the data unsuitable for pay banding, equity planning, or hiring decisions. |
Industry- and location-specific salary reports are surveys produced by industry thought leaders, communities, organisations, or trade groups.
They focus on a defined role set, function, or region and use employee-reported surveys to gather data, with surveys typically accessible through the publisher’s community, website, newsletter, or member network.
Survey sample size and methodology vary by publisher, but these are not robust compensation benchmarking surveys and should not be relied on for this purpose.
Examples of these industry- and location-specific salary surveys include:
Pros | Cons |
|---|---|
Typically free to access data. | Unreliable insights as data is self-reported, where even minor reporting errors can skew results. |
Often more up-to-date than free governmental salary data sources. | Data is limited to averages per role, which isn’t robust enough to generate usable benchmarks for compensation planning. |
Limited role standardisation across companies. |
Short answer: No, free salary data isn’t reliable for compensation planning.
Sure, free salary data is useful for building market awareness and sense-checking assumptions. But compensation planning requires accurate, relevant data in real-time that’s comparable across levels and peer groups. Most free salary data isn’t built to meet that bar.
As a result, free salary data is not reliable enough for:
That leaves free salary data appropriate only for:
That's why FTAPI moved away from free sources to Ravio when it professionalised its compensation decisions.
As Kim Heckner, Head of People & Culture, puts it: "Of course, people wanted to understand why we have to spend money on a product when we can search for the same information online for free. But Google and LLMs are not the Mr. Know-It-All."
TestGorilla found the same before switching to Ravio.
"We were working from free reports from European providers and scraping them manually to create company-wide bands," says Luis García de la Cruz, Senior People & Culture Partner. He rated his confidence in that data at five or six out of 10 – and falling as it aged.
And Tiqets had a similar experience. It used to run compensation reviews on Glassdoor and LinkedIn data, and line managers didn't trust the figures enough to have productive pay conversations.
Free sources typically provide high-level salary ranges for broad roles and industries, with limited transparency around data freshness, sample size, and verification.
In contrast, specialised benchmarking providers offer verified, up-to-date, granular data aligned to your hiring philosophy and the specific roles you’re hiring for.
Here’s a detailed comparison:
| Free salary data | Paid salary benchmarking tools |
|---|---|---|
Data freshness |
Often irregularly updated or based on historical averages, giving outdated salary data.
|
Depending on the tool, data is continuously refreshed in real-time. |
Compensation dataset
|
Typically limited to base salary ranges, with inconsistent or missing insights into variable pay or equity. |
Usually includes base salary, variable pay (bonuses, commissions, incentives), and equity compensation
|
Data relevance |
Drawn from broad roles, industries, and regions, with limited filtering by company size, stage, or peer group. |
Different providers offer stronger data coverage in specific industries and regions.
Allow filtering by role, level, location, industry, company size, and revenue.
And many tools also support percentile targeting aligned with compensation philosophy.
|
Data reliability
(collection methods) |
Often relies on self-reported employee data or traditional salary surveys, which increases the risk of reporting errors impacting data accuracy.
|
Commonly collected via HRIS integrations (direct employer data) reducing manual entry errors and improving data accuracy. |
Data reliability
(verification and maintenance processes) |
Limited or no formal data validation. Data is also often based on small or inconsistent sample sizes. |
Many providers apply data validation processes, including outlier detection, stale data removal, and provide visibility into sample size and confidence levels.
|
Data granularity
|
Broad or unstandardised role definitions limit usable granularity.
|
Offers role granularity (example, frontend, backend, and full-stack engineers) with some providers like Ravio giving you data for niche or emerging roles (example, AI engineers).
|
Traditional salary surveys are generally more reliable than crowdsourced platforms – but only under specific conditions when:
However, many free surveys still rely on self-reported data, increasing the risk of errors from manual submissions. And because surveys are typically conducted at a large scale only once or twice a year, results are often aggregated and published months after collection – making the data outdated by the time it reaches you.
Ultimately, the difference isn’t “survey vs crowdsourced.” It’s whether the data is current, accurate, and representative of your actual workforce context.
Free salary data can be genuinely useful as long as you’re clear on its intended use cases and limitations.
As you review free pay data sources, step back from the numbers to look at the signals behind them. Pay attention to whether:
Just as importantly, consider which roles, company sizes, and industries the data reflects – and which are underrepresented.
These checks aren’t about finding a perfect free source. They’re about understanding how much confidence a source actually deserves before you use it to inform real compensation decisions.
Ultimately, remember that free salary data is best used as a starting point, not a source of truth.
And if you’re ready to move beyond broad market averages, reliable, human-verified benchmarks can help. One place to start is Ravio’s three free benchmarks.
Free salary data sources are publicly accessible tools and reports that provide pay information at no cost. These include crowdsourced platforms, job ads, salary surveys, government datasets, and free tools from modern compensation benchmarking platforms. They’re designed for general reference and market awareness, not formal compensation planning.
Free salary data is pay information that's freely available – from job boards, crowdsourced sites, recruiters, and governments – but it isn't built as benchmarks, so it's rarely verified or comparable like-for-like. A free salary benchmarking tool gives you salary benchmarks, usually with limits.
It comes in three kinds: a free tier from a compensation benchmarking platform, like Ravio's three free benchmarks or Pave's Market Data Lite; a free tool from an EOR or payroll provider, like the Playroll x Ravio tool or Deel's Salary Insights; or a free consumer tool from a benchmarking provider, like Salary.com's salary calculator or Payscale's salary report.
Free tiers from benchmarking platforms give you the most robust data; the others are best for quick checks.
Free salary data is collected in several ways. Some platforms rely on self-reported employee submissions. Others use employer-reported job ads, statistical modelling, or government surveys. Some salary benchmarking tools provide real-time data from HRIS integrations. Each method varies in accuracy, freshness, and reliability.
Trust salary data only as a starting point for high-level market analysis and sense-checking assumptions – not for compensation planning. Although free salary data gives you a broad understanding of market ranges, it lacks the reliability, relevance, and granularity you need to build pay bands or conduct equity analysis.
Relying on free salary data becomes risky when you use it for salary band design, equity compensation analysis, or competitive pay decisions. At this stage, small inaccuracies compound into long-term cost, retention, and compliance risks. Free data often lacks consistent levelling, representative samples, and up-to-date market signals required for precision.
The biggest limitations of free salary data are outdated insights, sample bias, limited role and company relevance, and incomplete total rewards data. Many sources rely on self-reported or averaged figures – making it difficult to get accurate data, compare insights for like-for-like roles, or understand how salary, equity, bonuses, and benefits work together.
Free salary data has limited value for pay equity analysis. While it can highlight high-level trends, it lacks the demographic controls, sample consistency, and standardized role definitions that you need for accurate equity assessments. Relying on it for pay equity decisions can lead to misleading conclusions and increased compliance risk.
Yes, a few options are built for employers rather than job seekers. Ravio offers three free benchmarks for any role, level, and location, Pave's Market Data Lite is free for companies with 1-200 employees, and the Playroll x Ravio tool shows salary benchmarks alongside the full cost of an international hire. Professional bodies also offer free reports to members – for example, WorldatWork members get a limited number of free benchmark reports each year from Salary.com and Payscale.
People teams should validate free salary data by checking data recency, role and level consistency, and sample transparency. Confirm how data freshness is handled, whether roles are over- or under-segmented, and if contractor and full-time pay are separated. Also, assess whether benchmarks reflect total compensation and if contributing companies represent your industry, size, and hiring context. Finally, cross-check multiple sources for consistency, not precision.
The most up-to-date free salary data typically comes from compensation platform-derived free online tools such as Ravio’s free benchmarks, as it reflects real-time total compensation data that’s verified by a human team of benchmarking experts. Government datasets and salary surveys are also reliable, but update less frequently. Crowdsourced platforms often lag behind fast-moving labour markets.
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From free salary calculators to real-time benchmarking platforms, the options are wide – and the quality varies enormously. Here's every type of salary benchmarking tool compared for 2026.
