Lifecycle
The Lifecycle insight breaks your active users into four buckets per period — answering “of the people doing X this week, how many are new, returning, resurrected, or about to churn?”
Open Lifecycle in the sidebar (/lifecycle).
The four cohorts
| Cohort | Definition |
|---|---|
| New | First-ever occurrence of the target event in this period. |
| Returning | Fired the event last period and this period. |
| Resurrected | Fired the event in some earlier period, was dormant, now active again. |
| Dormant | Fired the event last period but not this period (shown as a negative bar). |
The chart is a stacked bar per period — positive bars (new / returning / resurrected) above the axis, dormant below.
Filters
| Field | Notes |
|---|---|
| Date range | Bounds the periods shown. |
| Target event | The event that defines “active” — e.g. signed_in, app_opened. |
| Group by | day, week, or month — the period width. |
| Wakeup latency | Positive integer (default 1). A user is considered dormant after this many consecutive inactive periods. Set it higher for products with naturally low usage frequency. |
Pick week or month for B2B tools where daily usage isn’t expected, otherwise the dormant bar dominates. Daily lifecycle is best for products users open most days.
Reading the chart
A healthy growth chart has rising new and returning bars and a small dormant bar. If dormant exceeds new + resurrected, your active user base is shrinking. The resurrected bar is your win-back channel — large here suggests churn is recoverable.
Limits & gotchas
- Wakeup latency must be
>= 1. A value of0is rejected by the API. - Lifecycle is per-user, not per-group. Use Groups reports if you want a company-level lifecycle.
Related
- Stickiness — how often the same users come back
- Retention — long-tail return rates by cohort