SDR Ramp Cost Calculator

Every month a new SDR spends ramping has a salary cost and an assumed productivity gap. Enter your numbers below to model the cost per hire and per year, then compare a target-ramp scenario. The output is a planning model, not a forecast.

SDR Ramp Cost Calculator

Adjust the inputs below. Results update instantly.

$7,000

Enter salary, benefits, taxes, and tools for your team.

5 mo

Editable scenario. Use your observed time to productive work.

40%

Productivity gap you pay for: 60%

$25,000

Won revenue a fully-ramped rep generates per month

5
3 mo

Scenario only. Compare with your own onboarding data.

Annual Ramp Cost (Whole Team)

$480K/yr

Across 5 hires per year

Sunk salary / hire

$21K

Lost pipeline / hire

$75K

Total ramp cost per hire

$96K

Target scenario5 mo → 3 mo

$192K/yr modeled difference

$38K modeled difference per hire at the target ramp

How the calculator works

Ramp cost is modeled from two inputs. Sunk salary is the compensation you enter while a rep produces below the selected productivity level. Lost pipeline is the revenue you enter for a fully-ramped rep over the same months. The result changes directly with your assumptions.

Frequently asked questions

How is the cost of SDR ramp time calculated?

Ramp cost has two parts. Sunk salary = fully-loaded monthly cost x ramp months x the productivity gap (the share of full quota the rep is NOT yet producing). Lost pipeline = the monthly revenue a fully-ramped rep generates x ramp months x the same gap. Add them for the cost per hire, then multiply by hires per year for the team total.

What is a typical SDR ramp time?

There is no universal ramp time. The calculator starts at 5 months as an editable scenario; replace it with your observed time to productive work and compare the result with your own hiring records.

How can I reduce SDR ramp cost?

Structured onboarding and deliberate practice are possible operating choices, not guaranteed outcomes. Use the target-ramp slider to model a scenario, then compare it with your own cohort data before treating the difference as a planning estimate.

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