The lifeblood of any app lies in its ability to capture and maintain user engagement. After all, countless apps have fallen by the wayside due to a lack of user interest. This is where mobile app engagement metrics comes into play. They provide valuable insights into user behavior, helping you understand what's working, what's not, and where to focus your marketing and development efforts.
This blog dives deep into 10 crucial mobile app engagement metrics that you absolutely need to monitor. By tracking these metrics and analyzing the data, you can gain a comprehensive understanding of your app's health and make data-driven decisions to optimize the user experience.
Ten mobile app engagement metrics you need to monitor
1. Retention rate
Retention rate measures the percentage of users who remain active on an app after a certain period from installation.
How to calculate retention rate?
The formula for calculating retention rate is:
Let's say you have 150 users at the beginning of the month. You bring in 30 new customers during that month and end the month with a total of 120 users.
In this case, your user retention rate will be 60% [(120 - 30) / 150] x 100. So, you have kept 60% of your existing customers happy.
It is important to note that retention rate can be measured over days, weeks, months, or years. Choose a timeframe relevant to your business (e.g., monthly for subscription services)
What is a good user retention rate?
The average 30-day retention rate across various app categories falls between 27% and 43%. High-performing apps can reach retention rates as high as 66%. It's important to benchmark your app's retention rate against competitors in your specific industry.
How to improve retention rate?
Improve Onboarding
A strong onboarding process significantly boosts retention. Make sure new users understand the app's value and how to get started effectively.
Offer In-App Incentives
Well-timed incentives like rewards or loyalty programs can encourage users to come back regularly.
Personalize the Experience
Tailor the app experience to individual users based on their preferences and usage patterns.
Gather User Feedback: Actively seek user
Gather User Feedback
Actively seek user feedback through surveys or in-app prompts to understand what's working and what's not.
2. Churn rate
In the context of mobile apps, churn rate refers to the percentage of users who stop using your app over a defined period of time. This can happen in a few ways:
01.
Uninstalling the app
This is a clear sign a user has abandoned the app altogether.
02.
Disengaging with the app
Even if users don't uninstall, a drop in activity can signal churn. This might involve them no longer logging in or using the app's features for an extended period.
How to calculate churn rate?
The formula for calculating churn rate is
For example, if you started a month with 1,000 users and ended with 800, your churn rate for that month would be 20%.
What is a good churn rate?
Similar to retention rates, average churn rates vary by app category. Generally, a churn rate below 5% per month is considered excellent, while anything above 25% is a cause for concern.
What are the common reasons for user churn?
01.
Poor user experience: Bugs, crashes, or a confusing interface can frustrate users and lead to abandonment.
02.
Lack of value proposition: If users don't find your app useful or engaging, they'll have no reason to stick around.
03.
Unmet expectations: Misleading marketing or failing to deliver on promised features can disappoint users.
How to prevent user churn?
Focus on onboarding: Ensure a smooth and informative onboarding process that clearly explains the app features and benefits.
Gather user feedback: Actively seek user feedback through surveys or in-app prompts to understand pain points and areas for improvement.
Personalization: Personalise the user experience to cater to individual needs and preferences.
Re-engagement campaigns: Win back inactive users with targeted campaigns that remind them of the app's value.
Track user behaviour: Monitor how users interact with your app to identify potential drop-off points and optimise features accordingly.
3. Active users (DAU and MAU)
DAU (Daily Active Users) and MAU (Monthly Active Users) are two key metrics used in mobile app analytics to understand user engagement and app growth.
DAU represents the number of unique users who interact with your app in a single 24-hour period. A high DAU indicates a strong user base that actively uses the app on a regular basis. It can be helpful for apps where daily usage is expected, like social media or news apps.
MAU represents the number of unique users who interact with your app within a 30-day window (usually a rolling 30 days). It provides a broader picture of your user base and its overall activity level.
A high MAU indicates a larger user base overall, even if some users might not engage daily. It's useful for apps where usage might be less frequent, like banking apps or travel booking apps.
4. Average session length
Average session length is a metric that measures how long users, on average, stay active within your mobile app during a single session. It's a valuable indicator of user engagement, as it reflects how deeply users are immersed in your app's functionalities.
How to calculate average session length?
The formula for calculating average session length is
For instance, if an app had five sessions in a day, totaling 100 minutes, the average session length would be 100 minutes divided by five sessions, which equals 20 minutes. Thus, users, on average, spend 20 minutes in the app each time they use it.
What is a good average session length to have?
The "ideal" average session length can vary significantly depending on the app category. For instance, gaming apps or entertainment apps might see higher average session lengths compared to productivity or utility apps. It's important to benchmark your app's session length against industry standards for similar apps.
A study from Localytics indicates that an average session length of 2-3 minutes is typical for most mobile apps.
How average session length can be used to improve your app?
A low average session length might indicate that users are losing interest quickly. You can analyze user behavior data to see where users drop off and identify potential issues with the app's design, features, or content.
If you make changes to improve user engagement, tracking average session length can help you gauge their effectiveness. Did the changes lead to users spending more time in the app?
Ultimately, the goal is to create an app that users find valuable and engaging enough to spend more time with. By monitoring average session length, you can get valuable insights to optimise the user experience and keep users coming back for more.
5. Session frequency
Session frequency refers to how often users open and interact with the app within a specific timeframe. Unlike average session length, which focuses on the duration of a single session, session frequency looks at the overall pattern of app usage.
Session frequency provides valuable insights into user habits and engagement levels. High session frequency indicates users are opening the app frequently, suggesting they find it valuable and useful for their needs. This is particularly positive for apps designed for regular use. Low session frequency may suggest users lose interest quickly or don't find the app relevant enough for their daily lives.
How to calculate session frequency?
The formula for calculating session frequency is,
For example, if your app has been used 1000 times (sessions) by 250 unique users in a month, the session frequency would be 1000/250 = 4 sessions per user per month.
What is a good session frequency to have?
The "ideal" session frequency can vary depending on the app category. News apps or social media apps might see higher session frequency as users check them for updates throughout the day. Finance apps or travel booking apps might have lower session frequency as users might only need them occasionally.
How session frequency can be used to improve your app?
Identify power users vs. churned users: Analyzing session frequency can help differentiate between highly engaged users (power users) who open the app frequently and users who churn (abandon the app) due to low usage.
Target user engagement efforts: By understanding user segments with low session frequency, you can target specific user groups with re-engagement campaigns or personalized content to bring them back to the app more often.
Optimize app features and content: Low session frequency might indicate a lack of engaging features or content. Analyzing user behavior data alongside session frequency can help identify areas for improvement to keep users coming back for more.
6. Session interval
Session interval refers to the amount of time that elapses between two separate sessions for a single user. It provides insights into user behaviour and how frequently they return to the app.
Short session intervals indicate users are opening the app frequently, suggesting they rely on it for immediate needs or find the content highly engaging. Long session intervals may suggest users don't find the app essential for their daily needs or that the content isn't compelling enough to warrant frequent revisits.
How to calculate session interval?
There isn't a single, universally accepted way to measure session interval. It can be calculated in different ways depending on the app's specific goals and functionalities. Here are two common approaches:
01.
Time between app opens: This is a straightforward approach that simply measures the time difference between when a user closes one session and opens the next.
02.
Time spent inactive: This method focuses on how long a user remains inactive within the app before returning to it. It considers a session "inactive" after a predefined period of inactivity (e.g., 30 minutes) and then measures the time until the user actively engages with the app again.
How session interval can be used to improve your app?
For apps with long session intervals, targeted notifications or timely content updates can nudge users to come back sooner.
Long session intervals after initial use might indicate a confusing onboarding process. Optimizing onboarding can help users understand the app's value and encourage them to return more frequently.
Note: Session interval should be considered alongside other metrics like session frequency and average session length. This combined analysis provides a more comprehensive picture of user engagement and helps you make informed decisions to improve your app and keep users coming back for more.
7. Conversion rate
Conversion rate refers to the percentage of users who complete a desired action within the app. This desired action can vary greatly depending on the app's purpose and goals. You can find some of the widely used conversion actions for mobile applications below,
1. Completing a purchase, adding items to a cart, or initiating a checkout process.
2. Signing up for a paid subscription or upgrading a free account.
3. Completing a level, making an in-app purchase, or logging in daily for a reward.
4. Uploading content, following other users, or clicking on an advertisement.
By understanding and monitoring conversion rates for these actions within your app, you can gain valuable insights into user behavior and make data-driven decisions to improve the app's effectiveness in achieving its goals.
How to calculate conversion rate?
The formula for calculating conversion rate is
Imagine a fitness app has 10,000 users visit a specific workout routine within the app in a week. If 500 users actually complete the workout, the conversion rate for that workout routine would be (500 conversions / 10,000 visitors) x 100% = 5%.
What is a good conversion rate?
A good conversion rate for mobile apps falls around 1-2%.
How conversion rate can be used to improve your app?
Identify areas for improvement: By tracking conversion rates for different actions within the app, you can identify areas where users are dropping off and not completing desired actions. This can help pinpoint usability issues, confusing interfaces, or unclear calls to action.
Optimize user journey: Analyzing user behavior data alongside conversion rates can help you understand the user journey within the app. You can then optimize the user experience to guide them smoothly towards completing desired actions.
Effective A/B testing: Conversion rate is a great metric to use for A/B testing different app features, layouts, or marketing messages. By comparing conversion rates, you can see which variations resonate more with users and drive higher conversion.
8. Exit rate
Exit rate refers to the percentage of users who leave a specific screen or page within the app without interacting further. It essentially tells you how often users navigate away from a particular screen, before or after engaging with any of its elements.
By monitoring and analyzing exit rates for different screens within your app, you can gain valuable insights into user behavior and make data-driven decisions to improve user experience, reduce user frustration, and ultimately keep them engaged with your app.
How to calculate exit rate?
Exit rate is normally calculated for individual screens or sections within the app. It's represented as a percentage and is often tracked using mobile app analytics tools.
For example, if your website was viewed 500 times and 200 visitors left from one particular page, the exit rate for that page would be (200 exits/ 500 views) * 100 = 40%.
What does a high exit rate mean?
High exit rate indicate users are finding the screen confusing, irrelevant, or lacking the information they need. This could lead to frustration and ultimately churn (users abandoning the app).
How exit rate can be used to improve your app?
Identify user drop-off points: Analyzing exit rates across different screens can help you pinpoint where users are losing interest and abandoning the app flow.
Optimize screen design and content: High exit rates on specific screens might indicate a need to improve the design, content clarity, or calls to action to better engage users.
Improve user journeys: By analyzing exit rates alongside other user behavior data, you can understand how users navigate the app and identify areas where the user journey can be optimized to keep them moving towards your desired actions.
9. Most visited / active screens
Most visited or active screens refer to the pages or sections within the app that users access and interact with the most. Identifying and understanding these key screens is crucial for optimizing user experience and improving app engagement.
How to identify the most visited or active screens?
Two common methods to identify the most visited or active screens in your app are,
01.
Using a mobile app analytics tools
Most mobile app analytics platforms track user behavior data, including screen views, time spent on each screen, and user journeys within the app. These tools can provide reports that highlight the most frequently visited screens and user flows.
02.
Heatmaps and behaviour analysis tool
Heatmaps are visual representations of user interactions within the app. They typically use color gradients to show areas of a screen that receive the most taps, swipes, or other user interactions. This can help identify specific elements within a screen that are attracting the most attention.
How understanding most visited/active screens can be used to improve your app?
Prioritize feature development: Focus development efforts on features and functionalities associated with the most visited screens, as these are what users value most.
Optimize user journeys: Analyze user flow data to see how users navigate from one screen to another. Identify opportunities to streamline the user journey and make it easier for users to find what they need.
Personalization: Leverage user data to personalize the app experience based on which screens users visit most frequently. This can involve tailoring content recommendations or functionalities to their specific interests.
10. Daily uninstalls
Daily uninstalls refer to the number of users who uninstall your mobile app on a particular day. It's a key metric for understanding user retention and gauging the health of your app.
How to calculate daily uninstalls?
These figures are typically calculated and reported via the dashboard of app stores like Google Play Console or Apple App Store Connect, or through third-party analytics tools. It's a raw count of how many users have chosen to uninstall your app from their devices on a particular day.
Aarathy Sundaresan
Content Marketer , CometChat