Which salary websites are most accurate?

Accuracy depends on source, occupation definition, and geography — not on branding. Government-style occupation wages are usually more stable than self-reported samples. Job-ad scrapes reflect asking prices, not accepted pay. Use more than one source and prefer the one whose job definition matches your work.

Why is my offer so far from the published median?

Level mismatch, geo tier, variable pay, overtime, or a thin sample can all do it. Check whether you are comparing base to base. If you are far below p25 or above p75 for the stated seniority, ask whether the requisition’s level is wrong before you assume the market chart is wrong.

Are job-ad salary ranges reliable?

They tell you what the company is willing to advertise, which may be a legal range, a recruiting range, or a copy-paste from another geo. They are not a wage survey. Compare the posted range to local percentiles, then ask which level and geo the requisition is opened at.

Should I trust a modeled city salary on Pay by Role?

Trust it as a directional estimate: a real national median scaled by a pay index. Do not treat it as metro microdata. Prefer an observed city page when you have one. If modeled is all you have, confirm with another source or with HR before you make a hard negotiation from it.

How recent does salary data need to be?

Stable occupations can use last year’s survey; fast-moving specialties cannot. Our dataset typically refreshes monthly, but underlying programmes still lag. If your title is new or contractor rates have jumped, treat published bands as an anchor and add recent offer evidence.

When is it fair to ask HR for the salary band?

When pay is omitted, when the role could be two levels, or when your research puts you at a cliff. Ask for the budgeted base range for the level and geo, what it includes, and typical hire position in the band. In pay-transparency jurisdictions, employers may already be required to disclose a range — follow local law.

Can two honest sources disagree by a lot?

Yes. Different occupation codes, employee versus job-ad samples, and overtime inclusion can move a “median” substantially. Disagreement is a signal to triangulate, not to pick the number you like. Our coverage rule — no invented national medians — is one way we avoid adding a third fictional number.

Pay by Role editorial · Updated August 25, 2026 · 14 min read

When to trust salary data (and when not to)

A government occupation wage programme, a self-reported employee survey, a recruiter “market flash,” and a job-ad scraping product can all quote a “median” for the same title and disagree. That is not a glitch. Definitions, samples, and incentives differ.

This guide is when to trust salary data — including ours — and when to ask HR for the budgeted band instead of arguing with a chart. For how Pay by Role is built, read how we source salary data.

Why do published salary numbers disagree?

Not all published numbers are equal. Sample, occupation definitions, and incentives change the result. On Pay by Role we favour public statistical aggregations for country and city percentiles, label observed vs modeled city figures, and refuse to invent national medians when sources do not cover a pair.

That does not make every page equally strong — it makes the strength legible. Trust goes up when occupation, geography, and recency line up. Trust goes down when any of those are fuzzy.

What are red flags in job posts and recruiter ranges?

Wide postings without level or location often mean the band is undecided — or the company wants maximum applicant volume. Ask which level and geo tier apply.
Ranges far above local p90, or far below local p25, deserve a clarifying question. The title may be inflated or deflated relative to scope, or a national range may have been recycled for a cheaper location.
Commission-only, “uncapped OTE,” or equity-heavy posts should separate on-target earnings from base. Compare base to market base; treat OTE as a forecast that depends on territory, quota, and ramp.

How do survey bias and sample size distort “the market”?

Self-reported surveys over-represent people who changed jobs recently, work at large tech brands, or feel underpaid enough to look numbers up. They under-represent stable mid-career employees in smaller firms. That skew often pulls fashionable titles upward.

Small samples are noisy. A thin metro–occupation cell can swing when a few employers report overtime-heavy or partnership-track pay. Prefer large statistical programmes when you need a stable anchor; treat niche survey slices as colour, not gospel.

Definition drift matters as much as sample size. “Software engineer,” “data scientist,” and “product designer” mean different scopes across firms. If your day-to-day matches a neighbouring occupation better, benchmark that slug too and triangulate. Changing careers and pay covers peer occupations.

When should you trust observed vs modeled pages on this site?

Observed city pages use percentile sets returned for that metro and occupation. They are our strongest local estimates.

Modeled city pages start from a real national median and scale by the city’s pay index, then apply a spread model. They are useful for navigation and rough comparison, not metro microdata. If a modeled page is your only reference, widen your confidence interval before you negotiate hard.

Derived helpers — COL-adjusted pay, rent sketches, tax take-home, trend illustrations — should never be cited as if they were official statistics. They exist to help you ask better questions. See understanding pay and COL indexes.

When should you ask HR for the band — and what should you ask?

Ask for the band when the posting omits pay, when your research puts you near a cliff (below p25 or above p75), or when the role spans multiple levels. A fair question: “What is the budgeted base range for this level in [geo], and where do you typically hire within it?”

Ask how level and geo are determined, whether the range includes bonus or equity, and when compensation is reviewed. Those process answers often matter more than extracting a single number.

If HR cannot share a range, you can still share yours: cite a public percentile band for the city and role, state the total package you need, and invite them to say whether that is realistic before final rounds. Screening for fit early saves everyone time.

Key takeaways

Occupation match, geography match, and sample quality beat a flashy “median.”
Wide posts without level or geo are a process smell, not a market.
Self-reported surveys and thin cells need a wider confidence interval.
Observed city pages outrank modeled pay-index pages for local decisions.
Ask HR for the budgeted band when the posting is silent or the level is unclear.

Frequently asked questions

Which salary websites are most accurate?: Accuracy depends on source, occupation definition, and geography — not on branding. Government-style occupation wages are usually more stable than self-reported samples. Job-ad scrapes reflect asking prices, not accepted pay. Use more than one source and prefer the one whose job definition matches your work.
Why is my offer so far from the published median?: Level mismatch, geo tier, variable pay, overtime, or a thin sample can all do it. Check whether you are comparing base to base. If you are far below p25 or above p75 for the stated seniority, ask whether the requisition’s level is wrong before you assume the market chart is wrong.
Are job-ad salary ranges reliable?: They tell you what the company is willing to advertise, which may be a legal range, a recruiting range, or a copy-paste from another geo. They are not a wage survey. Compare the posted range to local percentiles, then ask which level and geo the requisition is opened at.
Should I trust a modeled city salary on Pay by Role?: Trust it as a directional estimate: a real national median scaled by a pay index. Do not treat it as metro microdata. Prefer an observed city page when you have one. If modeled is all you have, confirm with another source or with HR before you make a hard negotiation from it.
How recent does salary data need to be?: Stable occupations can use last year’s survey; fast-moving specialties cannot. Our dataset typically refreshes monthly, but underlying programmes still lag. If your title is new or contractor rates have jumped, treat published bands as an anchor and add recent offer evidence.
When is it fair to ask HR for the salary band?: When pay is omitted, when the role could be two levels, or when your research puts you at a cliff. Ask for the budgeted base range for the level and geo, what it includes, and typical hire position in the band. In pay-transparency jurisdictions, employers may already be required to disclose a range — follow local law.
Can two honest sources disagree by a lot?: Yes. Different occupation codes, employee versus job-ad samples, and overtime inclusion can move a “median” substantially. Disagreement is a signal to triangulate, not to pick the number you like. Our coverage rule — no invented national medians — is one way we avoid adding a third fictional number.

Next step

Salary data is a flashlight, not a verdict. Use observed local figures when you have them, widen the interval when you do not, and ask for the real band when the posting will not tell you.

See how Pay by Role sources and labels figures →

Then open an observed city page for your role, or read how to read a salary range.