• Analyze the Retention table → 

• Save & Analyze specific cohorts to get to the why → 

 

» Cohort Analysis with the Retention Table

The table below the graph is referred to as the retention table. This table offers a more detailed breakdown of your retention data.

The first row of the table outlined in red shows the overall average retention for each day/week/month/quarter, depending on the return interval selected. 

• Each row with the blue arrow represents a cohort of users grouped by the start action date. 
• Each column represents the time window from the start event, defined by the return interval.

Cohort analysis helps you uncover patterns in your retention data. The use of colors in the cohort table helps you quickly identify retention patterns. The blue shading gets darker the higher the retention percentage. It's important to note that the scale is relative to each cohort row.

 

In the example below, we created a retention report to see the retention of users who have signed up on our delivery app and have completed a purchase. We have grouped cohorts by week (represented in rows)  and have defined the return interval as each week (represented in columns) as we think users should order weekly on our app. We're looking at retention on a rolling basis.

 

How to read the table? 

 

• In the week of Aug 26 - Aug 31, there were 19 users who signed up, users with the start action selected. In the < Week 1 bucket, we can see that from the 19 who signed up at any point of the week of Aug 26 - Aug 31, 13 users returned to complete the return action, purchase within 7 days or < Week 1 after signing up. 
• In the Week 1 bucket, there were 12 users who did "Sign Up" in the same week of Aug 26 - Aug 31, but returned to complete a purchase 7-14 or Week 1 days after signing up. 

💡 Note » Count vs. Percentage: You can switch between count and percentage views in the table.

 

Save & analyze retained and drop-out cohorts 

The cohort table helps you quickly identify patterns and which cohorts are performing well or underperforming, but why is this happening? Dive deeper into the reasons by saving any retention cohort, and instantly access a pre-built dashboard with all relevant data regarding the cohort's performance. By saving and analyzing specific cohorts, you can slice and dice your data to get the most granular insights to make a positive impact on retention. 

• • Watch sessions of churned users to understand what they last did in your app. 
  • Compare the usage and behavior between retained cohorts and dropped-out cohorts to understand what drives retention in your app.
  • Save churned users and identify if users were impacted by tech issues. 
  • Filter by cohorts in funnels, app flows, dashboards and other UXCam features to investigate even further. Example:
    
    
    • Filter funnels by saved retained cohorts and learn whether users who complete the onboarding flow retain better.
      
      
    • Find out if cohorts with strong retention follow a specific path in your app in app flows. 

Click over any cell to save the retained or dropped-out cohorts. Simply click on the button, and a pop-up will prompt you to name and add a description to your cohort.  By default, the cohort will already be named in the format: Report title - Return time 

 

 

Click Start Analysis to get an instant dashboard with all relevant pre-built reports. You can choose which reports matter to you and remove others. With the automatic dashboard, you can investigate the engagement, adoption, and various other aspects within cohorts such as: 

• • How many sessions do users have on average?
  • Average time spent in the app
  • From which screens are users leaving the app?
  • IOS vs. Android usage
  • Most used app versions

» How to use cohorts to create reports or filters?

Once you save a cohort, you can apply it as a filter across various features in UXCam. You can apply cohort filters as regular filters on any page to analyze those cohort users' sessions, events, screen flows, heatmaps, etc. 

Using Cohort Filters to watch sessions

It's very easy to watch sessions of your churned users or well retained users. Understanding what your churned users did last in your app, or how users who retain well user your app can be insightful. 

Once you save a cohort, it will automatically become a filter. You just need to go on sessions, filter by the cohort saved, and you will get all sessions of the users from the cohort. 

 

 

Using Cohort Filters in Funnels

Example:

Onboarding Conversion Analysis

• • Compare the onboarding conversion of users who dropped out within the first week against those who were retained.
  • Create separate funnels for dropped-out users and retained users, observing differences in behavior.
  • Evaluate whether completing the onboarding flow correlates with higher retention.

» Applying Cohort Filters on Dashboards

 

Example

Compare reports between retained and dropped-out cohorts to investigate and identify key differences in user behavior and engagement.

Apply cohort filters on dashboards to compare time in the app, engagement, and other metrics between retained and dropped-out users.

» Applying Cohort Filters on Screenflow

 

• Explore the screen flow feature to understand the paths followed by retained users.
  
  
• Identify the best paths followed by retained users and strategize ways to guide unretained users along the same journey.

Combining Cohorts with Other Filters 

• Combine different cohorts for instance those that retained in week 1 and not in week 4.
• Combine cohorts with other filters, such as crashed sessions or device types, to create more nuanced segments.
• Save these filters as segments to gain insights into specific user groups and their interactions with the app.
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