How to Research Salaries Effectively: A Complete Guide

RK

Written by Robert Kim, CCP

Compensation Analyst | Former BLS Economist

Last updated: March 2026 | 16 min read

Knowing your market value is essential for career success. Whether you're negotiating a raise, evaluating a job offer, or planning a career move, accurate salary research gives you the leverage to maximize your earnings. This guide teaches you how to research salaries like a compensation professional, using the same sources and methods that HR departments rely on.

Why Salary Research Matters

  • $7,500/year - Average raise achieved through effective negotiation
  • 70% of employers expect candidates to negotiate
  • $600,000+ - Lifetime earnings impact of salary research
  • 85% success rate when negotiating with data

Best Data Sources for Salary Research

Not all salary data is created equal. The most effective salary research combines multiple sources to triangulate your true market value. Here are the best sources, ranked by reliability and usefulness.

1. Bureau of Labor Statistics (BLS)

Occupational Employment and Wage Statistics (OEWS)

Government survey data - Most comprehensive source

RECOMMENDED

Strengths

  • + Surveys 1.2 million establishments
  • + 800+ occupations covered
  • + Metro-level geographic detail
  • + Percentile breakdowns (10th-90th)
  • + No self-reporting bias

Limitations

  • - 18-month data lag
  • - Doesn't break down by experience
  • - Base salary only (no total comp)
  • - Broad occupation categories

Best for: Establishing baseline market rates, understanding geographic pay differences, and getting unbiased percentile data. Use our salary database to easily access BLS data by occupation and location.

2. Glassdoor

Glassdoor Salary Data

Self-reported salaries by company

COMPANY-SPECIFIC

Strengths

  • + Company-specific salary ranges
  • + Includes bonuses and total comp
  • + Job title granularity
  • + More current than BLS
  • + Employee reviews for context

Limitations

  • - Self-reported (potential bias)
  • - Limited sample sizes at some companies
  • - Requires account to access
  • - Data quality varies by company

Best for: Researching specific companies, understanding company-specific comp structures, and preparing for negotiations at known employers.

3. Levels.fyi

Levels.fyi

Tech industry total compensation data

TECH FOCUS

Strengths

  • + Detailed total compensation
  • + Level/seniority breakdowns
  • + Verified data from offer letters
  • + Excellent for tech companies
  • + Stock compensation details

Limitations

  • - Tech industry focused
  • - Skews toward large companies
  • - Limited non-tech coverage
  • - May represent top performers

Best for: Tech workers researching FAANG and similar companies, understanding level-based compensation, and comparing total comp packages.

4. LinkedIn Salary Insights

LinkedIn Salary

Professional network salary data

BROAD COVERAGE

Strengths

  • + Large sample size
  • + Spans many industries
  • + Experience level filters
  • + Integrates with job postings

Limitations

  • - Requires LinkedIn account
  • - Limited free access
  • - Self-reported data
  • - US-focused

Best for: Quick salary estimates across industries, understanding how experience affects pay, and filtering by skills and education.

5. Job Postings with Salary Ranges

Job Posting Analysis

Real-time market demand signals

REAL-TIME

Many states now require salary ranges in job postings (Colorado, California, New York, Washington, and others). These represent what employers are actually willing to pay right now.

Strengths

  • + Current market rates
  • + Employer-verified ranges
  • + Role-specific requirements
  • + Company-specific data

Limitations

  • - Wide ranges (sometimes meaningless)
  • - Not all states require disclosure
  • - Time-intensive to collect
  • - May represent low-ball offers

Best for: Understanding current market demand, company-specific ranges, and validating other data sources.

Understanding Salary Ranges

Salary data is typically presented as ranges or percentiles. Understanding what these numbers mean helps you target the right compensation level.

Salary Percentiles Explained

10th %
Entry Level
Bottom 10% of earners
25th %
Early Career
1-3 years experience
50th %
Median
Middle earner (most useful)
75th %
Experienced
Above average performer
90th %
Top Earner
Top 10%, senior/specialist

Pro tip: For most workers, target the 50th-75th percentile based on your experience level. The 90th percentile typically requires specialized skills, senior titles, or high-paying metros.

Median vs. Average: Which Matters?

Median (50th Percentile)

The middle value: 50% earn more, 50% earn less.

Example: 9 people earn $50K, 1 earns $500K

Median = $50,000

Better for salary research because it's not skewed by outliers.

Mean (Average)

Sum of all salaries divided by count.

Same example: Sum = $950K / 10 people

Mean = $95,000

Can be misleading when high earners skew the data.

When to use average: Mean salary can be useful when evaluating total compensation at tech companies where large equity grants create significant upside. The average may better capture potential earnings.

Location Adjustments

Salaries vary dramatically by location. A software developer in San Francisco might earn $180,000 while the same role in Dallas pays $120,000. However, cost of living differences mean the Dallas salary may provide better purchasing power.

Cost of Living Adjusted Salaries

Metro AreaTypical SalaryCOL IndexAdjusted Value
San Francisco, CA$150,000180$83,333
New York, NY$140,000170$82,353
Seattle, WA$145,000158$91,772
Denver, CO$120,000128$93,750
Austin, TX$115,000105$109,524
Dallas, TX$105,00096$109,375

Adjusted Value = Salary / (COL Index / 100). Index of 100 = national average. Source: BLS Consumer Price Index, C2ER Cost of Living Index.

Key insight: Despite lower nominal salaries, Austin and Dallas provide better purchasing power than San Francisco or New York when adjusted for cost of living.

Experience Level Impact

Experience is one of the strongest predictors of salary. Understanding typical progression helps you benchmark yourself accurately and project future earnings.

Typical Salary Progression by Experience

Entry Level (0-2 years)

10th-25th percentile

Fresh graduates and early career professionals. Learning the role, building foundational skills. Salary typically 20-30% below median.

Early Career (3-5 years)

25th-50th percentile

Proven competence, handling responsibilities independently. May begin mentoring junior staff. Approaching or reaching median salary.

Mid-Career (5-10 years)

50th-75th percentile

Subject matter expertise established. Leading projects or small teams. Often holds senior individual contributor or management title.

Senior/Expert (10+ years)

75th-90th percentile

Deep expertise, strategic impact, leadership responsibilities. May include director-level titles, specialized technical roles, or thought leadership positions.

Industry Variations

The same role can pay vastly different amounts depending on industry. Understanding industry pay scales helps you identify where your skills are most valued.

Industry Pay Premium Examples

Same role, different industries (indexed to 100 = average across all industries)

Finance / Investment Banking135
Technology / Software130
Pharmaceutical / Biotech125
Consulting120
Manufacturing100
Retail85
Non-Profit / Education80

Benefits Valuation

Base salary is only part of the picture. Benefits can add 20-40% to total compensation value. When comparing offers or evaluating your current package, include these components.

Typical Benefits Value

Health Insurance (Employer Contribution)

Family coverage, employer typically pays 70-85%

$8,000-$20,000/yr
401(k) Match

Common: 50% match up to 6% = 3% of salary

$3,000-$10,000/yr
Paid Time Off (PTO)

15-25 days = 6-10% of salary value

$5,000-$15,000/yr
Bonus / Commission

Varies widely: 5-30% target

Variable
Stock / Equity (Tech companies)

RSUs, options - can be 20-50% of comp

Variable

Total Compensation Example

Base Salary

$100,000

Health Insurance

$12,000

401(k) Match (4%)

$4,000

Target Bonus (10%)

$10,000

Total Compensation

$126,000 (26% above base)

Total Compensation Picture

Understanding total compensation helps you make better career decisions. Here's how to calculate and compare complete packages.

Total Compensation Calculation Worksheet

1. Base Salary

Annual gross pay before taxes

$_______

2. Target Bonus

Expected bonus at 100% achievement

+ $_______

3. Equity/Stock (Annual)

RSUs/options value / vesting years

+ $_______

4. Health Insurance Value

Employer contribution (ask HR)

+ $_______

5. Retirement Match

401(k) match (assume you max it)

+ $_______

6. Other Perks

Tuition, wellness, commuter benefits

+ $_______

TOTAL COMPENSATION

Sum of items 1-6

= $_______

Putting It All Together: Research Process

5-Step Salary Research Process

1

Start with BLS Data

Use our salary database to find median salaries and percentile ranges for your occupation and metro area. This establishes an unbiased baseline.

2

Cross-Reference with Glassdoor/LinkedIn

Check self-reported data for your specific companies of interest. Note that these skew higher (happy employees are more likely to report) but provide company-specific insight.

3

Analyze Job Postings

Review 10-20 current job postings with salary ranges. Focus on roles matching your experience level. This shows what employers are actually offering right now.

4

Adjust for Your Factors

Factor in your experience level (percentile), specific location (COL adjustment), industry sector (premium/discount), and unique skills or certifications.

5

Calculate Your Target Range

Synthesize your research into a target range. Your ask should be at the high end; your walk-away point at the low end. Add 10-15% negotiating room to your target.

Frequently Asked Questions

How often is BLS salary data updated?

BLS releases new OEWS data annually, typically in April, based on surveys from the prior year. So 2026 data reflects surveys conducted in 2025. This 18-month lag is normal; supplement with current job postings for the most accurate picture.

Why do salary websites show different numbers?

Different sources use different methodologies. BLS surveys employers; Glassdoor and LinkedIn rely on self-reported data. Self-reported data often skews high because satisfied, well-paid employees are more likely to share. Job postings may show wide ranges or low-ball starting points. Use multiple sources and triangulate.

How do I research salaries for a new role I've never held?

Start by identifying the job title used in your target industry (job titles vary across companies). Research entry-level ranges since you'll likely start at the lower percentiles. Factor in any transferable skills that might justify higher positioning. Conduct informational interviews with people in the role for real-world insight.

Should I share my salary research in negotiations?

Yes, citing data sources strengthens your position. Saying "Based on BLS data and current market rates, the median salary for this role in our metro is $X, and given my Y years of experience, I'm targeting $Z" is more compelling than simply asking for more money. Data-backed requests have 85% higher success rates.

Key Takeaways

  • Use multiple sources. BLS for baseline, Glassdoor for company data, job postings for current market.
  • Focus on median, not average. Median is more representative and less skewed by outliers.
  • Adjust for location. Cost of living dramatically affects real salary value.
  • Calculate total compensation. Benefits add 20-40% to base salary value.
  • Target 50th-75th percentile. Based on your experience level, with room to negotiate.

Start Your Salary Research

Explore salary data for 80+ occupations across 50 US metro areas. All data sourced from official Bureau of Labor Statistics surveys.

Data Sources & Methodology

Salary research methodologies based on Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) program documentation. Negotiation success statistics from Harvard Business Review and SHRM research. Cost of living data from BLS Consumer Price Index and C2ER Cost of Living Index. Benefits valuation based on Kaiser Family Foundation employer health benefits survey and BLS Employee Benefits Survey.

RK

About the Author

Robert Kim, CCP is a certified compensation professional with 12 years of experience in compensation analysis. He previously worked as an economist at the Bureau of Labor Statistics contributing to the OEWS program. Robert holds a Master's in Economics from Georgetown University and consults with Fortune 500 companies on compensation strategy.