Salary decisions usually get made with a stale spreadsheet and a recruiter’s hunch. This replaces both: current market data, your own grades mapped onto it, and the budget consequence of every option before you commit to it.
Six pieces of work that used to take a week of spreadsheet archaeology each.
Sources get cleaned, outliers get questioned, and job titles get matched to real roles rather than to whatever the posting called them.
Compare by role, city, industry and seniority, with percentiles rather than a single misleading average.
Build the whole offer in one place: base, bonus, equity and benefits, with the real cost to the company attached.
Model the raise round before you announce it, with inflation, planned hires and the variance you are already carrying.
Where rates are heading in your roles, and which people have drifted far enough below band to become a resignation.
Connects to your HRIS, ERP, accounting and BI stack, with single sign-on and an API that covers everything the interface can do.
Most teams start with benchmarks and add planning once the first review cycle proves the point.
Current market rates for your roles and cities, with your grades mapped onto them and everything exportable.
Complete workforce financial modeling with scenario planning, inflation tracking, and strategic budget controls.
Machine learning-powered market forecasts, retention risk analysis, and strategic compensation recommendations.
Before a comp review you need three answers: where your bands sit against the market, which roles have drifted, and what the year costs if you fix them. The overview puts all three in one place, so you walk into the room with a position instead of a spreadsheet.
Every grade with its range, and the people sitting outside it, on the same axis.
Your medians against fresh market data for the same roles and the same city.
What closing the gap does to payroll this year, before you promise anything.
Each one answers a question that comes up in every review cycle. Figures below use sample data, not client numbers.
Interquartile range, EUR gross per year. Labels show the median.
| Grade | P25 | Median | P75 |
|---|---|---|---|
| L1 | 32 000 | 38 000 | 44 000 |
| L2 | 42 000 | 50 000 | 58 000 |
| L3 | 56 000 | 66 000 | 78 000 |
| L4 | 74 000 | 88 000 | 104 000 |
| L5 | 96 000 | 114 000 | 136 000 |
| L6 | 124 000 | 148 000 | 178 000 |
Median total cash by role, EUR gross per year.
| Role | Market | Your company |
|---|---|---|
| Backend | 78 000 | 81 000 |
| Frontend | 71 000 | 68 000 |
| Data | 84 000 | 79 000 |
| DevOps | 86 000 | 92 000 |
| QA | 58 000 | 57 000 |
Projected annual payroll, EUR millions, by quarter.
| Quarter | Baseline | Market catch-up |
|---|---|---|
| Q1 | 4.20 | 4.20 |
| Q2 | 4.32 | 4.48 |
| Q3 | 4.41 | 4.71 |
| Q4 | 4.55 | 4.98 |
Share of total package by level, per cent.
| Level | Base | Bonus | Equity | Benefits |
|---|---|---|---|---|
| Junior | 84 | 6 | 2 | 8 |
| Mid | 76 | 9 | 7 | 8 |
| Senior | 66 | 12 | 15 | 7 |
| Staff | 56 | 14 | 23 | 7 |
"TalentTech brought transparency to our compensation strategy, reduced budget overspend by 12%, and delivered evidence-based decisions for our salary adjustments."
Full plan detail, billing and refund terms are on the pricing page.
Flexible SaaS subscription model. Seat and project limits grow with you.
Send us a role list and we will run it against current market data before the call, so the walkthrough uses your figures instead of a demo account.
Tell us which roles matter most and we will bring benchmarks for them to the first conversation.