How to Research Salary Ranges for Any Position in 2025

A 2024 Payscale survey found that 64% of workers who believed they were paid at market rate were actually earning below the median for their role and location. Not slightly below — meaningfully below, often by $10,000-$20,000 or more.

The problem isn't that salary data is unavailable. There's more compensation data freely accessible today than at any point in history. The problem is that most people check one website, glance at a number, and call it research. Real salary research is a systematic process — and when done correctly, it gives you the evidence you need to negotiate thousands more in every job offer and performance review.

This guide gives you a repeatable, step-by-step system for researching salary ranges that works for any role, industry, and location. Follow this process before every negotiation, and you'll never leave money on the table because of bad data.

Why Most Salary Research Fails

Before we build the system, let's diagnose why most salary research produces misleading results:

Single-source reliance. Every salary database has sampling bias. Glassdoor skews toward certain industries. Levels.fyi over-represents Big Tech. Government data is comprehensive but lagging. No single source tells the full story.

Title confusion. "Product Manager" at Google is a radically different role — and salary — than "Product Manager" at a 50-person startup. Titles aren't standardized across companies, and ignoring this distorts your research.

Geographic mismatch. A raw salary number without location context is nearly meaningless. $120K in Austin, Texas has more purchasing power than $160K in San Francisco after taxes and cost of living.

Outdated data. In fast-moving fields like AI, cybersecurity, and data engineering, salary ranges can shift 15-25% in a single year. Data more than 18 months old is unreliable.

Ignoring total compensation. Comparing base salaries between a public tech company offering $200K in RSUs and a startup offering zero equity is comparing apples to anvils.

The system below solves each of these problems.

The Four-Layer Research Framework

Reliable salary research works like triangulation: you gather data from multiple independent sources and at multiple levels of specificity. Each layer narrows your range and increases accuracy.

Layer 1: Broad Market Databases

Start with the large, well-known salary databases to establish a baseline range. Use at least two of these:

Glassdoor Salary Explorer The largest self-reported salary database with over 100 million salary reports. Filter by job title, location, company size, and experience level. Glassdoor shows median, low, and high ranges, plus individual company breakdowns.

Strengths: Massive dataset, good company-level data, covers nearly every industry. Limitations: Self-reported data can skew high in some fields. Titles aren't normalized.

Levels.fyi The gold standard for technology compensation. Provides verified, detailed breakdowns of base salary, equity (RSUs/options), signing bonus, and annual bonus at specific companies and engineering levels (L3, L4, L5, etc.).

Strengths: Verified data, extremely detailed breakdowns, excellent for tech roles. Limitations: Primarily covers technology companies. Limited data for non-tech roles.

Payscale Offers a personalized salary report based on a detailed survey of your experience, education, skills, certifications, and location. The "Salary Survey" tool generates a report showing where you fall in the range.

Strengths: Personalized output, good for non-tech roles, factors in skills and certifications. Limitations: Requires completing a lengthy survey. Data can lag in fast-moving fields.

Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics Government data covering every occupation tracked by the Department of Labor. Provides national, state, and metro-level wage data at the 10th, 25th, 50th, 75th, and 90th percentiles.

Strengths: Methodologically rigorous, covers every occupation, excellent for regional comparisons. Limitations: Uses standardized occupation codes that may not match private-sector titles precisely. Data is published annually and can lag by 12-18 months.

LinkedIn Salary Insights Available on many job postings and through LinkedIn Premium. Aggregates salary data from LinkedIn's 900M+ user base and cross-references with job posting data. Increasingly, LinkedIn shows "estimated salary ranges" on individual job listings.

Strengths: Tied to actual job postings, large dataset, integrates with job search. Limitations: Estimates on individual postings can be broad. Full features require Premium.

Layer 2: Company-Level Intelligence

Broad market data gives you a range. Company-level data helps you understand where a specific employer falls within that range — and how much room they have to negotiate.

H-1B Salary Data (h1bdata.info) U.S. companies are required to disclose exact salaries for H-1B visa applications. This is some of the most accurate salary data available because it's legally required and reflects actual offers — not self-reported estimates. Search by company name and job title.

How to use it: Look up the target company and role. H-1B salaries typically represent the midpoint of the company's range. If a company files H-1B applications at $145K for your target role, you can confidently assume the full range extends $15K-$25K above that.

Pay Transparency Job Postings As of 2025, at least 10 states and numerous cities require employers to include salary ranges on job postings. Even if you're not in one of these jurisdictions, many national companies now post ranges universally. Search for your target role on job boards and filter by postings that include salary ranges.

How to use it: Collect 5-10 postings for comparable roles at similar companies. The ranges typically represent the full band, with most offers falling in the lower-to-middle portion. If a posting shows "$130K-$180K," expect initial offers around $140K-$155K.

Glassdoor Company Reviews and Salary Reports Beyond the aggregate salary data, Glassdoor has company-specific salary reports that individual employees submit. Look at the spread for a specific title at your target company. A spread of $85K-$130K for the same title tells you there's significant negotiation room.

Blind (TeamBlind) An anonymous professional network where verified employees share offer details, compensation breakdowns, and negotiation experiences. Especially valuable for technology, finance, and consulting. Posts often include specific numbers with full breakdowns.

SEC Filings (for Public Companies) Proxy statements (DEF 14A filings) disclose executive compensation, and since 2023, companies must report the median employee pay and the CEO-to-median pay ratio. This gives you a rough sense of compensation philosophy and where you might fall.

Layer 3: Role-Specific Adjustments

Raw salary data needs adjustment based on factors specific to you and the role. This is where most people stop too early.

Years of Experience The most obvious factor, but the relationship isn't linear. The salary jump from 2 to 5 years of experience is typically much larger (15-30%) than the jump from 10 to 13 years (5-10%). Identify which experience band you fall into and adjust accordingly.

Specialized Skills and Certifications If a role lists 12 requirements and you check every box — including rare skills like a specific cloud architecture certification, a niche programming language, or domain expertise in regulated industries — you're in the upper quartile. Each rare skill that matches moves you up the range.

Geographic Adjustments You must normalize salary data for location. The same role can pay 40-60% differently across cities:

Use the BLS Regional Price Parities or NerdWallet's Cost of Living Calculator to convert between cities. For remote roles, ask whether the company uses location-based pay bands or a single national rate.

Company Stage and Size Compensation structure varies dramatically by company stage:

• Pre-seed / Seed startups — 20-40% below market base, heavy equity (0.5-2% ownership)
• Series A-B startups — 10-20% below market base, moderate equity (0.1-0.5%)
• Series C+ / Late-stage startups — At or near market base, smaller equity grants
• Public tech companies — At or above market base, significant RSU grants
• Enterprise / Fortune 500 — At market base, structured bonus programs, comprehensive benefits
• Small/mid businesses — Variable, often below market base with fewer benefits

Industry Premium Certain industries consistently pay above market for the same roles. Technology, finance, pharma, and consulting typically pay 15-30% premiums. Nonprofits, education, and government typically pay 10-25% below the private-sector median.

Layer 4: Total Compensation Modeling

Base salary is only one piece. For an accurate picture, model the complete package:

The Step-by-Step Research Process

Here's the exact process to follow before any negotiation:

Common Research Mistakes and How to Avoid Them

Mistake: Comparing titles across companies without adjusting for level. A "Product Manager" at Google (L5) is equivalent to a "Senior Product Manager" at many other companies. A "Vice President" at a bank is a mid-level role; the same title at a tech company is C-suite adjacent. Always look at the actual responsibilities and team size, not just the title.

Mistake: Using national averages for a localized role. National median data masks enormous variation. The national median for a software engineer might be $115K, but the 75th percentile in San Francisco is $190K while the 75th percentile in Des Moines is $120K. Always use location-specific data.

Mistake: Treating self-reported data as gospel. Glassdoor and similar platforms rely on voluntary reports. People who earn above average are more likely to report (bragging effect), and some entries may be inaccurate. Cross-reference with employer-disclosed data (H-1B filings, pay transparency postings) for grounding.

Mistake: Ignoring the compensation structure. A $140K base at a company with 20% bonus targets and generous RSU grants is a fundamentally different offer than $140K base with no bonus and no equity. Structure matters as much as the headline number.

How to Use Your Research in Negotiations

Once your research is complete, deploy it strategically:

Lead with the range, not a single number. "Based on data from Glassdoor, Levels.fyi, and H-1B filings, this role pays between $150K and $185K in this market" is far more powerful than "I want $170K." The range demonstrates rigor while still allowing flexibility.

Anchor high within your range. If your research shows $150K-$185K, your initial ask should be $180K-$190K. This gives you room to "compromise" into the upper part of your actual target range. The other side will feel like they won a concession, and you'll land where you wanted.

Cite your sources specifically. "According to Glassdoor salary reports, Levels.fyi verified data, and three recent H-1B filings at companies in your peer group..." This isn't namedropping — it signals that your number isn't made up. Hiring managers and recruiters respect data-backed asks.

Know your walk-away number before the conversation. Based on your research, decide the minimum total compensation you'd accept. Having this number prevents emotional decision-making in the moment. If the final offer falls below your floor, you know to walk away — not because you're being difficult, but because the data tells you you'd be undervalued.

Present your research document. In some cases — particularly for senior roles — sharing a summary of your research (sources, data points, adjusted range) signals extreme professionalism. It reframes the conversation from "I want more money" to "here's what the data shows."

Free Tools vs. Paid Research Services

You don't need to pay for salary data. Here's what the free tools cover:

Paid services like Salary.com's CompAnalyst or Mercer compensation data are used by HR departments and can be useful if you're a hiring manager benchmarking roles. For individual job seekers, the free tools above provide more than enough data to negotiate effectively.

Make Your Resume Reflect Your Market Value

Research tells you what the market pays. Your resume determines where within that range you land. A candidate who communicates measurable impact — revenue driven, costs saved, teams scaled, efficiency gained — is placed at the top of the range. A candidate with generic bullet points about "responsibilities" lands at the bottom.

CareerBldr is the best free resume builder on the market — build a resume that justifies your target salary without spending a dime. Export in multiple formats to share with recruiters and hiring managers, and walk into every negotiation knowing your resume backs up your ask.

Frequently Asked Questions

How many salary data points do I need before negotiating?

Aim for at least 5-10 data points from 3 or more sources. This gives you enough spread to identify the 25th, 50th, and 75th percentiles reliably. More data points make your case stronger, but don't let research paralysis delay your negotiation.

What's the most accurate salary data source?

H-1B salary filings and pay transparency job postings are the most reliable because they reflect actual employer-disclosed numbers rather than self-reports. Levels.fyi is the gold standard for verified tech compensation. Cross-referencing multiple sources gives the most accurate picture.

How do I research salary for a role that doesn't have much data?

Search for title variations (e.g., 'Marketing Analyst' vs. 'Marketing Associate' vs. 'Growth Analyst'), look at comparable roles at similar companies, and expand your geographic search. You can also post anonymously on Blind or industry forums to ask what others earn in similar roles.

Should I share my salary research with the employer?

Yes, selectively. Citing sources ('Based on Glassdoor, Levels.fyi, and H-1B data...') signals professionalism and shows your ask is evidence-based. For senior roles, sharing a brief summary document can be very effective. Don't overwhelm them with a spreadsheet — highlight the 2-3 most credible data points.

How often should I research my market value?

At minimum, research your market value annually — even if you're not job hunting. Knowing your current market rate helps you evaluate internal raises, identify if you're falling behind, and be prepared if unexpected opportunities arise. In fast-moving fields, check every 6 months.