What is Active Users?
Active Users is the count of unique people who meaningfully interact with your site or app during a chosen time window (e.g., day, week, month). “Meaningful” typically means having an engaged visit rather than a brief bounce. In GA4, the default Users metric represents active users aligned to Engaged Sessions. Privacy-first tools (e.g., Plausible, Matomo, Simple Analytics) usually define it as unique visitors who triggered at least one request within the window.
How to measure Active Users
- Definition (generic):
Count distinct user identifiers who met your engagement rule during the window. Often this is a cookie-based ID like Client ID. - Engagement rule examples:
Session lasts ≥10s, ≥2 Pageviews, or any Conversion. - Windows and labels:
| Window | What it counts | Typical label |
|---|---|---|
| 1 day | Unique engaged users in last 24h | DAU |
| 7 days | Unique engaged users in last 7d | WAU |
| 28–30 days | Unique engaged users in last 28–30d | MAU |
Quick formula (conceptual):
Active Users (window) = COUNT DISTINCT(user_id) WHERE engagement_rule = TRUE AND timestamp ∈ window
Why it matters
- Product health: DAU/WAU/MAU show habitual use and retention; plotting DAU/MAU highlights “stickiness.”
- Marketing impact: Tie Active Users to UTM campaigns to see which sources grow the active base.
- Conversion modeling: More actives usually correlate with higher Conversion Rate, but verify via cohorts.
Differences across tools
- GA4: “Users” ≈ Active Users based on engaged-session logic across each Session in scope.
- Alternatives (Plausible/Matomo/Simple Analytics): Commonly treat any non-bot visit as activity; you can still add an “engagement” filter to mimic GA4.
Common pitfalls
- Consent gaps: A strict Cookie Banner can suppress tracking and undercount actives.
- ID churn: Clearing cookies or ITP short lifetimes inflate DAU relative to MAU.
- Bot filtering: Poor filters overstate activity; good filters may drop real traffic—monitor Real-Time Data during changes.
- Attribution bias: Channel spikes can lift actives without improving journeys; validate with User Flow and Cohort analysis.