We all know that churn and retention are critical concepts to understand in SaaS. As customers churn each month, we track logo and dollar counts in our churn and retention reports. And we document the reasons why. This is an aggregate view of retention. Let me introduce SaaS cohort analysis.
Cohort analysis is an analytical framework that provides a more granular view of this same data. It gives us an understanding of the why, how, and when of our customer's actions, which helps us take steps towards improving customer retention and customer lifetime value.
What is a Cohort Analysis?
A cohort refers to a group of individuals having a statistical factor (such as age or class membership) in common in a demographic study.
In our SaaS perspective, a cohort refers to a subset of customers who share a common characteristic. This common characteristic is usually the date or month of customer acquisition (i.e., what I like to call "basic" cohort analysis). "Segmented" cohort analysis, uses additional characteristics (e.g., acquisition channel) to create cohorts.
In a cohort analysis, we study how the characteristics of a cohort change over time. This could be staying or leaving us, spending more or less with us (e.g., increasing/decreasing modules or users), and/or specific actions taken by the customer that make them successful or unsuccessful on our product.
