User status segmentation: new, returning, resurrected and dormant users

User status segmentation classifies users each week or month as new, returning, resurrected, at risk or dormant, so you can see the flows behind your active user count. This guide defines each status, explains the growth accounting identity and quick ratio, lists actions per status, and shows a week where a campaign doubled new users but sent many straight to dormant.

What is user status segmentation?

User status segmentation groups users by where they are in their lifecycle with your product right now: new, active (returning), resurrected (back after a gap), at risk and dormant (inactive). Instead of one "active users" number, you see the flows between these states each week or month, which explains why the active base grows or shrinks.

A growing user count can hide trouble. If new users pour in while most of them go dormant a week later, growth is being bought, not earned. Status segmentation makes that visible.

The standard user statuses

The period (day, week or month) should match how often your product is naturally used. A daily messaging app and a monthly invoicing tool need different windows.

Save each status as a segment to compare behavior and revenue.

The growth accounting identity

Active users this period = new + returning + resurrected, and the change from last period is:

Δ active = new + resurrected − dormant

A related ratio, sometimes called the quick ratio for users, is (new + resurrected) ÷ dormant. Above 1 the active base grows; below 1 it shrinks. Products with healthy organic growth often sit well above 1; mature products hover near 1 with large returning bases.

How to use status segmentation

1. Choose the activity definition

Decide what counts as "active": any session, or a core action such as "created an invoice". Core actions give a truer picture.

2. Pick the period

Weekly for products used several times a week, monthly for products used a few times a month.

3. Read the flows, not just the totals

Each period, look at how many users entered (new, resurrected) and left (dormant). A stable total with high churn and high acquisition is a fragile business.

4. Act on each status differently

• New: onboarding and time to first value.
• Returning: deeper feature adoption, upgrades, referrals.
• Resurrected: find what brought them back (season, campaign, feature) and repeat it.
• At risk: reminders tied to their past use, help content, check-ins for valuable accounts.
• Dormant: win-back campaigns with a reason to return; learn why they left.

5. Track segments over time

Save each status as a segment so you can compare conversion, revenue and feature use across them.

Worked example: weekly lifecycle

A project management app (sample data), weekly active users defined as "updated a task":

Week 3's campaign more than doubled new users and active users jumped 12%. But dormant users rose to 2,600 in week 4: many campaign sign-ups did not return. The quick ratio fell back to 1.13. The next action was not more campaign budget but a better first-week experience for campaign users.

Common mistakes

• Using a window that does not match usage. Monthly statuses for a daily app hide churn; daily statuses for a monthly app show false churn.
• Counting opens as activity. Use the core action where possible.
• Watching only total active users. The flows explain the total.
• One message for all statuses. At-risk and dormant users need different approaches.
• Ignoring resurrection. It is often a large and cheap source of active users.

User status segmentation in TapCub

• Lifecycle view: All-platform analytics › Behavior › Behavior analysis › Lifecycle shows four counts per week or month: new, returning, resurrecting and dormant (drawn as negative on the next period). You can set an optional activity event and an "established" cutoff (default 7 days).
• Inactivity buckets: see how many people have been inactive for at least 7, 14, 30, 60 and 90 days.
• Segments: create rule-based user segments such as "active before, not seen in 14 days" and compare their behavior; RFM segments split buyers by recency, frequency and value.
• Retention: cohort retention for the same activity definition. See how to do cohort analysis.

Related: user segmentation examples, retention metrics.

FAQ

What is the difference between user status segmentation and cohort analysis? Cohort analysis follows groups of users who started at the same time. Status segmentation looks at all users in each period and classifies them by their current state.

How do I define a dormant user? Someone who was active in the previous period and inactive in this one, using the same activity definition and period length.

What is a resurrected user? A user who is active this period, was inactive in the previous period, and had been active at some point before.

Which period should I use? Match the natural usage interval: daily for apps used several times a day, weekly for apps used several times a week, monthly for occasional tools.

Sources

• Wilson, J. Growth accounting and the quick ratio. Social Capital.
• Mixpanel Docs. Lifecycle and retention reports.