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The Cohort tool allows you to understand how often your customers return and engage with your website or product.
- Analyze drivers of user retention as well as the factors related to churn
- Create user cohorts based on repeated behaviors and attributes
- Identify customers with high lifetime value (LTV)
Build your Cohort Analysis
Define your Cohort
To begin a cohort query, determine an initiating event (called the Cohort event). The first event of a cohort is required; a user must complete the initiating event or Cohort event and then return to perform a second event which is explained in the section "Target Behavior". Custom Events and Merged Events can be used. As with other tools, you may apply a Filter Where.
You may select a different time zone from your project time zone on a per query basis by locating the globe icon on the top right of the query screen.
You can chain multiple events in a sequence using an "and then performed" clause to define your cohort of users. In the following example, PetBox wants to measure users who download their app, and then start the app.
Generations and Breakouts
In addition to the first event, cohorts can be defined by a shared generation or a shared property. A generation is a unit of time, such as a month. A monthly cohort would include all users who entered the cohort during that month. A property is a characteristic or attribute, such as device type. Cohorts defined by device type would include all users with an iPhone, all users with an Android, etc. A user will only appear once in the results of a cohort analysis. For generation cohorts, users will be put into the first generation they fall into chronologically. For property cohorts, users will be put into the property breakout in which they first appear during the time interval.
After selecting an initiating event, you must select a Target Behaviour event. This second event of a cohort is also required; Custom Events and Merged Events can be used. As with the initiating event, you are also able to apply a Filter Where.
- Event: Often this is an event that is repeated multiple times, such as a purchase. This is the event that represents the subsequent user behavior that you wish to analyze.
- Revenue: Target behavior can also be represented as revenue. Using revenue as the target behavior will analyze the revenue generated over time by each cohort.