Cohort analysis is the best way to truly understand how your subscriptions evolve over their lifespan. In ChartMogul, you can analyse your cohorts' progression using the following metrics: Customer Churn, Net MRR Churn, Quantity Churn, Customer Retention, Net MRR Retention, Quantity Retention and Conversion of non-subscription customers to subscribers cohort analysis.
Why are cohorts so useful?
Instead of looking at a metric such as customer churn rate for all your customers in aggregate, a cohort analysis visualises the evolution of your churn specific to a targeted group of customers. This enables you to answer various questions such as:
- At which point in the lifetime of a subscription is churn at it’s highest?
- Does churn stabilise after some period of time?
- How has a product change impacted churn trends?
The cohort analysis can provide insights that may help you take appropriate actions to mitigate churn.
The different cohort analyses
You can access the cohorts by clicking on the Cohorts icon on the left-hand side in the navigation bar. You can view any of the following cohorts by selecting them from the list:
- Customer Churn - The percentage or number of customers that churned.
- Net MRR Churn - The percentage or MRR amount that churned.
- Quantity Churn - The percentage or quantity that churned.
- Customer Retention - The percentage or number of customers retained.
- Net MRR Retention - The percentage or MRR amount retained.
- Quantity Retention - The percentage or quantity retained.
- Conversion of non-subscription customers to subscribers - This analysis is useful to see how and when your non-recurring customers convert into subscribers.
This cohort analysis is only available to Scale and Volume customers.
How to read cohorts
Each row contains one group of customers (cohort) that started paying in a particular month. We follow the lifespan of each cohort, starting with the month they converted.
Depending on which chart you look at, the cohort value represents the total amount, customer number, or quantity acquired in that month.
The numbers in the top row represent the lifetime months. Month 0 refers to month 0-1, Month 1 covers month 1-2 and so on.
You can select the starting month and year in your analysis by clicking on the drop-down next to Starting month. You can create a cohort starting at any point in time.
Depending on which chart you are viewing, each cell in the cohort analysis can be shown as Customers or Rate (%), MRR or Rate (%),Quantity or Rate (%) and Rate (%) and Conversion. Clicking on the drop-down next to Show allows you to select one of the two available options.
It is important to note that the value for the average percentages shown at the bottom of each column is actually an aggregate value, which takes into account the differing size of each cohort. It is obtained by obtaining the total change in the underlying values for a particular month for all cohorts, and dividing this by the summed value of the cohorts' sizes. This prevents small variations in smaller cohorts from having the same contribution of a larger cohort (e.g. a decrease of 1 in a cohort of 2 vs. a decrease of 50 in a cohort of 100).
For example, in the Churn cohort, if in one month a cohort of 2 people decreases to 1, and another decreases from 100 to 75, the average churn of these two cohorts would be 37.5%, with the first cohort having a much larger influence considering its size. In contrast, our aggregate value ((1+25)/(2+100)) takes this into account and results in a value of 25.49%.
You can choose to view the data relative to the previous month cell or relative to the starting month (original cohort value) via the Relative to drop down.
Include current month toggle
You can choose to include the current month by ticking the box next to Include current month.
By clicking on any of the cells in the cohort analysis, you are able to see all of the activities of that particular month.
Cohorts work best with monthly subscriptions. If you have plans with other time intervals, we recommend creating a plan group of your monthly plans so that you can isolate them for your analysis.