The Cohort module of MoEngage Analytics helps you understand user cohorts & retention. Retention & cohort analysis is essential to understand product health with respect to loyal returning users.
A cohort is a set of users, who are identified by their common behavior. The cohort for web and app analytics is a group of users who have performed the same events in a given duration. For example, new users on a music streaming app who are actively playing music for 15 days.
You can get graphical cohort reports for easy visualization. Tabular reports are also available for download and deeper analysis. Reports are helpful for analyzing cohorts over time.
You can use Cohorts to answer questions such as:
- How many users are using the platform after signing up?
- What percentage of users visited a particular product on the e-commerce app, returned to the app, and bought the product?
- What is the quality of users of paid channels compared to others?
To create a cohort,
- Navigate to the Analytics > Cohorts.
- Select the First Event and Return Event for cohort analysis from the drop-down menu.
You can use filters to drill down the cohorts to specific attributes such as Event Attributes, User Attributes, Device Attributes, or a combination of them.
Filters can be added to both the first and return event of the cohort depending on the data you want to segment. To add filters:
- Click Add Filters
- Select appropriate filters from the Filter By section.
- Select the Case Sensitive checkbox if you want the report to match the exact case of the value you specify.
You can add multiple filters and apply all filters or only one filter.
Toggle the switch between AND/OR based on your requirements.
You can also compare different cohorts by a specific attribute. You can compare cohorts for any property of the first event. To compare cohorts, click Split By and select the attribute from the drop-down menu. You can see the top 1000 values of the selected event property. The table has all the cohorts and the chart shows the top 5 cohorts.
Setting the data Time Frame
After defining the Cohort events, and the Split cohort attribute, in the Duration section, select the time frame of the cohort report. Choose any one of the following:
- Last 7 Days
- Last 30 Days
- This Month
- Last Month
- Select your own custom date range
Three different types of cohort analysis are Unbounded Retention, N Day Retention, and First Occurrence. You can access this on the chart.
Unbounded Retention provides the percentage of users retained until the selected date. The users can also be retained for more duration. Users performing the return event until the selected date or higher. For a higher level of granularity choose Hour, Week or Month instead of day.
The user installed the app (first event) on Week 0. The user opened the app (return event) on Day 0, Day 1 and Day 3 but did not open the app on Day 2. The user is counted as retained for Day 0, Day 1, Day 2(as well), and for Day 3. User will be counted retained for Day 2 as the user was active on the platform for the later period Day 3.
N-Day Retention provides the percentage of users retained on the selected day. It also includes the users who performed the return event on the selected day. For a higher level of granularity choose Hour, Week or Month instead of day.
The user installed the app (first event) on Day 0. The user has opened the app (return event) at least ones on Day 0, on Day 2 and on Day 4 but not opened app anytime on Day 1 and Day 3. She will be counted as retained only for Day 0, Day 2 and for Day 4. User will not be counted retained for Day 1 and Day 3 as she was not active on these days.
First Occurrence show the percentage of users, who perform the return event for the first time (after the first event) on a specific day. The percentage of users, who did not perform the return event until the selected day. First occurrence is how much time users are taking to perform the return event. For a higher level of granularity choose Hour, Week or Month instead of day.
The user installed the app (first event) on Day 0. The user did not perform the Purchase (return-event) on Day 1 & Day 2, user is counted as inactive on Day 1 & Day 2. On Day 3, when the user Purchase (return-event) for the very first time, user is counted as a returned user on Day 3. We do not consider what happens after Day 3 as this analysis only provides how long the user was away from the app, came back and performed the returned event.
Custom Segment Analysis
The cohort analysis is performed on all users available in the MoEngage system. Cohort analysis can also be performed for a group of users. The group of users is created using User Properties, or User Activity or Custom Segments, or any combination of them. Cohort analysis on users is similar to creating a segment and analyzing.
The cohort line chart is created as a weighted average of the percentage of cohort users for the selected day or selected granularity. The calculation is applicable for Retention and Return Visits.
By default, MoEngage Cohorts shows you your App/Site Open retention cohort for the last six weeks with weekly granularity.
You can break down the report into the granularity of Hourly, Daily, Weekly, or Monthly for easy visualization. Cohort users is displayed based on the granularity you select.
Few limitations for the cohorts granularity are:
- Hourly cohorts can only be viewed for the duration of a day.
- Daily cohorts can only be viewed for 90-day durations.
- Weekly cohorts can only be viewed for 180-day durations.
Add to Custom Dashboard
Cohort analysis reports can be pinned to any desired dashboard. You do not have enter all the steps & filters, and can see the analysis in one click on the custom dashboards. Click Save to Dashboard button to save the cohort analysis in custom dashboards. For more information, refer to Custom Dashboards.
Cohort Table Report
The column ‘Cohort’ shows the number of users who performed the first event on a specific day. The rows ‘Day 0’, ‘Day1’,.... ‘Day n’, provide the percentage of users according to Retention and Return Visit as explained. Day can be replaced with any granularity like Hours, Week or Month. The percentage numbers are color graded for a better holistic view.
Download the report after viewing the report. The charts are downloaded in PNG format and the table is exported in CSV format.