Understanding customer activity over time can yield valuable insights into customer purchasing patterns, and the factors that drive those patterns. With these insights, there are opportunities to employ sales targeting and optimization techniques.

Use this Block to understand which customer cohorts are the most engaged, the most loyal, and the most profitable. Use this analysis to dive deeper and identify the factors that drive the greatest user loyalty. This Block can be applied to any data where users are being created and performing a transaction. Such as, computing revenue per user signup ('revenue/signup'). When you’re evaluating these metrics for different cohorts of users, you’ll create a parameterized derived table that allows you to dynamically calculate cohort size. This design pattern can also be used to compute revenue/signup for users by attribution channel, signup date, state, behavior, and any other user attribute, allowing you to quantify the historical value of users in different cohorts.