= Cohorot analysis terminology =

I am doing a lot of research related to cohort analysis in relation to customer lifetime value (CLV). Here’s a breakdown of key terminology associated with this topic:

• Cohort: A group of users who share a common characteristic or experience within a defined period. Cohorts are often defined by their first purchase date, sign-up date, or first use of a service.

• Cohort Analysis: The process of breaking down data into these groups and analyzing their behavior over time. This analysis helps in understanding patterns and trends across different segments of users or customers.

• Acquisition Cohort: Refers to users grouped by when they first made a purchase, signed up, or otherwise started using a service. The focus is on when users entered the funnel.

• Behavioral Cohort: Users are grouped based on specific actions they have taken within the app or service, like achieving a particular level in a game, completing a purchase, or engaging in a specific feature.

• Size Cohort: Groups users based on the size of their first purchase or engagement level. This can help in understanding how initial engagement level affects long-term behavior.

• Time Cohort: Groups users based on specific time periods, like monthly or quarterly cohorts, to analyze how seasonality or specific events affect user behavior.

• Retention Rate: The percentage of users who continue to use a service or product over time. It’s a critical metric in cohort analysis, indicating the long-term value of cohorts.

• Churn Rate: The percentage of users who stop using a service or product over a specific period. It’s the inverse of the retention rate and critical for understanding customer loss.

• Lifetime Value (LTV): The total revenue a business can expect from a single customer account throughout their relationship. Cohort analysis can help in estimating LTV by cohort.

• Segmentation: The process of dividing users into more granular cohorts based on demographics, behavior, or other characteristics to analyze more specific trends.

• Engagement: Measures how actively involved or engaged users are with a product or service. Metrics for engagement can vary but often include actions per session, session length, or frequency of use.

• Conversion Rate: The percentage of users who take a desired action out of the total number of users, often used in cohort analysis to measure the effectiveness of different cohorts in achieving business goals.

• Cohort Matrices: Tables that display the data of various cohorts over time, often used to visually analyze changes in behavior, retention, or other metrics across different groups.