What is ARPU?
Used in a sentence: Our user base grew last quarter, but ARPU slipped, so the new users are not spending the way earlier ones did.
How it works
ARPU spreads total revenue across every active user, including those who never pay. That makes it a useful single number for comparing periods, cohorts and markets.
ARPU can rise in two ways: more users start paying, or paying users spend more per order or per month. It can fall when a lot of new, low-spending users join at once, even if nothing is wrong with the product. That is why teams read ARPU alongside conversion to paid, average order value and retention, and break it down by cohort or segment rather than relying on the blended figure.
Example
A music streaming app wants to know whether its new family plan helped revenue. The team takes total subscription and ad revenue for the month and divides it by the average number of monthly active users. They then repeat the calculation for the month before launch. ARPU rose even though the user count barely changed, which suggests existing users moved to the higher-priced plan rather than new users driving the gain.
ARPU vs ARPPU
| ARPU | ARPPU | |
|---|---|---|
| Divides revenue by | All active users | Paying users only |
| Shows | Average value across the whole base | How much payers spend |
| Moves when | More users pay, or payers spend more | Payers spend more |
ARPPU, average revenue per paying user, is always higher. Reading both shows whether growth comes from converting more users or from earning more from existing payers.
Best practices
- Fix the definition of active user and the period before you compare ARPU over time.
- Break ARPU down by cohort, platform and acquisition channel so a mix shift does not hide a real change.
- Track ARPPU and conversion to paid alongside it to see what is driving the movement.
- Test upsells against a holdout group so you measure added revenue, not revenue that would have happened anyway.
How to do this with Digia Engage
Growth teams raise ARPU with in-app upsells: add-on suggestions at checkout, upgrade prompts at plan limits and inline offer widgets on the home screen. They build these in the no-code builder, target them using CEP segments, and launch without an app release. BBlunt launched seasonal campaigns 5x faster using inline homepage widgets, as covered in the BBlunt case study. More patterns are on the Monetization use case page.
Frequently asked questions
- How do you calculate ARPU?
- Add up all revenue earned in the period, including subscriptions, purchases and ad revenue if relevant. Divide it by the average number of active users in the same period, often the mean of the start and end counts. Use the same definition of active user every time so comparisons stay fair.
- What is the difference between ARPU and LTV?
- ARPU measures average revenue per user over a single period, such as a month. LTV, or lifetime value, estimates the total revenue a user brings over their whole relationship with the product. LTV depends on both ARPU and retention, since users who stay longer keep adding revenue.
- How can in-app experiences increase ARPU?
- They put relevant offers in front of users at the right time. Examples include an add-on suggestion at checkout, an upgrade prompt when a user hits a free plan limit, and personalised bundles on the home screen. Each raises revenue per user without needing more traffic.
Related terms
Read more
Part of the In-app engagement glossary.