Live Job Ads
Scanning live online job ads from a variety of sources that contain salary information and related benefits.
Methodology
Triangulation,
not estimation.
The truth is always somewhere in the middle. We capture real-time data from a variety of online sources to create the most robust and accurate salary benchmark report.
Why triangulation
One source is a guess. Triangulation is a benchmark.
Every salary source has blind spots. Job ads only show what employers are willing to advertise. Salary guides reflect what consultants think the market should pay. Public databases lag the labour market by months. Lean on any one of them in isolation and you're getting a partial view of a moving target.
EvenBetter benchmarks every role across five categories of data in parallel — live job ads, anonymised historical offers, AI research, salary guides, and public databases. Each source has its bias; combined, they cancel each other out. The truth emerges from the overlap.
We clean the data before we triangulate — removing duplicate listings, converting hourly rates to annual figures, excluding foreign-currency outliers, and trimming extremes that would skew the median. Every number on every report links back to where it came from.
Data Sources
Where every figure comes from
Visible
Historical Offers
Anonymised data captured by EvenBetter as users run salary benchmarking reports.
AI Research
Running salary queries across a variety of AI platforms.
Salary Guides
Triangulated salary information across publicly available salary reports and industry research.
Public Databases
Publicly available salary information from industry bodies and government surveys.
Confidence
Built bottom-up from quality and quantity.
We collect salary information from online sources, industry bodies, and surveys. Before any number reaches your report it passes through two scoring layers that decide how much weight it carries.
Step 1
Quality Score
Every individual data point is given a Quality Score based on relevance, recency, and trust level.
Step 2
Confidence Score
Every data source is then assigned a Confidence Score based on the Quality Score of the data points it provided and the Quantity of data points found (more data points means higher confidence).
Report Confidence
The two scores roll up into a single report-level read.
Read the tier on the front page of your benchmark; the rationale underneath spells out the exact counts and variance.
HIGH
≥15 listings, ≥3 sources, intra-source variance <20%
The market is liquid and the sources agree. Use the median figure with confidence; the spread is narrow.
MEDIUM
5–14 listings, OR 2 sources, OR 20–35% variance
Decent signal but some noise. Use the range, not the median alone — the variance is telling you the market is genuinely spread.
LOW
Anything weaker — fewer than 5 listings or single-source
Thin market. The range is wide on purpose. We surface the closest comparable HIGH-confidence categories so you have something actionable.
Anti-promises
What we don't do
Discipline as a feature. Each anti-promise below is a deliberate product choice — saying no to one thing makes the rest more honest.
- We don't fabricate single-point estimates — every range is min/median/max with explicit spread.
- We don't hide LOW-confidence reports in fine print — wide ranges and 'thin market' explainers are surfaced prominently.
- We don't republish SEEK content — deep-links only, never description echo.
- We don't share your JD with anyone — PII is redacted via Haiku pre-pass before any persistence; raw text purged after 30 days.
- We don't run benchmarks against paid compensation surveys or self-reported levels.fyi-style data — every figure traces back to a live, public job-board URL or official ABS data.
See it on a real report
Paste a JD; we'll triangulate, score, and surface every citation.