---
title: Lifecycle
description: "Understand how users start, return, remain, and churn over time"
product: general
token_estimate: 743
---
# Lifecycle

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## How Lifecycle charts work

Lifecycle charts in Metrics Explorer help you understand how usage changes over time. These charts classify your unique units (for example, user\_id) within each time interval based on whether the units used an event recently, returned after a gap, continued to use the event, or churned.

![Life Cycle chart interface in Metrics Explorer](https://docs.statsig.com/images/product-analytics/lifecycle/lifecycle_demo_v4.png)

### 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 return.
- **Compare retention health across releases**: Spot changes in retention and reactivation patterns over time.

## Creating a lifecycle chart

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

Decide whether to use a metric or an event. Lifecycle works with a single underlying event and count-style metrics 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).

![Life Cycle chart interface in Metrics Explorer](https://docs.statsig.com/images/product-analytics/lifecycle/lifecycle_interval_selector.png)

### 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 didn't use at any point earlier within the lookback window (up to 1 year before this interval).

**Resurrected**: Used during this interval, didn't use in the immediately previous interval, and used 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 (Statsig displays this below the axis to make churn visually apparent).

### 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 dormant component highlights drop-off between adjacent intervals.