How to Research Your Salary

The tools and methods to find reliable market data on what your role should pay — before a negotiation, a review, or a job search.

Salary research is the process of gathering market data on what a given role, at a given level, in a given location, pays at comparable companies — so you can negotiate from facts rather than assumptions or hope. The difference between candidates who negotiate salary effectively and those who don't is almost never confidence or personality; it's access to specific, credible data. A candidate who says 'market data shows this role at this level in this city ranges from $130K–160K and I'm targeting the upper half' negotiates from a position of strength. A candidate who says 'I was hoping for more' negotiates from a position of weakness.

Salary data comes from several sources with different strengths and limitations. Crowdsourced platforms — Glassdoor, Levels.fyi (tech-specific), LinkedIn Salary, Payscale, and Blind — aggregate self-reported data and are best used for directional ranges rather than precise benchmarks, because self-reporting bias skews numbers (top earners are more likely to report). Government data from the Bureau of Labor Statistics provides reliable median figures across broad occupational categories but lags current market by 1–2 years and lacks the granularity of tech vs. traditional industry. Recruiter and hiring manager conversations — asking 'what's the range for this role?' during a phone screen — are often the most current and role-specific data points available.

The most important context variables in salary research are: exact job title and level (a 'senior engineer' at a FAANG company and a 'senior engineer' at a regional bank have very different comp), company size and stage (public large-cap tech pays at a different scale than Series A startups), location (San Francisco and Austin may differ by 30–50% for the same role), and total compensation vs. base (many technology roles have substantial equity and bonus components that make base-only comparisons misleading). Research should always define these variables before drawing conclusions from any data source.

Best Data Sources by Role Type

  • Tech (software, data, product, design): Levels.fyi is the gold standard for total compensation data including equity, especially at public tech companies. Blind for senior roles at major companies.
  • All roles: LinkedIn Salary is broad and useful for directional context across industries and geographies. Search by job title + location.
  • Corporate/business roles: Glassdoor, Payscale, and compensation.bestcompaniesgroup.com. Look at multiple sources and average the ranges.
  • Finance and consulting: Mercer, Robert Half annual salary guides, and Wall Street Oasis (for finance-specific roles).
  • Government and nonprofit: USAJobs.gov for federal roles (salaries are public); IRS 990 filings for senior nonprofit salaries.
  • Ask recruiters directly: 'What's the budgeted range for this role?' is a legitimate question on a first call. Recruiters who won't share a range are a signal worth noting.

How to Use Salary Data in a Negotiation

Salary data is most powerful when it's specific, credible, and cited. 'Levels.fyi shows that senior product engineers at companies of similar size and stage in this city have total compensation ranging from $220K–$280K. Based on my experience and the scope of this role, I'm targeting $260K' is a negotiation opening. 'I think I deserve more' is not. The goal is to anchor the conversation to market reality rather than to what either party is hoping for. When citing data, stick to sources the other party will recognize as credible — Glassdoor and Levels.fyi are widely accepted. Avoid citing single data points as if they were ranges, and avoid using outlier numbers as if they were typical. The aim is to be seen as informed and reasonable, not to win a debate.

Example

Before negotiating a senior data scientist offer, a candidate spends 45 minutes researching: LinkedIn Salary shows $130–175K for the title and city; Levels.fyi shows total comp (including equity) ranging from $180–240K at similar-stage companies; and a recruiter friend at a comparable company confirms base is typically $145–165K for this level. Armed with specific sources and ranges, she counters the initial $138K offer with $158K citing these benchmarks — and receives $152K plus a $10K sign-on.