Cohort analysis is a method used to analyze the behavior and performance of a group of users, called a "cohort," over a designated period. A cohort typically consists of individuals who share a common characteristic or experience within a defined time frame. For example, a cohort might include users who signed up for a service in the same month or customers who made their first purchase in a particular quarter. By studying these groups, businesses can gain insights into how specific factors influence user engagement, retention, and conversion rates.
One common application of cohort analysis is in tracking user retention over time. For instance, a mobile app developer might analyze cohorts based on the month users downloaded the app to see which group has the highest retention rate after three months. By comparing these cohorts, developers can identify trends and determine if any changes made to the app (like updates or new features) affect user loyalty. If users from a more recent cohort show significantly lower retention, this might indicate a need to investigate issues or improve the onboarding experience.
Cohort analysis can also be useful for optimizing marketing strategies. For example, if a company runs multiple campaigns, it can segment the users who responded to each campaign into cohorts and analyze their subsequent behaviors, such as making a purchase or engaging with content. This analysis helps businesses understand which marketing efforts were most effective at attracting quality users and generating sales. Overall, cohort analysis provides a clearer picture of user behavior, helping teams make data-driven decisions that enhance product development and marketing strategies.