Cohort#
A group of users sharing a common start characteristic, tracked over time.
Important
✨ AI-generated content. This page was written with the assistance of an AI language model and is provided as a learning aid. Despite careful review, it may still contain mistakes, omissions, or out-of-date information. Whether you are new to the topic, a team lead, or a senior practitioner, treat it as a starting point rather than an authoritative reference: read it critically and independently verify anything you act on (code, commands, figures, and factual claims) against official documentation and primary sources before relying on it.
What it is#
A cohort is a group of individuals who share a common characteristic within a defined time period. Across statistics, business, healthcare and ML, cohorts let you study patterns within one group over time rather than blurring everyone together — the idea is to track the journey of a group that has something in common.
Kinds of cohort#
The shared trait varies. A signup cohort is everyone who joined in January 2024; an acquisition cohort is everyone won through a Q1 ad campaign; a behavioural cohort is those who purchased within their first week. The same idea drives a medical cohort (patients diagnosed in 2022) and an education cohort (the Fall 2020 entering class).
Cohort analysis#
Cohort analysis tracks a metric for each cohort over time. A retention table, for instance, follows monthly signup cohorts down the rows and elapsed months across the columns — a January cohort might retain 70% at month 1, 50% at month 2, 35% at month 3 — revealing whether later cohorts behave differently from earlier ones. It removes noise by comparing groups with shared starting points, and it controls for time-based effects like seasonality.
Cohort vs segment#
The distinction is time. A cohort is defined by a shared event in a time window (“everyone who joined in March”); a segment is defined by attributes regardless of when (“all users aged 18-24”). Cohorts answer “how does this group evolve?”; segments answer “who are these people?”.
Theme: Business & Growth Analytics · All terminology
Hint
Mind map — connected ideas
Customer Segmentation · Retention · Churn · Causal Inference · Revenue per User (RPU / ARPU)
Hint
More in Business & Growth Analytics
Blended CAC (Customer Acquisition Cost) · CAC (Customer Acquisition Cost) · Cannibalization · Channel-Specific CAC (Customer Acquisition Cost) · Churn · Cohort-Based LTV (Simple Version) · Conversion Rate (CR) · Cost-Per-Click (CPC) Models · Cross-Selling · CTR (Click-Through Rate) · Customer Lifetime · Customer Segmentation · D2C (Direct-to-Consumer) · FTEs
See also
Source article Adapted (context, re-expressed) in our own words from: Cohort (insightful-data-lab.com).