WageDex guide
Using Salary Data for Negotiation
How to turn BLS wage data into a stronger negotiating position.
The short answer
Government wage data is the most credible number you can cite in a negotiation: employer-reported, statistically designed, and publicly verifiable. For Software Developers, pay runs from $82,460 at the 10th percentile to $214,670 at the 90th, so an experienced candidate should anchor to the 75th percentile ($171,980), not the median.
- $135,980
- Median (50th)
- $171,980
- Experienced anchor (75th)
- $214,670
- Top of band (90th)
Establish the range with percentile data, then position yourself within it based on experience, skills, and local cost of living.
Why BLS Data Is Your Best Negotiation Tool
Most salary negotiation advice focuses on tactics, when to pause, how to frame a counter. But the foundation of any good negotiation is data. BLS wage data gives you three advantages over self-reported salary sites:
- Credibility: It's federal government data, not a startup's marketing tool. No employer can dismiss BLS statistics as unreliable.
- Percentile ranges: Instead of a single "average salary" that means nothing, you get the full distribution, 10th through 90th percentile, so you can position yourself appropriately.
- Geographic precision: Data is available by metro area, so you're comparing against your actual labor market, not a national average.
The negotiation ladder: Software Developers
National pay at each percentile, anchor to the 75th, not the median, when you have experience
- 10th (entry) $82,460
10th percentile
$82,460 annual wage
- 25th
25th percentile
$105,210 annual wage
- 50th (median)
Median
$135,980 annual wage
- 75th
75th percentile
$171,980 annual wage
- 90th (top)
90th percentile
$214,670 annual wage
Step 1: Research Your Occupation
Start by finding your occupation on WageDex. The BLS uses the Standard Occupational Classification (SOC) system, which may categorize your job differently than your company's title. A "Growth Hacker" at a startup is likely classified as "Market Research Analysts and Marketing Specialists" (SOC 13-1161). Search WageDex by your actual job function, not your company-specific title.
Look at the full percentile distribution nationally, then narrow to your state or metro area. The metro-level data is most relevant because that's your actual labor market.
Step 2: Establish Your Target Range
Based on BLS percentiles, determine a realistic range for your experience level:
- 0-2 years experience: Target the 25th-50th percentile. You bring enthusiasm and current knowledge but limited track record.
- 3-7 years: Target the 50th-75th percentile. You have demonstrated competence and some specialization.
- 8+ years or specialized skills: Target the 75th-90th percentile. You bring deep expertise that commands a premium.
Use the comparison tool to see how your occupation's wages compare to related roles, this helps if you're transitioning between occupations.
Step 3: Frame the Conversation
When presenting data in a negotiation, frame it as market research, not a demand:
- Do say: "Based on BLS data for [occupation] in the [metro] area, the median salary is $X and the 75th percentile is $Y. Given my [specific experience/skills], I believe a salary in the $Z range reflects the market."
- Don't say: "The government says you should pay me $X" or "I know I'm worth $X because the BLS says so."
The goal is to establish an objective baseline, then build your case on top of it with specific contributions and qualifications.
Step 4: Adjust for Total Compensation
BLS data covers wages only. Factor in the full compensation picture: health insurance (employer contribution), retirement matching, equity/stock options, bonuses, signing bonus, paid time off, remote work flexibility, and professional development budgets. A salary at the 50th percentile with a 10% bonus and 6% 401k match may be worth more than a 75th percentile salary with no bonus and no match.
Use the salary calculator on WageDex to see how wages adjust for cost of living across different metros.
Frequently Asked Questions
When should I bring up salary data in a negotiation?
After receiving an offer, not before. Sharing salary expectations too early anchors the negotiation. Once you have an offer, you can reference BLS data to support a counter: "Based on BLS data, the 75th percentile for this role in this metro is $X, and given my experience, I believe that range is appropriate."
Which percentile should I target?
It depends on your experience and leverage. Entry-level candidates should expect the 25th-50th percentile range. Mid-career professionals with relevant experience should target the 50th-75th percentile. Senior experts or candidates with rare skills can justify the 75th-90th percentile. Having a competing offer strengthens your position at any level.
Should I use national or local salary data?
Always use local data (state or metro level) when negotiating. National figures include both high and low cost-of-living areas. If you are in San Francisco, citing the national median underpays you. If you are in a rural area, the national median may overstate local market rates. WageDex shows wages by metro area for exactly this purpose.
How do I account for benefits in salary comparison?
BLS data covers wages only, not total compensation. When comparing offers, estimate the value of benefits: health insurance ($5,000-$20,000/year for employer contribution), retirement matching (typically 3-6% of salary), stock options, bonuses, and paid time off. A lower salary with excellent benefits may be worth more than a higher salary with minimal benefits.
Can I use BLS data in a current-job raise discussion?
Yes. Frame it as market data, not a demand: "I've been researching market rates for my role and experience level. BLS data shows the median in our metro is $X, and I am currently below that. I'd like to discuss aligning my compensation with the market." Support it with your contributions and performance.
What if the employer says BLS data doesn't apply to them?
BLS data covers industry averages, not specific companies. Employers may legitimately pay above or below market for various reasons (startup equity, nonprofit mission, premium benefits). Acknowledge this, but note that significant deviation from BLS benchmarks should be justified by other compensation elements. If the total package still falls short, that is useful information for your decision.
The Bureau of Labor Statistics OEWS survey, current as of May 2025, is the source: WageDex tracks 831 occupations across 582 U.S. states and metro areas, comprising 36,367 state-level wage records, according to the same federal survey.
Sources
- U.S. Bureau of Labor Statistics, OEWS, May 2025
- BLS, Employer Costs for Employee Compensation (ECEC)
This content is for informational purposes only and does not constitute financial advice.
Understanding the Data
The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.
It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.
For readers who want to conduct their own research, we recommend going directly to the source whenever possible. the U.S. Bureau of Labor Statistics provides detailed documentation on the OEWS survey's collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.
How We Analyze Data Records
Our pipeline pulls the raw OEWS release, standardizes occupation and area names against a fixed taxonomy so the same job title matches across editions, and computes derived figures (percentile bands, metro-vs-national ratios, year-over-year change) that BLS publishes as separate files but most readers want to see side by side.
The metrics we track for every occupation include median and mean annual wage, employment counts, and percentile wage bands (10th through 90th percentile). These figures let you see not just what an occupation pays nationally, but how that compares across metro areas, states, and neighboring occupations, since a single national average can hide wide regional and role-level variation.