1. First time users: How many users came back to your app each week after their first visit?

Start Action : First visit 

Grouped by : Week (Will group users who's start action happened the same week together in a cohort) 

Return Action : App launch 

Return interval : In or After Each Week

Insight: Helps understand if your customers are getting value in your app. Did you waste money to acquire these customers? Are your customers seeing the value immediately after using the app for the first time?  

2. Value action retention: How many users are coming back to the app to  perform a value action?

 

Start Action : First visit 

Return Action: Value Action 

Return Interval : The expected interval depends on your product and user behavior. Usually we recommend weekly intervals but this might vary for you. 

3. Feature Adoption: How many users come back to use a specific feature every week after they have discovered it?

1. Start action : Anything related to new feature : Exposure to new feature, screen feature, event interaction with feature etc...
2. Return action : Event or screen of feature 
3. Return Interval : In or after each week 

Insights : This type of analysis is valuable for product teams as it helps in assessing the sustained interest and utility of a feature over time. It provides insights into whether users continue to find value in the feature or whether they incorporate it into their regular usage patterns. If users are coming back again and again, that's a good sign that this feature is valuable and worth sustaining.

4. Impact of Feature on Retention : Measure the retention of users who have interacted with a specific feature. Did the feature help bring back users to the app?

1. Start action: Anything related to usage of new feature
2. Return Action: App launch (Represents users who came back on the app to do anything) 
3. Return Interval : In or after each week 

Insight: Evaluate the effectiveness of new features or changes in user behavior related to certain features.

Segmented Retention: Identify patterns and differences in retention among different user groups.

5. Device-Specific Retention: How does user retention differ across various devices? Is there a model with a noticeable poorer retention?

Start Action : First visit 

Return Action : App launch 

Return interval : In or After Each Week

Grouping: Device properties include: 

• Platform (Android vs. IOS) : Do android users have higher retention? Is there a performance of IOS users causing them to churn? 
• App version : Is the latest app version retaining more users? Have the performances had an impact on retention? 
• Device Model : Is the app not optimised for certain models?   

6. Geographic Location Retention: Are there variations in user retention based on geographic locations?

Start Action : First visit 

Return Action : App launch 

Return interval : In or After Each Week

Grouping: City/Country