SaaS Pricing Calculator
Adjust the inputs below. Results update as you type.
How it works
Monthly Recurring Revenue (MRR) = paying users × average revenue per user. Annual run rate = MRR × 12. Net revenue retention accounts for churn, expansion, and contraction. A 5% monthly churn rate means you lose half your customers in a year. SaaS businesses typically aim for >100% net revenue retention, meaning expansion revenue exceeds lost revenue.
Input guidance
- Confirm date/time/unit settings before comparing outputs.
- If a task has optional fields, run both with and without them to understand impact.
- Save scenario variants when making practical decisions.
The formula
MRR = paying users × ARPU. ARR = MRR × 12. Simple LTV ≈ ARPU ÷ monthly churn (when churn > 0). A month-ahead projection grows users by growth then applies churn: users × (1 + growth) × (1 − churn).
Worked example
500 users at $29 ARPU yield $14,500 MRR ($174,000 ARR). At 5% monthly churn, LTV ≈ $29 ÷ 0.05 = $580 before accounting for COGS.
More examples to test
- Quick-pass example: run default assumptions for a first estimate.
- Refined example: update one assumption at a time to isolate impact.
How to interpret results
Use outputs as operational estimates and pair them with local constraints, business rules, or provider requirements.
When this can be inaccurate
Utilities can miss local policy details, special-case rules, and environment-specific constraints.
Change history
- July 2026: Published SaaS pricing path with MRR/ARR framing notes.
Site-wide corrections also appear on the corrections log.
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General recommendation, not professional advice.
Frequently asked questions
What is a healthy churn rate?+
It varies by price and segment, but many B2B SaaS teams target low single-digit monthly churn. High churn erodes LTV and forces constant acquisition just to stay flat.
How does COGS affect the model?+
COGS as a percent of revenue reduces gross margin on each dollar of MRR — useful when hosting, support, or payment fees scale with usage.
Why project month by month?+
Growth and churn compound. A flat snapshot of today’s MRR understates (or overstates) where revenue lands after a year of net user change.
Why are outputs slightly different from another tool?+
Different tools can use different rounding rules, default assumptions, and treatment of edge cases.
How can I improve estimate reliability?+
Use verified inputs from real records and re-run calculations after major assumption changes.