How to Research Your Real Market Rate Before Any Interview

How to Research Your Real Market Rate Before Any Interview

Finding your real market rate means triangulating at least two independent source types, adjusting for your specific location, company size and level, and cross-checking the result against real peer conversations — not copying a single number off one website.

Updated for 2026. Salary figures are indicative ranges and move quarterly — always cross-check against a current source before negotiating.

Most candidates walk into an interview with exactly one number in their head, usually the first figure a search engine handed them, unadjusted for anything specific to their actual situation. That single number is often wrong in a way that costs real money either direction.

A Real Research Methodology

Follow these steps in order — each one narrows a generic number into something specific enough to actually use in a negotiation.

Source Types and What Each One Is Actually Good For

Levels.fyi and similar crowdsourced platforms. Self-reported by individuals, strong for level-specific detail at large and well-known tech companies, especially in major hubs. Weak for smaller companies and less tech-dense regions, where fewer people submit data.

U.S. Bureau of Labor Statistics. Broad occupational categories, not company or level specific, but a genuinely independent, non-self-selected data source. Useful as a floor check against an inflated crowdsourced number, weak as a precise negotiating figure on its own.

Glassdoor and Indeed aggregates. Wider coverage across company size and geography than the crowdsourced platforms, mixing self-reported and modeled estimates. Useful for filling in gaps the other two sources miss, weaker on granularity for a specific internal level.

Direct peer conversations. The only source that tells you what actually got negotiated and how a leveling guide plays out in real practice — genuinely irreplaceable, but limited by how many people you can reasonably and respectfully ask.

No single one of these is sufficient alone. The research habit that actually works is using at least two, ideally three, and noting where they agree and where they diverge.

Adjusting for Location and Company Size — A Worked Example

Say a baseline search for a mid-level backend engineer returns a U.S.-wide range of roughly $110,000–$160,000 total compensation from a crowdsourced platform. Before treating that as your number, run it through two adjustments.

Location adjustment. If you're interviewing for a role based in a major coastal tech hub, the real range for that specific metro area is likely to sit toward or above the higher end of the national figure. If the role is in a lower cost-of-living region, or fully remote at a company with geography-based pay bands, the realistic range likely sits lower, sometimes by a meaningful margin.

Company size adjustment. A large, established public company offer at this level likely sits at the upper portion of the range, with a larger equity component. A smaller or earlier-stage company offer for the same title and years of experience often sits lower in base salary, with equity that carries materially more risk and uncertainty behind an equally large-looking headline number.

The output of this exercise isn't a single corrected number — it's a defensible range specific enough to actually anchor a real negotiation conversation, with a clear sense of which direction your specific situation should push it.

Building a Simple Personal Tracking Sheet

A useful habit that compounds over a career: keep a simple, private spreadsheet updated every time you gather new data, rather than re-researching from scratch each time you need a number.

Reviewing this sheet before any interview or annual review conversation takes minutes and replaces a from-scratch research session with a quick refresh — particularly valuable since compensation research, done properly across multiple sources, is genuinely time-consuming and easy to skip when rushed.

Reading Job Postings as a Direct Data Source

An underused research method: read actual job postings for your target role and level directly, not just aggregated compensation tools.

Since 2023, an increasing number of U.S. states and cities have required salary range disclosure directly in job postings for many employers. Where this applies, a real, current posted range for a specific company and role is often more reliable than a third-party estimate, because it comes straight from the employer rather than being inferred or self-reported by someone else. Collecting several real postings for comparable roles, even ones you're not applying to, builds a useful, current, first-party dataset alongside the aggregator-based research above.

What These Numbers Do Not Include

Your specific negotiating leverage. Market rate research tells you what's typical, not what you personally can extract in a given conversation — that depends on your track record, any competing offers, and how the conversation is handled.

Non-cash value. None of the source types above capture benefits quality, remote-work flexibility, or visa sponsorship terms, all of which meaningfully change whether a given number represents a genuinely good offer for your specific circumstances.

Real-time market shifts. Aggregated data lags actual market movement by weeks to months in normal conditions, and considerably more during a sudden hiring freeze or boom in a specific specialty.

Company-specific budget realities. A researched market range tells you what's typical across the industry — it doesn't tell you what a specific hiring manager's specific budget actually has room for on a specific requisition.

How to Approach a Peer Salary Conversation

Directly asking a peer what they earn feels awkward for most people, which is exactly why the research method above stays underused despite being genuinely valuable. A few practical habits make it easier.

Frame it as a two-way exchange, not a one-sided ask. Offering your own figure first, or explicitly stating you're comfortable sharing in return, lowers the barrier considerably compared to a cold, one-directional question.

Ask about the process, not just the number. "What was the negotiation like" or "did the leveling guide match reality" often produces more useful information than the raw figure alone, since it captures context a compensation aggregator cannot.

Respect a no without pressing. Some people are simply not comfortable discussing compensation, for entirely valid personal or cultural reasons, and pushing past a polite decline damages the relationship for no research benefit.

Prioritize peers at your target company or a close comparable, not just any peer. A friend's compensation at an unrelated industry or company size tells you less than a peer at a genuinely similar role, level, and company profile.

The Five Mistakes

1. Anchoring to a single unadjusted number. The first figure a search returns is rarely adjusted for your specific location, company size, or level — treat it as a starting point, not a conclusion.

2. Skipping the location adjustment entirely. A national or blended average can be meaningfully off from what's actually available in your specific market.

3. Never talking to a real peer. Aggregated data misses the texture of what actually got negotiated and what a leveling guide means in day-to-day practice — a resource most candidates underuse simply because the conversation feels awkward to initiate.

4. Letting research go stale. A market-rate figure from eighteen months ago in a fast-moving specialty can be meaningfully out of date — recheck roughly every six months to a year.

5. Comparing a startup offer directly against a big-company benchmark. Different risk profiles behind similarly-sized headline numbers make this an apples-to-oranges comparison unless explicitly adjusted for.

Researching Market Rate for a Specialty With Thin Public Data

Some roles and specialties, particularly newer or narrower ones, simply don't have much crowdsourced data yet on platforms like Levels.fyi, which means the standard methodology above needs adapting.

Widen the comparison to adjacent, better-documented roles. If your specific specialty has thin data, find the closest well-documented adjacent role and adjust from there, explicitly noting the adjustment you're making and why, rather than presenting an adjacent number as if it were a direct match.

Weight peer conversations more heavily. In a thin-data specialty, direct conversations with a handful of people doing genuinely similar work often carry more real signal than sparse or unreliable aggregated data, simply because there isn't much aggregated data to begin with.

Read job postings directly, even more than usual. Where legally required salary disclosures apply, real postings for your specific specialty are often the single best source available when general aggregators haven't caught up to a newer role category yet.

Be explicit with recruiters about the data gap. It's reasonable to tell a recruiter directly, "there isn't much public compensation data for this specific specialty yet, so I'd like to understand your internal band for this role" — a legitimate ask given the genuine data scarcity, not an admission of weakness in your position.

Common Signs Your Research Might Be Out of Date

A few practical signals suggest it's time to refresh your numbers rather than trust an existing figure.

The figure is older than a year. Even in a stable market, a year-old number has likely drifted from current reality by an amount worth rechecking before using it in a real conversation.

Your specialty has seen recent, visible hiring-demand shifts. A sudden wave of layoffs or a sudden hiring surge in your specific area of tech is one of the clearest signals that last year's number no longer reflects the current market.

You've changed level, scope, or location since you last researched. A number gathered for your previous level or a different city doesn't automatically transfer to your current situation — treat a material change in any of these as a trigger to re-research, not just a routine annual check.

You're about to enter a real negotiation. Regardless of how recently you last checked, a final refresh immediately before a real offer conversation or annual review is worth the small time investment, given how much is riding on the number being current.

Researching Market Rate for a Career Transition

The methodology shifts slightly when you're researching a move into a new specialty or role type rather than benchmarking your existing one, since there's no direct personal baseline to anchor from.

Research the destination role's market rate independent of your current pay. It's tempting to anchor a transition's expected pay to a percentage of your current salary, but the more accurate approach benchmarks the destination role and level on its own terms, since a transition often resets your effective level in the new specialty, sometimes below where you sat in your prior one.

Expect a temporary step sideways or down in some transitions, and plan for it explicitly. Someone moving from a general backend engineering role into a specialized area with a steep learning curve may take a real-terms pay cut for a year or two while building credibility in the new specialty, before the higher long-term ceiling (if the specialty genuinely has one, verified against real hiring data) becomes accessible.

Weight peer conversations with people who've made the same transition especially heavily. Someone who has personally navigated the same career pivot can tell you not just the destination pay range, but the realistic timeline and any pay dip involved along the way — information a generic compensation aggregator simply doesn't capture, since it isn't built to track career-transition trajectories.

Recheck your research more frequently during an active transition. A market you're actively entering, rather than one you're already established in, can shift meaningfully within a single year, particularly for newer or fast-growing specialties — a six-month re-check cadence is more appropriate here than the standard annual check for an established role.

Using Market Rate Research to Evaluate a Whole Offer, Not Just Base Salary

Market rate research is most often framed as a base-salary exercise, but the same discipline applies to every negotiable component of a full offer, and skipping this wider view leaves real value unexamined.

Bonus targets vary by company culture, not just role. Some companies structure a smaller base with a larger, more variable bonus target; others do the reverse. Comparing only base salary across two offers with very different bonus structures can produce a misleading read of which is actually more generous, especially once you factor in how reliably each company's bonus has historically paid out near its stated target.

Benefits carry real, calculable dollar value that's easy to skip past. Health insurance quality, retirement matching, and paid time off policy differ meaningfully between companies and, in aggregate, can represent a meaningful fraction of total compensation once priced out — worth doing the arithmetic on rather than assuming benefits are roughly equivalent everywhere.

Remote and hybrid policy affects your effective, after-cost compensation. A fully remote role in a lower cost-of-living area can leave more real disposable income than a nominally higher-paying role requiring relocation to an expensive metro area — a calculation worth running explicitly rather than comparing gross figures alone.

Researching all of these components with the same rigor as base salary — checking multiple source types, adjusting for your specific situation, and talking to peers where possible — produces a genuinely complete picture of an offer's real value, rather than a partial one anchored to the single most visible number on the offer letter.

🔗 Once you have a real, adjusted range in hand, the next step is putting it into words during the actual conversation — see The Salary Negotiation Script, Line by Line, or explore the full landscape at the pillar — Tech Salaries Ranked.