Lifecycle

Use the Lifecycle view in Statsig product analytics to track new, returning, dormant, and churned users over time and quantify retention by cohort.

Overview

Lifecycle charts in Metrics Explorer help you understand how usage changes over time by classifying your unique units (for example user_id) within each time interval based on whether they used an event recently, returned after a gap, continued to use it, or churned.

Use Cases

• Track new-user ramp after a launch: See whether adoption is growing week over week after shipping a new feature
• Monitor churn and reactivation: Understand whether users are falling off (and whether they come back)
• Compare retention health across releases: Spot changes in “stickiness” and reactivation patterns over time

Creating a Lifecycle Chart

Step 1: Choose an event (or a compatible metric)

The first step to creating a lifecycle chart is to decide if you want to use a metric or an event. Lifecycle is designed for a single underlying event and count-style metrics that are composed of a single count type event

Step 2: Choose your unit (unique units)

Select what you want to count uniquely (for example user_id, stable_id, or another unit). The chart reports how many unique units fall into each category for each time interval.

Step 3: Choose your interval (granularity)

Pick an interval unit (day / week / month) and a number of intervals per bucket (1–48). Each bar on the chart represents one interval bucket, and the chart shows one data point per bucket across the selected date range (max 1 year).

Step 4: (Optional) Add filters

Apply filters to focus on a specific segment (for example platform, country, app version, or a feature-related property).

Interpreting your Lifecycle Chart

Each interval bucket classifies unique units into four categories (mutually exclusive):

New: Used during this interval, and did not use at any point earlier within the lookback window (up to 1 year before this interval).

Resurrected: Used during this interval, did not use in the immediately previous interval, and did use earlier within the lookback window.

Recurring: Used during this interval and the immediately previous interval.

Dormant: Used in the immediately previous interval, but not during this interval (often displayed below the axis to make churn visually obvious).

Reading the chart

X-axis: Time, grouped into your chosen interval buckets.

Y-axis: Count of unique units.

Stacked bars: Show how the composition of usage changes over time (new vs resurrected vs recurring), while the churn component (dormant) highlights drop-off between adjacent intervals.