How RankedIn builds and publishes its LinkedIn career benchmarks.
Every benchmark is built from completed RankedIn analyses of official LinkedIn data exports — not scraped or estimated data.
If you’ve analysed your LinkedIn profile more than once, only your most recent completed analysis counts toward any benchmark. Repeat analyses never inflate a sample size.
We first determine whether a profile represents a working professional, an active student, an early-career/adjacent profile (intern, trainee, apprentice, recent graduate with no current role), or is unclassified. Only working professionals are compared in professional benchmarks; only active students are compared in student benchmarks, grouped by major rather than by aspirational job title. Interns and trainees are excluded from professional benchmarks even when their role’s function is otherwise clear.
Professional benchmarks group people by their current professional function (e.g. Software Engineering, Marketing, Finance) rather than by employer industry. A profile’s function is determined from their current job title first, their headline second, and prior role history last — never from employer industry or a passing mention of a skill or tool.
When a profile’s function can’t be determined with reasonable confidence — for example, multiple current roles pointing to different functions, or no clear title at all — that profile is held out of every published benchmark until it can be confirmed, rather than being counted on a best guess.
For each eligible group, we calculate the median as the primary statistic, plus the 25th and 75th percentiles (the "middle 50%"). We report sample size, publication date, and week-over-week movement alongside every benchmark.
A benchmark only becomes "Established" once it has at least 50 eligible profiles ("Emerging" at 20+, "Directional" at 10+). Below that, we don’t make quantitative benchmark claims. To avoid a benchmark flickering between states as its sample size moves near a threshold, demotion requires falling further below that threshold than the promotion required — not just dipping one below it.
Every benchmark recalculates on a weekly schedule. A calculation that fails validation never replaces the last published benchmark — pages keep showing the most recent good data rather than a zero, a null, or an unpublished page.
Every benchmark shown is an aggregate statistic across a group of people — never an individual profile, name, or identifiable record. Small groups are held below our publication threshold specifically to avoid this.
This page describes methodology version v1. Material changes to population rules, taxonomy, eligibility, or calculation methods will increment this version rather than silently changing what a published number means.