Benchmark compensation for a {{role title}} at a {{company size and stage, e.g. 200-person Series C SaaS}} in {{geography}}.
For each, source from public salary databases (Levels.fyi, Glassdoor, payscale, public 10-Ks, hiring posts that disclose ranges), industry comp surveys, and public job posts.
Output:
## Range summary
| Component | P25 | P50 | P75 | Notes |
|---|---|---|---|---|
| Base salary | $X | $X | $X | |
| Variable / bonus | $X | $X | $X | Typical structure |
| Equity (4-year value) | $X | $X | $X | Refresh patterns |
| Total comp | $X | $X | $X | |
## Assumptions
List every assumption baked into the range:
- Geography norm used (e.g. SF Bay Area = 1.0)
- Stage norm (Series C = ?)
- Industry norm (SaaS infra vs. consumer)
- Remote vs. in-office adjustment
- Currency / inflation date
## Where the range is uncertain
- Components that public data is thin on
- Where the geography is non-standard
- Anything you had to extrapolate
## Comparable roles I should also benchmark
Adjacent titles that overlap on responsibilities (e.g. "Director of Engineering" can mean very different things — list the variants).
## Sources
Every number cited with a source and date.
Hard rules:
- Date every data point — comp moves fast
- Show your work — if I disagree with an assumption I should be able to recalculate
- Don't average across geographies without saying so
- Flag any range that comes from a small (<5) samplecompensationhiringbenchmarking