What is an active user?

When people ask what is an active user, they’re really asking: who actually used our product in a meaningful way this period?

In analytics, a standard active user definition is: A unique user who performs at least one meaningful, predefined action in your product during a specific time window (day, week, or month).

That action can be as light as “opened the app” or as strict as “logged in and completed a transaction.” The active user meaning in practice: real humans doing real things in your app, not just names in a database or installs in a store.

You’ll usually see active users broken out as DAU, WAU, MAU – daily, weekly, and monthly active users.

Example of active users within apps

What counts as an active user depends on the product:

• Messaging app. Anyone who opens the app and sends or reads at least one message that day.
• Neobank / fintech app. Users who log in and either view balance, move money, or pay a bill this week.
• Mobile game. Players who start at least one session, level, or match in 24 hours.
• Meditation app. Users who complete at least one session in the last 30 days.

Same pattern every time: you’re not counting installs. You’re counting people who reached a moment of value.

What is the difference between users and active users?

Short answer: users are everyone; active users are the ones that actually show up.

• Users
  All accounts / installs / registrations you’ve ever collected. This includes people who churned months ago.
• Active users
  The subset of those users who did something meaningful in the last day (DAU), week (WAU), or month (MAU).

So you might have 500,000 total users in your CRM. If only 60,000 of them opened the app and completed at least one real action this month, then your MAU is 60,000.

That gap between “total users” and “active users” is your engagement reality check.

How to define active users

Here’s the part teams often gloss over – and where the expertise actually lives. You define active user meaning along three axes:

Time window

• Daily: DAU – good for “habit” products (social, comms, productivity).
• Weekly: WAU – good for weekly-use products (food delivery, travel).
• Monthly: MAU – good for lower-frequency or subscription products (finance, B2B).

Identity

• Use a stable identifier: user ID, account ID, or login.
• Avoid double-counting the same person across multiple devices.

Qualifying events

• Minimal: “opened app at least once.”
• Stronger: “opened app AND performed a core action.”
• Define 1–3 “this proves they used us” events and stick to them.

Active users formula

Conceptually, the formula is simple:

Active users (for a period) = count of unique users who triggered at least one qualifying event within that period

If you also want a rate against your total base:

Active user rate (%) = (Active users in period ÷ Total users) × 100

Most dashboards surface this as DAU, WAU, MAU, plus DAU/MAU for stickiness.

Example of calculation for apps

Let’s say you run a language-learning app.

Total registered users: 250,000

In the last 30 days:

• 55,000 unique users opened the app
• 40,000 completed at least one lesson

You decide: active = completed at least one lesson in the last 30 days.

MAU (monthly active users) = 40,000

Now check your active user rate: 40,000 ÷ 250,000 × 100 = 16%

Zoom into a single day:

• Yesterday, 8,000 unique users completed at least one lesson.
• DAU = 8,000

Stickiness: DAU/MAU = 8,000 ÷ 40,000 = 0.2 → 20% DAU/MAU

So: 16% of your total user base was active this month, and about 1 in 5 of those monthly actives showed up on an average day. That’s the kind of pattern growth and product teams care about.

Why are active users important?

Because active users are where all the real business outcomes live: retention, revenue, referrals, reviews. Everything.

A few reasons teams obsess over them:

1. They tell you if growth is real. Installs and signups can spike from a single campaign. If DAU/WAU/MAU don’t move, that spike was vanity. Watching active users by cohort and channel shows whether acquisition campaigns are delivering people who actually stick.
2. They’re the backbone of stickiness and retention metrics. The DAU/MAU ratio is one of the simplest engagement signals you’ll ever use. A higher DAU/MAU means your monthly users show up more often – they’re building a habit.
   For many utilities and commerce apps, 10–25% is a realistic band.
3. They forecast revenue better than installs ever will. Almost every monetization model in apps – ads, IAPs, subscriptions, upsell – scales with active users, not total users. If MAU is flat or declining, future revenue usually follows. If MAU is growing faster than your total base, you’re deepening engagement and increasing lifetime value.
4. They keep your experiments honest. You can’t judge onboarding, paywalls, or new features with “signups this week” alone. You want to see: did this change create more active users at D1, D7, D30? If not, it was noise.

FAQs

What is an active user in an app?

An active user is a unique person who performed at least one meaningful action in your app (like opening it and doing something useful) during a defined period – usually a day, week, or month. That’s the practical active user definition behind DAU, WAU, and MAU.

How strict should my “active” criteria be?

Strong rule of thumb: tie “active” to your value moment, not just a random event.
For a music app, “played a track.” For a finance app, “viewed balance or made a transaction.” For a game, “played a level.” Too loose, and your numbers look good but lie. Too strict, and you miss early engagement. Start simple, then refine.

Should I optimize for more users or more active users?

If you have to choose, always favor active users. More total users with flat or declining DAU/MAU just means your leaky bucket got bigger. More active users – especially by cohort – means you’re actually improving the product, not just buying traffic.