JavaScript is required for the interactive calculator. Please enable JavaScript and reload.

ARPU Growth Decomposition Calculator

Decompose revenue growth into ARPU change vs user growth (and interaction) between two periods.

Revenue changes because user count changes, ARPU changes, or both. Decomposing growth helps you see whether pricing/monetization or distribution/scale is doing the work.

This calculator uses a standard two-factor decomposition: revenue = users x ARPU.

Prefer an explanation- Read the guide.

Related definitions:arpu arpa arpa vs arpu

ARPU growth decomposition: what drove revenue (ARPU vs users)ARPA: how to calculate Average Revenue Per Account (formula + examples)Cohort payback curves: how to model payback with early churn Gross margin improvements: how margin changes LTV, payback, and growth ability

Revenue (start period)

Average active users (start period)

Revenue (end period)

Average active users (end period)

Tip: you can type commas (e.g., 10,000).

Example

Using the default inputs, the result is:

$15,000.00

Revenue (start period): $50,000
Average active users (start period): 2,000
Revenue (end period): $65,000
Average active users (end period): 2,300

How to calculate

Enter revenue and average active users for the start period.
Enter revenue and average active users for the end period.
Review how much of revenue growth is explained by ARPU change vs user growth.

Formula

Revenue = users * ARPU; Delta revenue = Delta users * ARPU_start + Delta ARPU * users_start + Delta users * Delta ARPU

Start/end periods use the same definition of revenue (gross vs net) and 'active user'.
Decomposition is directional; it helps explain changes but does not prove causality.

FAQ

Why is there an 'interaction' term-

Because users and ARPU can change at the same time. The interaction term captures growth that comes from both increasing together (or offsetting each other).

Should I use ARPU or ARPA for B2B SaaS-

If you bill per company (accounts), ARPA is usually more natural. If you bill per seat or per user, ARPU may match pricing better.

Common mistakes

Comparing periods with different 'active user' definitions (denominator drift).
Mixing net revenue in one period with gross revenue in another (inconsistent revenue base).
Attributing interaction effects incorrectly; use it as a directional decomposition.

How to interpret

How to interpret the decomposition

User-driven growth often points to distribution, acquisition, or activation improvements.
ARPU-driven growth often points to pricing, packaging, upsell, or mix shifts to higher-value segments.
If ARPU rises but user growth stalls, check conversion and retention by segment (pricing can shift who you attract).