analysis is a tool to measure user engagement over time. It helps to know whether user engagement is actually getting better over time or is only appearing to improve because of growth. Cohort analysis proves to be valuable because it helps to separate growth metrics from engagement metrics as growth can easily mask engagement problems. In reality, the lack of activity of the old users is being hidden by the impressive growth numbers of new users, which results in concealing the lack of engagement from a small number of people.
1)product lifetime (as depicted vertically down in the table) – comparing different cohorts at the same stage in their life cycle – we can see what % of people in a cohort are coming back to app after 3 days and so on. The early lifetime months can be linked to the quality of your onboarding experience and the performance of customer success team.
2)user lifetime (as depicted horizontally to the right of the table) – seeing the long term relationship with people in any cohort – to ascertain how long people are coming back and how strong or how valuable that cohort is. This can be presumably linked to something like the quality of the product, operations, and customer support.