Salary Data Methodology

How WhatIsTheSalary.com Researches, Calculates, and Presents Salary Data

Salary information is only useful if you can trust how it was put together. A number without context — or worse, a number built on a flawed process — can lead someone to accept a lowball offer, walk away from a fair one, or build career expectations around data that was never reliable to begin with.

This page explains exactly how we research, calculate, and present every salary figure published on WhatIsTheSalary.com. No vague claims. No “we use trusted sources” without explaining what that actually means. Just a transparent, step-by-step breakdown of our process.

Why Methodology Matters for Salary Data

Salary data falls into the YMYL (Your Money or Your Life) category — a classification used by Google’s quality rater guidelines to identify content that can meaningfully impact a person’s financial decisions, career trajectory, and livelihood.

We take that seriously. The way salary data is collected, interpreted, and presented determines whether it actually helps someone — or misleads them.

Our methodology is built around three principles: accuracy through multiple sources, clarity through structured ranges, and honesty about what the data can and cannot tell you.

Step 1 — Source Collection Across Multiple Platforms

Every salary page begins with data collection from a range of primary, publicly recognized sources. We never build a salary estimate from a single platform. The sources we pull from include:

• Bureau of Labor Statistics (BLS) — official U.S. government occupational wage and employment data
• Glassdoor — employer-reported and employee-reported compensation data across industries
• LinkedIn Salary Insights — role-specific compensation trends filtered by region, industry, and experience
• PayScale — skill-based and role-based compensation benchmarking data
• Indeed — real-time salary ranges drawn from active job listings and user-reported figures
• Government labor portals — official wage data from relevant national and regional labor authorities for non-U.S. coverage
• Niche professional communities and groups — real salary discussions from working professionals in specific fields and industries

Pulling from this range of sources gives us a broad data set to work with — and more importantly, it lets us identify where figures are consistent across platforms versus where significant variation exists and why.

Step 2 — Cross-Referencing and Discrepancy Analysis

Once data is collected, we compare figures across all sources side by side. This step is where the actual analytical work happens.

When sources broadly agree, that consensus forms the foundation of our range. When sources show significant variation, we investigate the reason — because salary discrepancies across platforms are usually explainable. Common reasons include differences in geographic coverage, sample size, recency of data, job title standardization, or industry segmentation.

We do not average out discrepancies blindly. If two sources show very different figures for the same role, we look at why before deciding how to represent that in our content. Where variation is significant and explainable, we reflect that in the page — including a clear explanation of what drives the difference.

Step 3 — Building the Low / Mid / High Range

Rather than publishing a single salary figure — which is almost always misleading — we present every role in a structured three-tier range. Here is how each tier is defined:

Low Range — Entry Level / Fresher This tier represents compensation for individuals just entering the field. This typically means zero to one year of experience, no significant prior work history in the role, and base-level qualifications with no advanced certifications or specializations.

Mid Range — 2 to 5 Years of Experience This tier covers professionals who have moved past the entry stage, have demonstrated competence in the role, and bring practical, applied experience. They may hold additional certifications or have developed specialized skills that push their value above the entry-level baseline.

High Range — Senior Level / 5+ Years of Experience This tier represents experienced professionals with deep domain knowledge, leadership or strategic responsibility, advanced specializations, or a track record of measurable performance. Senior-level compensation often reflects not just experience but impact — what the professional brings beyond just doing the job.

Secondary Factors That Can Shift Tiers

Experience level is the primary driver of the range in most cases — but it is not the only one. Depending on the role and industry, the following secondary factors can push compensation up or down within or across tiers:

• Geographic location — compensation for the same role can vary dramatically between cities, states, and countries due to cost of living, local demand, and regional labor market conditions
• Company size and type — enterprise organizations, funded startups, government bodies, and small businesses often pay very differently for identical roles
• Industry vertical — a software engineer in fintech typically earns more than the same engineer in a nonprofit, even at identical experience levels
• In-demand skills or certifications — specific technical skills, licenses, or credentials can push compensation well above the standard range for a given experience tier
• Remote vs. on-site — location-independent roles increasingly reflect the employer’s home market rather than the employee’s, which affects figures significantly

Where these secondary factors are relevant to a specific role, we include them directly on that page — not as footnotes, but as part of the main explanation.

Step 4 — Handling Location-Based Variations

WhatIsTheSalary.com covers salary data globally — across the United States, the United Kingdom, Canada, Australia, India, the Middle East, and other regions.

Location is one of the most significant variables in compensation. A marketing manager in New York, London, Dubai, and Bangalore will have very different salary expectations — not because the role is different, but because local labor markets, cost of living, currency, and economic conditions are different.

Here is how we handle location in our data:

Country-level coverage is the baseline. Every salary page starts with data relevant to the country or region being covered, sourced from platforms and government data specific to that geography.

City or region-level breakdowns are included where the data supports it and where location materially affects compensation. For roles where geographic variation within a country is significant — such as tech roles in the U.S. where San Francisco and Austin pay very differently — we break that down explicitly.

Currency and cost-of-living context is provided where relevant. A salary figure without currency context is meaningless for global readers, and a figure without cost-of-living context can be misleading. We include both where they add meaningful value to the reader.

Where our data for a specific location is limited or less reliable than our standard, we say so clearly rather than presenting thin data with false confidence.

Step 5 — Keeping Data Current

Salary data has a shelf life. Compensation shifts with inflation, labor market demand, industry cycles, economic conditions, and emerging skill requirements. Data that was accurate eighteen months ago may no longer reflect reality today.

Our update process works as follows:

Immediate corrections are made whenever a reader reports an inaccuracy, whenever we identify an error in our own review, or whenever a significant market development affects compensation for a covered role. Reported issues are reviewed and resolved within 24 hours.

Ongoing monitoring means we keep an eye on labor market trends, major compensation surveys, and industry reports that could affect the accuracy of existing pages. When updates are warranted, pages are revised and the “last updated” date is refreshed so readers always know how current the information is.

We do not leave outdated pages live without correction. Accuracy is not a one-time effort — it is an ongoing responsibility.

What Our Data Can and Cannot Tell You

We believe in being upfront about the limits of salary data, because understanding those limits helps you use the information more effectively.

Our data can tell you:

• What a role realistically pays across experience tiers in a given location or industry
• What factors most significantly affect compensation for a specific role
• How compensation for a role compares across regions, industries, or company types
• What the realistic range looks like for someone entering vs. growing vs. leading in a field

Our data cannot tell you:

• Exactly what a specific employer will offer you for a specific position
• What your personal compensation will be, given your unique combination of skills, background, and negotiation
• Real-time figures that reflect today’s job market to the day — salary data inherently lags the market to some degree

The figures on this website are reference points built from the best available data — not guarantees, not quotes, and not a substitute for direct conversations with employers or professional recruiters.

A Note on Data Transparency

If you are reading a salary page on this website and something does not look right — a figure seems too high, too low, or inconsistent with your experience in the field — we want to know.

Our methodology is only as strong as the feedback loop that helps us identify where it falls short. You can report any data concern directly to contact@whatisthesalary.com with the page URL and what specifically looks off. Every report is reviewed personally and responded to within 24 hours.

For a full explanation of our editorial standards and AI tool usage in research, see our Editorial Policy page.