1) Meaning
A cohort is a group of individuals that share a common characteristic within a defined time period.
- In statistics, business analytics, healthcare, and ML, cohorts are used to analyze behavior, outcomes, or performance over time.
- The idea is to study patterns within the same group rather than mixing everyone together.
Think: “Track the journey of a group with something in common.”
2) Examples of Cohorts
(a) Business / Marketing
- Signup cohort: All customers who signed up in January 2024.
- Acquisition cohort: Customers acquired via Facebook ads in Q1.
- Behavioral cohort: Customers who made a purchase within their first week of signup.
(b) Healthcare
- Patients diagnosed with diabetes in 2022 → a medical cohort studied for treatment outcomes.
(c) Education / Social Science
- Students who enrolled in university in Fall 2020 → a graduation cohort.
(d) Machine Learning / Analytics
- Used in cohort analysis for churn modeling, retention analysis, or treatment effect estimation.
3) Cohort Analysis
Cohort analysis = tracking metrics for cohorts over time.
Example: Retention of user signup cohorts
| Month of Signup | Month 1 Retention | Month 2 Retention | Month 3 Retention |
|---|---|---|---|
| Jan 2024 Cohort | 70% | 50% | 35% |
| Feb 2024 Cohort | 72% | 55% | 38% |
| Mar 2024 Cohort | 68% | 52% | 36% |
This shows whether later cohorts behave differently from earlier ones.
4) Why Cohorts Matter
- Removes noise: Compares groups with shared starting points.
- Retention analysis: Tracks how long users/customers/patients stay engaged.
- Policy evaluation: Measures long-term impact of interventions.
- Fair benchmarking: Cohorts control for time-based effects (seasonality, macroeconomic events).
5) Difference from Segment
- Cohort: Group defined by time + shared event/characteristic (e.g., “all users who joined in March”).
- Segment: Group defined by attributes regardless of time (e.g., “all users age 18–24”).
Bottom line:
A cohort is a group of individuals who share a common characteristic within a defined period. Cohort analysis is widely used in business (retention), healthcare (patient outcomes), education (graduation rates), and ML (treatment effect estimation) to study patterns more accurately.