GITNUX MARKETDATA REPORT 2023

Must-Know Mobile App Retention Metrics

Highlights: The Most Important Mobile App Retention Metrics

  • 1. Daily Active Users (DAU)
  • 2. Monthly Active Users (MAU)
  • 3. Retention Rate
  • 4. Churn Rate
  • 5. Session Length
  • 6. Session Interval
  • 7. Stickiness
  • 8. LTV (Lifetime Value)
  • 9. ARPU (Average Revenue Per User)
  • 10. User Acquisition Cost (UAC)
  • 11. Day N Retention
  • 12. Time to First Action
  • 13. Feature Adoption Rate
  • 14. Virality Coefficient

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Mobile App Retention Metrics: Our Guide

Navigating the complex world of mobile app analytics can seem daunting, but understanding key retention metrics need not be a challenge. In this blog post, we will shed light on the metrics that matter most for keeping your users engaged and coming back for more. Equip yourself with these must-know mobile app retention analytics to effectively drive user engagement and strategize your growth.

Daily Active Users (DAU) - DAU measures the number of unique users who interact with the app within a single day. This metric helps understand app engagement and user frequency on a daily basis.

Daily Active Users (DAU)

DAU measures the number of unique users who interact with the app within a single day. This metric helps understand app engagement and user frequency on a daily basis.

Monthly Active Users (MAU) - Similar to DAU, MAU focuses on the unique number of users who interact with the app within a month. It helps evaluate the app’s growth potential and long-term engagement.

Monthly Active Users (MAU)

Similar to DAU, MAU focuses on the unique number of users who interact with the app within a month. It helps evaluate the app’s growth potential and long-term engagement.

Retention Rate - Retention rate measures user return after initial app use. Higher rates signify a more engaging app.

Retention Rate

Retention rate measures user return after initial app use. Higher rates signify a more engaging app.

Churn Rate - The churn rate is the opposite of the retention rate. It measures the percentage of users who stop using the app within a specific time frame. A lower churn rate indicates better user retention.

Churn Rate

The churn rate is the opposite of the retention rate. It measures the percentage of users who stop using the app within a specific time frame. A lower churn rate indicates better user retention.

Session Length - The average time users spend within the app per session. Longer session lengths often indicate higher user engagement.

Session Length

The average time users spend within the app per session. Longer session lengths often indicate higher user engagement.

Session Interval - The average time between users’ app sessions. A shorter session interval typically means higher user engagement.

Session Interval

The average time between users’ app sessions. A shorter session interval typically means higher user engagement.

Stickiness - Stickiness is the ratio of Daily Active Users (DAU) to Monthly Active Users (MAU). A higher value means users are more consistently engaged with the app.

Stickiness

Stickiness is the ratio of Daily Active Users (DAU) to Monthly Active Users (MAU). A higher value means users are more consistently engaged with the app.

LTV (Lifetime Value) - Lifetime Value (LTV) predicts a user’s net value throughout their app engagement, aiding in profitability projections and data- driven marketing decisions considering user acquisition costs.

LTV (Lifetime Value)

Lifetime Value (LTV) predicts a user’s net value throughout their app engagement, aiding in profitability projections and data- driven marketing decisions considering user acquisition costs.

ARPU (Average Revenue Per User) - ARPU is calculated by dividing total revenue by the number of active users. This metric provides an understanding of the app’s revenue-generating capabilities per user.

ARPU (Average Revenue Per User)

ARPU is calculated by dividing total revenue by the number of active users. This metric provides an understanding of the app’s revenue-generating capabilities per user.

User Acquisition Cost (UAC) - UAC refers to the average cost of acquiring one new user for the app. Comparing UAC to LTV helps in determining if the user acquisition strategy is profitable.

User Acquisition Cost (UAC)

UAC refers to the average cost of acquiring one new user for the app. Comparing UAC to LTV helps in determining if the user acquisition strategy is profitable.

Day N Retention - Day N Retention measures the percentage of users returning on specific days (e.g., Day 1, Day 7, or Day 30) after initial app installation. It reveals user behavior and engagement patterns.

Day N Retention

Day N Retention measures the percentage of users returning on specific days (e.g., Day 1, Day 7, or Day 30) after initial app installation. It reveals user behavior and engagement patterns.

Time To First Action - Time to First Action is the average time for new users to perform their initial app action, indicating onboarding efficiency.

Time To First Action

Time to First Action is the average time for new users to perform their initial app action, indicating onboarding efficiency.

Feature Adoption Rate - The percentage of users who adopt and engage with specific features within the app. This metric helps in understanding the usefulness of app features and prioritizing improvements.

Feature Adoption Rate

The percentage of users who adopt and engage with specific features within the app. This metric helps in understanding the usefulness of app features and prioritizing improvements.

Virality Coefficient - Virality coefficient measures how many new users are referred by existing users, indicating organic growth. Higher values mean more effective referrals.

Virality Coefficient

Virality coefficient measures how many new users are referred by existing users, indicating organic growth. Higher values mean more effective referrals.

Frequently Asked Questions

Mobile app retention metrics are measurements and key performance indicators (KPIs) that help in determining how well an app is retaining users over a specific period. They are important because retaining happy, engaged users is crucial for an app’s long-term success and profitability. Better retention rates lead to higher user lifetime value (LTV), improved engagement, and a larger user base.
Some common mobile app retention metrics to track include daily active users (DAU), monthly active users (MAU), user retention rate, churn rate, and session length. These metrics provide insights into user behaviour, app usage frequency, and app engagement, helping developers and marketers identify opportunities to improve the app experience.
To calculate the user retention rate, divide the number of users who return to the app by the number of users who installed it during the same time frame, multiplied by 100 to get a percentage. For example, if 200 users installed the app in a month and 60 of them return to the app in the same month, the retention rate would be (60/200) x 100 = 30%.
Churn rate, also known as attrition rate or customer loss rate, is the percentage of users who discontinue using an app within a given period. It differs from retention rate in that it measures the opposite – app abandonment instead of app engagement. A high churn rate indicates a larger number of dissatisfied users and can negatively impact an app’s growth and revenue.
To improve mobile app retention metrics, consider implementing a strong onboarding experience, engaging users through relevant and personalized push notifications, offering in-app rewards, incorporating regular app updates and feature enhancements, and utilizing in-app analytics to understand user behavior better. By addressing potential pain points and keeping users engaged, app developers can substantially enhance retention rates and overall app success.
How we write these articles

We have not conducted any studies ourselves. Our article provides a summary of all the statistics and studies available at the time of writing. We are solely presenting a summary, not expressing our own opinion. We have collected all statistics within our internal database. In some cases, we use Artificial Intelligence for formulating the statistics. The articles are updated regularly. See our Editorial Guidelines.

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