Are You Paid Fairly? Use Our New Salary Benchmarking Tool

Wondering if you're paid fairly? Our new Role Compensation Benchmarking tool uses official USA and Singapore government data to help you analyze your salary, understand your market percentile, and prepare for your next negotiation.

Role Compensation Benchmarking Is Live for the USA and Singapore

If you’ve ever asked “Am I being paid fairly for my role?” you’re not alone. Compensation is often opaque, varies by location and industry, and changes quickly as markets shift.

That’s why we’ve launched R ole Compensation Benchmarking for the United States and Singapore—a guided analyzer that helps you:

Identify the closest market-match for your role
Compare your current pay to market percentiles
Understand the source of the benchmark data
Turn the result into practical next steps (negotiation, leveling, role changes, etc.)

This post explains what the tool does, how it works, what data it uses, and how to troubleshoot common issues—so you can get a clear answer quickly, then go deeper if you want the full detail.

What is Role Compensation Benchmarking?

Role Compensation Benchmarking is a structured workflow that compares your current compensation to the closest available market benchmark for your role, location, and industry.

Quick answer: What do I get out of it?

You’ll see:

A visual snapshot of where your pay sits vs. the market (e.g., percentile)
Key insights on what’s driving the benchmark match
Transparency on where the data came from
A deeper, generated analysis that’s useful for interviews and negotiation prep

Two compensation analyzers: which one should you use?

There are two compensation analyzers available:

Current Profile + Current Roles Analyzer (recommended for most people)

Designed for users who already have a profile loaded.
Found under Tools → Role Review.

Role-by-role / exploratory analysis

Useful if you want to compare multiple roles or run “what if” scenarios.

If you’re primarily trying to benchmark your current job and understand your current market position, start with the Tools → Role Review pathway.

How do I run compensation benchmarking for my role? (Step-by-step)

Below is the simplest workflow from start to finish.

1) Start from Tools → Role Review

Navigate to the Role Review area and open the compensation benchmarking analyzer.

2) Import your role from your profile, resume, or CV

As long as you already have a profile loaded, you can import your latest role.

This saves time and reduces manual entry—especially for:

Job title
Employer
Basic role context

3) Confirm your industry and location (this improves match quality)

After import, the analyzer will pre-fill your core details (role, title, employer). Next, you’ll refine the inputs that most affect market comparability:

Industry (e.g., Finance vs. Healthcare vs. Tech)
Location (country and, when available, region/metro context)

4) Enter your compensation (salary + package) for an apples-to-apples comparison

You can enter your:

Base salary
Total compensation / package components (where applicable)

The output is only as useful as the inputs—so add what you’re comfortable sharing to get the most accurate comparison.

5) Save to “lock in” your role + compensation details

Once you’ve entered the details, save the compensation information to lock in your role and current compensation.

This step matters because it allows the system to:

Finalize the role context
Look for the closest market match
Map to the most relevant classification codes

6) Run the compensation analysis (and refresh if needed)

After saving, you should be able to see the code mapping and then click Run compensation analysis to generate your results.

If the details don’t appear immediately, you may need to refresh the page.

What data sources does the benchmark use?

We built the USA and Singapore analyzers using public, reputable datasets so the source of truth is transparent and repeatable.

Singapore: SingStat + SSOC codes

For Singapore benchmarking, the analyzer uses:

SingStat (Singapore Department of Statistics) datasets
SSOC (Singapore Standard Occupational Classification) codes to match roles to official classifications

Why it matters:

SSOC code mapping helps translate your job title into a standardized category.
Standardized categories allow more reliable comparisons across employers.

United States: BLS occupational data

For USA benchmarking, the analyzer uses:

BLS (Bureau of Labor Statistics) occupational data

Why it matters:

BLS provides a consistent national baseline for compensation-like labor market distributions by occupation.
It can be especially helpful for grounded “sanity checks” when job boards and recruiter ranges disagree.

What happens after I run the analysis? (What you’ll see)

Once the analysis finishes, you’ll immediately see:

A visual indicator of where you stand vs. the market (e.g., percentile)
A short list of key insights
Details on exactly where the data came from
A more thorough, generated compensation + market analysis below

Singapore-only: what it can mean for CPF contributions

For Singapore-specific role analysis, you’ll also see how the compensation benchmark may relate to CPF contributions context.

Quick guide: how to interpret your percentile result

Use this as a practical rule of thumb:

25th percentile (or lower): Often signals “below market,” or a mismatch in role scope/industry/location inputs.
Around 50th percentile: Commonly interpreted as “market-aligned” for the matched benchmark group.
75th percentile (or higher): Often signals “strongly competitive,” though company-specific leveling, performance, and equity can still change the full picture.

If your result surprises you, rerun after adjusting the two inputs that typically matter most:

Industry (benchmarks can shift substantially across industries)
Location (especially when metro-level pay differs from national baselines)

Feature comparison: our benchmarking vs. traditional alternatives

Approach	What you typically get	Common gaps	How our Role Compensation Benchmarking differs
Job boards (self-reported ranges)	Wide salary ranges by title	Inconsistent titles, mixed seniority levels, weak location/industry controls	Uses structured role inputs + standardized code mapping for closer matches
Recruiter anecdotes	“Most candidates get X” estimates	Biased by recent deals, limited sample size, limited transparency	Grounds results in public datasets and shows the data provenance
Company comp bands (if you have them)	Clear internal ranges	Hard to access; may not translate across companies/industries	Helps you translate your role into market context for cross-company benchmarking
Manual spreadsheet benchmarking	Custom analysis	Time-consuming, error-prone, difficult to keep updated	Guided workflow: import role → confirm inputs → save → analyze → insights

Practical examples and use cases (how people use this)

Use case 1: “Am I underpaid for my role in my city?”

Import your current role
Select the correct location and industry
Enter base salary and key compensation details
Read your percentile result and insights
Use the generated analysis to prepare negotiation points

Use case 2: “I’m switching from Singapore to the USA—what changes?”

Run two analyses:

One using Singapore inputs (SingStat/SSOC)
One using USA inputs (BLS)

Then compare:

Where your current comp sits in each market
Whether your title maps to a different classification
Which skills/role scope differences may explain gaps

Use case 3: “I’m evaluating an offer—should I negotiate?”

Use your benchmark result to:

Validate whether the offer is near median, below median, or above median
Identify which components to negotiate (base vs. total package)
Create a fact-based negotiation narrative

Best practices for accurate compensation benchmarking

Be precise about your role scope. A “Manager” title can map to very different market benchmarks depending on responsibility level.
Pick the closest industry. Industry selection meaningfully changes comparability.
Don’t skip the save/lock step. It ensures the role + comp snapshot is stable for code matching.
Use the result as a baseline, not a verdict. Government datasets are great for neutral benchmarks, but company-specific leveling and equity can still vary significantly.
Rerun after adjustments. If the match feels wrong, adjust the role description, industry, and location first.

Troubleshooting: if results don’t look right

Issue: “I can’t see the details after running the analysis.”

Refresh the page once after running the analysis.
Confirm the role and compensation were saved before clicking “Run compensation analysis.”

Issue: “My role doesn’t match well / the benchmark seems unrelated.”

Double-check industry and location inputs.
Make the title and role description more specific (e.g., “Data Analyst (Healthcare)” vs. “Analyst”).
If multiple roles are imported, ensure you selected the correct one as the target role.

Issue: “The tool shows a code, but I don’t know what it means.”

That code is the standardized classification used for benchmarking:

Singapore: SSOC code mapping
USA: occupational categorization derived from BLS groupings

Use the code as a clue: if it’s mapping to the wrong occupation family, refine your role scope and rerun.

Issue: “I’m not sure what compensation numbers to enter.”

If you want the cleanest comparison:

Enter your base salary first
Add other components only if you can estimate them reliably (bonuses, allowances, etc.)
Avoid mixing one-time payments with recurring annual comp unless clearly labeled

Common Questions (FAQ)

What is compensation benchmarking?

Compensation benchmarking is the process of comparing your pay to a relevant market reference point—typically for a similar role, in a similar location, and ideally in a comparable industry.

How accurate is this for my exact company?

It’s best viewed as a market baseline. Company-specific pay can differ due to leveling frameworks, equity, performance cycles, and internal bands. The analyzer’s strength is helping you answer: “Where do I sit relative to a broadly comparable market group?”

Why do I need to pick an industry?

Because compensation for the same role title can vary widely by industry. Industry selection helps prevent misleading comparisons.

What if I work remotely?

Choose the location that best reflects how your compensation is set (e.g., where you are employed and taxed, or the compensation band your employer uses). If you’re unsure, run the analysis twice with two locations and compare.

Do I need to upload my resume?

Not necessarily. If you already have a profile, importing the latest role can be enough. A resume/CV can help if your profile is incomplete or out of date.

What should I do if I’m below the market median?

Common next steps include:

Clarifying scope and impact (to support a level/promo case)
Benchmarking multiple comparable roles (to confirm the match)
Preparing a negotiation narrative tied to market percentiles
Exploring role transitions that move you into higher-demand categories

Keywords and concepts this article covers (for quick scanning)

Role compensation benchmarking
Salary percentile comparison
Market rate for my job
USA compensation data (BLS)
Singapore compensation data (SingStat, SSOC)
Compensation analysis tool
Pay transparency and negotiation prep

Conclusion: make compensation decisions with clarity

Role Compensation Benchmarking is designed to make pay transparency practical: import your role, confirm the inputs that matter, lock in your compensation snapshot, and run the analysis to get a grounded market comparison.

If you’re negotiating, planning a move, or simply checking whether you’re aligned with your market, this gives you a fast answer up top—and deeper context when you want it.

Salary Market Data - Role Analyser