
What to pay Product Managers in 2026: Salary and hiring trends
Product Manager salary in 2026: Β£69,000 on average in the UK, Β£122,100 at senior manager level, Β£214,100 for a CPO. Plus pay by country, stage, and hiring trends.

Last updated: 2 October 2026
Originally published: 20 November 2023
There's no shortage of options when it comes to salary benchmarking.Β
Free salary calculator tools from recruiters like Hays and Michael Page. Employee-reported platforms like Glassdoor. Annual surveys from traditional consultancies like Mercer. Purpose-built compensation benchmarking platforms that pull directly from HR systems.
Itβs easy to find data, but ensuring that data will actually hold up when you're making a hiring decision, defending a salary band to leadership, or working out whether your team is paid fairly isnβt always so easy.
Some tools are built specifically for that.Β
Others are useful for a quick sanity check β but will leave you exposed the moment a decision gets scrutinised.Β
The difference isn't always obvious from the outside.
So in this guide, weβll help you:
One thing before we start: we're a vendor in this space, and Ravio is included in the list below. We've tried to be straight about where we fit and where we don't β but you should judge Ravio by the same bar as everyone else here, and evaluate based on your specific company needs.
There are lots of places to get pay data β but data isn't the same as a salary benchmark.
To benchmark pay properly, you need benchmarks that are relevant to your organisation, reliable enough to defend, and built on a robust, transparent methodology.
For high-growth tech and tech-enabled companies hiring across Europe and globally, Ravio is the strongest choice. Its benchmarks are built from live HR system data from 1,800+ companies and validated by a team of data scientists before they're published.
Other options include Pave for US and Canadian startups, traditional salary surveys like Radford for large enterprises, HR platform modules like HiBob for basic coverage, and free tools like Glassdoor for a quick sense-check.
To see how all 20 tools weβve evaluated compare, jump to the comparison table.
When you're evaluating options for compensation benchmarking, it's important to know that not all salary benchmarking tools are built the same way.
A free salary calculator by a job platform isnβt going to give you the same insights as purpose-built compensation benchmarking software.
The most important difference is where the underlying data comes from and how it's turned into a benchmark.Β That determines how current, accurate, and relevant the salary benchmarks actually are β and, in turn, how confident and defensible the compensation decisions you use them to make are.Β
In other words, not every source that calls itself a βbenchmarkβ is one. A reliable benchmark needs a trustworthy data source, a clear validation methodology, and recently produced data.
There are five broad categories to understand β here's a quick summary of the differences, before we dive into a more detailed explanation:
Integration-based platforms (e.g. Ravio, Pave) | Salary survey providers (e.g. WTW, Radford, Brightmine) | HRIS platforms with benchmarking module (e.g. HiBob, Lattice) | Job ad aggregators (e.g. HRDataHub) | Unverified tools, calculators, and guides (e.g. Glassdoor, Hays) | |
|---|---|---|---|---|---|
Data delivery | External benchmarks and internal salary data accessible 24/7 via a software platform | Benchmarks delivered in a spreadsheet or online portal β software capabilities are limited. Payscale and CompAnalyst aggregate multiple survey sources into a platform | Licensed into your existing HRIS platform β convenient but limited | Salary ranges accessible via a dedicated platform or free online tool | Salary range via free online calculator or downloadable guide |
Data recency | Benchmarks updated regularly as HRIS data refreshes continuously at source | Point-in-time data gathered via surveys conducted annually or quarterly. Payscale's HRIS-integrated data refreshes more frequently | Inherits the refresh cadence of the underlying survey source β typically annual or quarterly, with limited transparency on timing | Updated daily or weekly from job posting activity | Unknown for job ad tools. Average from all-time submissions for Glassdoor |
Accuracy and reliability | High accuracy β data pulled directly from HRIS systems, no manual submission risk. Human validation adds a further quality layer | Risk of human error due to manual salary survey submissions | Inherits the accuracy limitations of the underlying survey source, with limited additional validation | Reflects advertised pay, not actual pay β ranges are often wide and unverified | Highly unreliable β unverified, no methodology, no quality controls |
Peer group relevance | Targeted data pools with filters for location, industry, company stage, and headcount. Percentile breakdowns available to position pay deliberately against the market | Broad global data pool, skewed toward large legacy enterprises. Filtered peer group reports available at added cost. Payscale and CompAnalyst offer some additional filtering | Reflects the underlying survey pool β typically broad and enterprise-weighted | No peer group filtering β data reflects all companies posting jobs, regardless of size, industry, or stage | No peer group filtering. No percentile breakdowns |
Job mapping | Automated job mapping against the provider's framework, ensuring like-for-like comparisons | Manual mapping against a complex job library. Payscale offers algorithm-assisted matching; CompAnalyst uses AI-guided matching | Manual mapping against the underlying survey provider's job catalogue | Keyword-based job title search β no formal level framework | No mapping |
Compensation tools | Typically include salary bands, pay equity analysis, and comp review workflows built on top of the benchmarking data | Piecemeal β survey data plus standalone tools or consultancy projects. Payscale and CompAnalyst include broader comp management tooling | Basic compensation tools within the wider HR platform | None beyond basic trend reports | None |
Integration-based platforms source compensation data directly from the HR systems, ATS platforms, and/or cap table tools their customers use, via live integrations.Β
Because the data comes straight from the source rather than being manually submitted or self-reported, it's not impacted by human error. Plus, the integration means the data is continuously updated at source, more accurately reflecting current market conditions compared to survey-based alternatives.
Most platforms in this category are built for robust compensation benchmarking analysis β with filters for peer group, location, industry, company size, and funding stage, and percentile breakdowns (25th, 50th, 75th, and above) so you can position compensation deliberately against the market rather than just referencing the median.Β
Most also include compensation management tools like salary bands, pay equity analysis, and comp review workflows, built on top of the benchmarking data.
Examples: Ravio, Pave, Figures, Carta Total Comp, Compa, OpenComp
The main limitation: Coverage varies by provider. Some focus on specific geographies, industries, or compensation components β Carta, for instance, is primarily equity-focused and strongest for US private companies.
To learn more about how integration-based benchmarks work β including why they produce more accurate insights and save teams time on manual processes β book a demo with the Ravio team.
Traditional salary surveys are run by HR consultancies β Radford, Willis Towers Watson, Korn Ferry, etc β who invite companies to submit their compensation data manually, usually once or twice a year. That data is aggregated and sold back as benchmarks.
Salary surveys were previously the only way to access salary benchmarking data, which means the data pools are large and consultancies like Mercer and Radford have established reputations that can make leadership buy-in easier.Β
The trade-offs are significant though: manual submissions introduce reporting inconsistencies, annual cycles mean data can be six to twelve months old by the time you use it, and datasets skew heavily toward large legacy enterprises β which can make them less relevant for high-growth or tech-focused organisations.
As Evert Kraav, Senior Compensation Manager at Bolt, puts it: "Traditionally, the survey providers launch once per year, and everything that happens after that date isn't available until the following year."
Examples: Radford, Willis Towers Watson, Korn Ferry, Brightmine, Croner
The main limitation: Data freshness and relevance β in fast-moving markets, salary survey data is already behind by the time it's published.
Several broad HR platforms β including HiBob, Lattice, Workday β offer compensation benchmarking as a module within their wider people management suite, typically by licensing data from a traditional survey provider like Mercer.
The appeal is convenience: if you're already running HR operations in one of these platforms, accessing pay data without adding another tool has obvious advantages.
The data limitations are the same as with the underlying survey source β typically annual or quarterly refresh cycles, manual job mapping, and a participant pool weighted toward large enterprises. But itβs often compounded further, because these modules typically license only a portion of the provider's full dataset, and it's rarely clear how or when that data is updated within the platform.
Examples: HiBob, Lattice, Workday
The main limitation: Benchmarking is a secondary product. The data quality and tooling depth rarely match what a dedicated platform offers.
Some tools scrape job postings from across the web to produce salary benchmarks based on advertised pay ranges β and with pay transparency legislation like the EU Pay Transparency Directive pushing more companies to disclose salary ranges in job ads, this data source is growing.
The limitation is that job adverts reflect what companies are willing to advertise rather than what they're actually paying β giving a broad range rather than an actual salary per role, level, and location.Β
Ranges can also be inflated or inaccurate relative to the eventual offer a candidate receives.
Examples: HRDataHub, Comprehensive.io, Compensation IQ (in part), Indeed's free salary calculator tool
The main limitation: Advertised pay and actual pay aren't the same thing. Ranges are often wide and context is limited.
Salary calculators, recruiter guides, and employee-reported tools are abundant, easy to access, and often cost nothing β but the data behind them is unverified and untrustworthy.
Glassdoor and Levels.fyi both collect self-reported salary submissions from individual employees to produce their salary checkers.
Recruiters like Hays, Michael Page, and Robert Half often use data gathered from the jobs they advertise and the placements they make to produce free salary reports or calculators too.
And some HR platforms produce similar free tools too β like BrightHR who aggregate payroll data into their salary benchmarking calculator.Β
These tools are useful for orientation and sense-checking as one-offs, but none of these are built for defensible compensation decisions β the data is unverified, thereβs no methodology for producing robust benchmarks beyond averaging, and the peer group filtering is limited or absent.
Examples: Glassdoor, Levels.fyi, Hays salary guide, Michael Page salary checker, Robert Half salary guide, Indeed, BrightHR
The main limitation: No rigorous methodology, no peer group filtering, and no way to verify accuracy. A useful starting point β but not a reliable basis for pay decisions.
It's an increasingly common question, and the same caution applies as with options 4 and 5 β because thatβs where LLMs pull their βbenchmarksβ from.
An AI tool can give you a plausible-sounding salary figure, but it can't tell you where that number came from, how recent it is, or whether it reflects companies like yours.
General AI tools don't have access to verified compensation datasets.
They generate a likely answer from training data and whatever they can find publicly β which is different from a validated benchmark you can defend.
As Kim Heckner, Head of People & Culture at FTAPI, puts it: "Google and LLMs are not the Mr. Know-It-All."
We've covered where AI does help in a benchmarking workflow, and where it doesn't, in our guide to using AI tools for salary benchmarking.
The right salary benchmarking software depends on what you actually need the data to do.Β
A free salary checker might be enough for a quick one-off sense-check before a hiring conversation. But it won't be enough for ongoing consistent and fair compensation decisions, building salary bands, running a compensation review, or defending pay decisions to leadership or regulators.
There are three core areas to consider to help you choose the right salary benchmarking tool for your organisation:
Before anything else, check whether the benchmarks actually reflect the roles, locations, and company type you need.Β
A large dataset isn't useful if it's built from companies nothing like yours β a dataset built primarily from large legacy enterprises in the US won't give you useful benchmarks if you're a tech scaleup hiring across multiple European markets, even if it contains millions of data points.
Coverage spans four dimensions: role and level granularity, geographic depth, peer group relevance (industry, size, and stage), and total rewards scope.
Questions to consider:
Coverage is important, but it doesnβt guarantee reliability.Β
The two factors that determine whether benchmarks are trustworthy are data source and benchmark methodology.Β
Data source determines how accurate and current the underlying data is β benchmarks built from live HRIS integrations are less prone to error than those built from manual survey submissions, job ad scraping, or employee self-reporting.Β
Benchmark methodology determines whether that raw data has been turned into something you can actually rely on β how outliers are handled, what sample sizes are required before a benchmark is published, and how transparent the provider is about all of the above.
Questions to consider:
Even accurate, relevant benchmarks have limited value if they can't be used by the people who need them, in the workflows where decisions actually get made.
Think about who uses benchmarking data in your organisation and when β talent teams at the point of offer, line managers reviewing their team's pay, Reward teams building salary bands or running comp reviews.Β
The ability to customise user access and visibility, and whether the platform includes broader compensation tools, determines how valuable a benchmarking tool will actually be for your compensation decisions and processes.
Questions to consider:
Now that you understand the landscape of options in the salary benchmarking space, letβs take a look at how different providers compare.
Below is a breakdown of 20 specific tools β what each one is, how it sources and builds benchmarks, and who it's actually best suited for.
How we compared these tools: we assessed every tool against the three questions above β coverage, reliability, and day-to-day use.
Our sources were each vendor's own website, published methodology, and pricing pages, plus independent sources like G2 and Vendr, all checked in October 2026.
Before we dive into the details, here's a summary who each tool on this list suits best:
Ravio is a compensation benchmarking platform built for high-growth tech companies, with particular depth across Europe.
Data is sourced via live HRIS integrations with 1,800+ companies and validated monthly by a team of data scientists β covering base salary, equity, variable pay, and benefits across 50+ countries and 300+ roles.
Biggest Ravio pro: Reliable, real-time total rewards benchmarks, validated by experts and especially deep across Europe.
Biggest Ravio con: Less depth for organisations with few tech or tech-enabled roles.

Pave is a strong option for US and Canadian tech companies, with real-time data from 9,000+ companies and a solid end-to-end comp planning suite.
It now covers 55+ countries, but equity and variable pay data is thinner outside North America, and modelled differentials are often relied on for non-US countries.
Biggest Pave pro: Strong real-time US and Canadian data, plus end-to-end compensation planning.
Biggest Pave con: Thinner coverage outside North America, with more reliance on modelled data. As one G2 reviewer puts it, "the depth of available market data varies by region and role. For a global organization, the coverage does not always go far enough."
Figures is a European compensation management platform offering benchmarks for base salary and variable pay through HRIS integrations and a Mercer partnership.
Biggest Figures pro: Benchmarks and EU pay transparency tools in one European platform.
Biggest Figures con: No equity or benefits benchmarks.
Carta is primarily a cap table management platform, so equity benchmarking is its strength due to cap table integrations, while salary data is less robust.
Carta only works with privately held startups β primarily US-based β so its benchmarks arenβt relevant for public companies, and coverage is limited internationally.
You also need to be a Carta cap table customer to use it.
Biggest Carta pro: Some of the strongest private-company equity benchmarks available.
Biggest Carta con: Only available to Carta customers, and salary data is less mature.
Compa is an offers-based tool designed to supplement traditional salary surveys. It surfaces real-time data from live job offers via ATS integrations β useful for understanding what the market is actively paying right now, but no broader comp management tools.
Biggest Compa pro: Live offer data that shows what the market is paying new hires right now.
Biggest Compa con: No salary band, pay equity, or compensation review tools, and offers data is not reflective of overall market rates.
OpenComp is a US compensation management platform that combines market benchmarking with tools for pay ranges, merit cycles, and pay equity.
It integrates with payroll platforms like Gusto, making it accessible for small and mid-sized businesses, and has a free version to get started.
Biggest OpenComp pro: An all-in-one compensation platform with a free starting point for US SMBs.
Biggest OpenComp con: US-focused, so less useful for companies hiring internationally.
Radford (Aon) is one of the most established names in compensation benchmarking, operating as the HR consulting arm of Aon and offering salary survey data as one service.
Its core compensation data offering is an annual salary survey covering base salary, equity, variable pay, and benefits β with particular depth in technology roles. Survey data is accessible via spreadsheet or Human Capital Analytics, Aon's online platform for the Radford McLagan Compensation Database.
Radford also publishes market practice studies covering areas such as salary increases, incentive design, and severance.
Mercer, Willis Towers Watson, Korn Ferry, and Culpepper are comparable alternatives worth evaluating for global enterprise needs β though all share the usual salary survey limitations.
Biggest Radford pro: A broad, trusted global dataset, with deep equity data for tech and life sciences.
Biggest Radford con: Annual, manually submitted data that's months old by the time you use it.
Brightmine β formerly XpertHR and Cendex β is a UK salary survey provider that has built a benchmarking platform around its employer-reported dataset.Β
Monthly refreshes make it faster than most traditional survey providers, but the underlying data is still manually submitted by employers rather than sourced via HRIS integrations β so the same limitations around submission consistency and verification apply.
Croner Reward is a similar UK salary survey alternative with particular depth in sector-specific reports for charity, care, and distribution.
Biggest Brightmine pro: UK data refreshed monthly β faster than most survey providers.
Biggest Brightmine con: UK only, and still based on manual employer submissions.
Payscale is a hybrid platform aggregating data from multiple sources β useful for teams that want survey data and HRIS-integrated benchmarks in one place. Data quality varies by source, and global coverage outside the US is thinner.
Biggest Payscale pro: Survey, employer, and employee data in one platform.
Biggest Payscale con: Reliability varies by source, and the product range is complex. Global coverage can also fall short β as one G2 reviewer puts it: "We were told the platform provided global market data, but the data available for us covered only two countries."
A US-focused aggregator combining survey data, employer HRIS uploads, and job posting ranges.
CompAnalyst offers a broad feature set and strong US coverage, but data reliability varies significantly across sources β job posting ranges in particular carry the usual caveats around advertised vs actual pay.
Biggest CompAnalyst pro: A broad US dataset and feature set for large enterprises.
Biggest CompAnalyst con: Mixes survey data with job posting ranges, so reliability varies by benchmark.
Deel is primarily a global payroll and compliance platform, with a compensation benchmarking tool built on data from its own payroll activity across 150+ countries.
It's useful for teams already running payroll through Deel, but the dataset reflects Deel's customer base β which skews remote-first and distributed β and compensation isn't their area of focus.
You can try the free version via Deel's Salary Insights tool.
Biggest Deel pro: Free base salary data across 120+ countries.
Biggest Deel con: Base salary only, and the data reflects Deel's own customer base.
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 β so you can get an accurate view on what a role pays, and what the hire will actually cost voerall.
Biggest Playroll salary benchmarking tool pro: Accurate salary benchmarks and the full cost to hire, side by side, for free.
Biggest Playroll salary benchmarking tool con: Base salary only, and built for pricing individual hires rather than ongoing benchmarking.
A broad HR platform that surfaces Mercer compensation data as a module within its people management suite.
Convenient for existing HiBob users who want basic pay benchmarking without adding another tool β but the data carries the same limitations as the underlying Mercer survey source.Β
Lattice, Workday, and other HR platforms offer comparable modules on the same basis.
Biggest Hibob compensation pro: Convenient benchmarking inside an HR platform you already use.
Biggest Hibob compensation con: A licensed slice of Mercer survey data, with little clarity on when it's updated.
A benchmarking aggregator combining Mercer survey data and job posting ranges via a Lightcast integration β primarily used by public sector, nonprofit, and charity organisations in the UK and Europe. Data reliability varies across sources.
Biggest Compensation IQ pro: An accessible option for UK and European public sector and nonprofit teams.
Biggest Compensation IQ con: Mixes survey data with unverified job posting ranges.
A UK-only job ad aggregator pulling from 30 million+ live and historical job listings, updated daily. More structured than a free salary checker β with trend data, sector filters, and exportable reports β but benchmarks still reflect advertised pay rather than actual compensation, and equity and benefits aren't covered.
Biggest HRDataHub pro: Daily-updated trends in UK advertised pay.
Biggest HRDataHub con: Advertised pay isn't the same as what companies actually pay.
Comprehensive.io publishes free, daily-refreshed salary ranges from 6,000+ US tech companies, built from the pay ranges employers disclose in job postings. It also offers a paid compensation management platform.
Biggest Comprehensive.io pro: Free, daily-updated US tech salary ranges.
Biggest Comprehensive.io con: Built from advertised ranges, not actual pay, and limited to US tech.
Juicebox is an AI-powered recruiting platform rather than a benchmarking tool.
Its Compensation Intelligence feature shows AI-estimated pay on candidate profiles, backed by verified data from a Levels.fyi partnership β useful for recruiters pricing candidates while they source.
Biggest Juicebox pro: Pay estimates right inside the candidate sourcing workflow.
Biggest Juicebox con: Built for recruiting, not compensation planning β estimates aren't benchmarks you can build bands from.
Free and widely used for general market awareness, but data is unverified and not built for compensation planning β should not be relied on for compensation benchmarking. You can search it via the Glassdoor salary index.
Biggest Glassdoor pro: Free, with broad role coverage.
Biggest Glassdoor con: Unverified, all-time averages that can be well out of date and completely inaccurate.
Started as a community tool for tech employees and has evolved into a more structured platform with an enterprise tier.
Document verification makes it more rigorous than Glassdoor β and the equity and vesting data is a differentiator for US tech roles. Coverage drops sharply outside the US and outside tech.
Biggest levels pro: Granular big-tech pay and equity data, company by company.
Biggest levels con: Employee-reported and US-tech-centric.
Free salary calculator tools from recruiters β like Haysβ free salary checker tool, Michael Pageβs salary benchmarking tool, and Robert Waltersβ salary survey guide reports β and HR platforms β like BrightHRβs free salary calculator β are easy to access and are typically free.
They can be useful for a directional sense-check, but are not built for defensible compensation decisions β theyβre created as useful resources for job seekers and hiring managers, not for robust, verified compensation benchmarking.
Biggest pro: Free and quick for a directional sense-check.
Biggest con: Unverified data with no methodology behind it.
Here's how all 20 tools stack up against the three questions from our how to choose section β who the benchmarks cover, how reliable they are, and what they help you do day-to-day.
Tool | Who the benchmarks cover | How reliable the data is | Day-to-day compensation tools | Best for |
|---|---|---|---|---|
Ravio | Tech and tech-enabled companies hiring globally β 50+ countries, strongest in Europe | Live HRIS data, validated by data scientists, with confidence shown per benchmark | Salary bands, pay equity analysis, compensation analysis | High-growth tech companies hiring across Europe and globally |
Pave | US and Canadian tech companies β 55+ countries, thinner outside North America | Live HRIS data, modelled where coverage is sparse | Salary bands, merit cycles, offer letters | US and Canadian tech startups and scale-ups |
Figures | European companies β base salary and variable pay only | HRIS data monthly, plus Mercer data quarterly | Salary bands, reviews, pay equity, EU pay transparency | European companies wanting benchmarks and pay transparency tools together |
Carta Total Comp | US private companies β strongest on equity | Cap table data, refreshed quarterly | Pay bands, offer letters, equity planning | US private companies already on Carta |
Compa | US enterprises in tech, life sciences, and retail | Live offer data from ATS, plus HRIS data | Offer workflows only | US enterprises adding live offer data to surveys |
OpenComp | US companies, including small businesses | Market data plus customers' own payroll data β limited public methodology detail | Pay ranges, merit cycles, pay equity, offer letters | US SMBs wanting an all-in-one tool with a free start |
Radford (Aon) | Large global enterprises, especially tech and life sciences | Employer surveys, typically annual and months old | None built in β consultancy available | Large enterprises needing board-level equity data |
Brightmine | UK companies only | Employer-reported, refreshed monthly | Pay grading for bands; pay equity as a separate product | UK-only benchmarking |
Payscale | Strongest in the US | Mix of survey, employer, and employee data β varies by source | Salary bands, pay equity, merit cycles | Enterprises wanting several sources in one platform |
CompAnalyst | Strongest in the US | Surveys, HRIS uploads, and job postings β varies by source | Salary bands, pay equity, increase modelling | Large US enterprises with complex job architectures |
Deel Global Salary Insights | 120+ countries free β base salary only | Deel's own payroll data, limited methodology detail | Bands and reviews in paid Deel Compensation | Companies already on Deel |
Playroll x Ravio | 40+ regions β base salary only | Ravio's live HRIS data, validated by data scientists | Cost-to-hire scenarios only | Pricing an international hire |
HiBob | Global via Mercer, weighted to large enterprises | Licensed Mercer survey data, unclear refresh timing | Basic tools within HiBob | HiBob customers wanting basic benchmarking |
Compensation IQ | UK and European public sector and nonprofits | Mercer surveys plus unverified job posting data | Dashboards β no salary bands or reviews | UK and European public sector and nonprofits |
HRDataHub | UK only | Advertised pay from job listings, updated daily | Trend reports only | Tracking UK advertised pay trends |
US tech companies | Advertised salary ranges, refreshed daily | Pay ranges and pay equity in the paid platform | A free daily check on US tech pay ranges | |
Juicebox | Candidate profiles, mainly North America | AI estimates, backed by Levels.fyi data | None β recruiting workflows only | Recruiters pricing candidates while sourcing |
Glassdoor | Global, broad roles, mostly base salary | Unverified submissions, all-time averages | None | A free directional sense-check |
US tech companies | Employee submissions, partly verified, updated daily | None β API on the enterprise tier | Big-tech pay and equity, company by company | |
Free salary checkers | Varies, mostly base salary | Recruiter placements and job postings, unverified | None | A quick sense-check before a hiring conversation |
Ravio is built for high-growth and tech companies hiring across the world, and for that profile it's difficult to match.Β
HRIS-integrated data validated by a human team, automated job mapping, full total rewards coverage across salary, equity, variable pay, and benefits, and built-in compensation tools β salary bands, pay equity analysis β all in one platform.
That said, no single tool is the right fit for every organisation.Β
Ravio is likely the strongest option if:
The best way to assess fit is to test the data directly. Ravio offers three free benchmarks for any role, level, and location β no commitment required.
| Ravio's salary benchmarking tool |
|---|---|
Up-to-date benchmarks | Yes β Real-time benchmarking data via HRIS integrations with 100+ systems. |
Accurate benchmarks | Yes β Data direct from HRIS source of truth. Internal verification by team of benchmarking experts. |
Robust data security measures | Yes β Enterprise grade security. SOC 2 Type 2 certification and GDPR policies in place. |
Relevant data pool | Yes β Global benchmarks using 618,000+ datapoints from 1,800+ companies. Currently strongest for European tech. |
Total rewards benchmarks | Yes β Benchmarks available for base salary, equity, variable pay, and benefits. |
Accurate job matching | Yes β Automated job mapping between Ravio job levels and your company's. |
Intuitive platform | Yes β G2 rating of 4.4 out of 5, with users regularly highlighting ease of use. |
Flexible user permissions | Yes β Ability to add users e.g. managers with bespoke permissions. Sharable total compensation reports for employees. |
Compensation tools | Yes β Compensation management features including salary bands review, pay equity analysis, and more. |
A salary benchmarking tool gives you data on market-typical pay for specific roles, levels, and locations β so you can make informed, competitive, and defensible pay decisions. Tools range from free salary calculators to purpose-built platforms with HRIS integrations, built-in compensation management, and total rewards data.
The best salary benchmarking tool meets your organisational needs. Typically this means integrating with your HRIS systems and offering real-time salary and total rewards data. It should also offer strong data coverage tailored to your needs, whether that's regional benchmarks or global market data, depending on your team's structure and hiring footprint.
For high-growth and tech companies Ravio is the strongest option. It pulls live data from 1,800+ companies via HRIS integrations, covers 50+ countries and 300+ roles, and includes total rewards benchmarks across salary, equity, variable pay, and benefits. Benchmarks are validated monthly by a team of data scientists, so you're working from data you can actually defend.
It ranges from free to tens of thousands of pounds a year. Several tools have free options: Pave's Market Data Lite is free for companies with 1-200 employees, Ravio offers three free benchmarks, the Playroll x Ravio tool is free for one-off cost-to-hire checks, OpenComp has a free version, Comprehensive.io publishes free US tech salary ranges, and Glassdoor and recruiter salary checkers are free to use. Among paid tools, Ravio starts at Β£5,400 a year for a 250-person company, Vendr estimates Payscale costs around $27,000 a year on average, and Compa starts at around $35,000 a year. Traditional survey providers like Radford rarely publish pricing.
Check how the tool collects and verifies data, and whether its coverage best fits your needs (regional vs global). Ensure it integrates with your HRIS system, is intuitive for team-wide adoption, and offers strong security standards β SOC 2 Type 2 certification and GDPR compliance for European data.
Start by checking whether the data actually covers your organisation β the roles, locations, and peer group you need. Then evaluate the data source and methodology to assess whether benchmarks are reliable enough to defend internally. Finally, consider whether the platform supports how you use benchmarks day-to-day β user permissions, compensation tools, and onboarding support all matter. Testing benchmarks before committing is the most reliable way to assess fit β Ravio offers three free benchmarks for any role, level, and location.
Not for decisions you need to defend. General AI tools like ChatGPT don't have access to verified compensation datasets, so they can't tell you where a figure came from or how current it is. They can help with tasks around benchmarking, like drafting job descriptions for matching. Read our guide to using AI tools for salary benchmarking.
Some do. Under the EU Pay Transparency Directive, employers need defensible pay structures and gender pay gap reporting. Tools that combine benchmarks with salary bands and pay equity analysis β like Ravio and Figures β support both. Survey-only providers and free tools don't.
For companies hiring across the UK and Europe, Ravio covers both with reliable HRIS-integrated benchmarks and filters by location, industry, and company stage. Brightmine and Croner Reward are other UK-focused providers, but both are traditional employer-reported salary surveys, which come with limitations of outdated data prone to human submission error.
Without reliable market data, compensation decisions become inconsistent β leading to overpaying, underpaying, pay equity issues, and difficulty retaining or attracting talent. Benchmarking gives you the foundation for fair, competitive, and defensible pay across your organisation.
Start by identifying the roles and locations you need data for, then choose a benchmarking tool that covers your peer group. Map your internal roles to the tool's framework to ensure like-for-like comparisons, set your target percentile in line with your compensation philosophy, and use the benchmarks to build or refresh salary bands. Revisit at least annually β or more frequently if you're in a fast-moving market.
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