Business Analytics
Intermediate
Cohort Analysis & Customer Lifetime Value
Measure customer retention curves, predict churn risk, and calculate true LTV.
Course Overview
Analyze user cohort retention tables, model customer acquisition cost payback periods, and build actionable customer segmentation strategies.
What You Will Learn
Construct customer acquisition cohort tables using SQL and Python
Model retention decay curves (power-law, exponential) to project long-term retention ceilings
Calculate historic and predictive Customer Lifetime Value (LTV)
Identify high-value customer personas based on behavioral purchasing patterns
Build automated churn risk scoring algorithms
Tools & Technologies Used
Python 3.11
Pandas
SQL
Lifetimes Library
Matplotlib
Structured Curriculum
2 Modules · 4 Lessons · 150 Minutes Total
Module 1
Module 1: Cohort Tables & Retention Curve Fitting
2 lessons
Module 1: Cohort Tables & Retention Curve Fitting
Transform transaction logs into readable cohort retention matrices.
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Building SQL & Python Cohort Heatmaps
Group users by signup month and track active user percentages across 12 periods.
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Fitting Retention Curves & Projecting Ceilings
Fit non-linear curves to estimate whether retention flattens into long-term product habituation.
Module 2
Module 2: LTV Modeling & Churn Prediction
2 lessons
Module 2: LTV Modeling & Churn Prediction
Predict future purchase behavior and build early churn risk models.
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Predictive LTV with BG/NBD Models
Use the Lifetimes package to estimate future transaction frequency and monetary value.
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Early Churn Risk Trigger Identification
Flag users showing sharp declines in session frequency before subscription cancellation.
Practical Project & Capstone Outcome
🚀 Capstone Project
Subscription Customer Retention & LTV Diagnostic Suite
Ingest 50,000 purchase logs, build interactive cohort heatmaps, project 3-year LTV for key customer segments, and output a churn risk alert list.
Prerequisites
- Basic SQL knowledge
- Python intermediate proficiency (Pandas)
Intended Audience
- Data Analysts evaluating subscription and e-commerce business health
- Product Marketers optimizing customer retention campaigns
Instructor Information
A
Alisha Fernandez
Course Author & Industry Expert
Alisha Fernandez is a Customer Analytics Director with extensive expertise in subscription business metrics and quantitative retention modeling.
Frequently Asked Questions
Does this course cover non-subscription e-commerce cohorts?
Yes! We cover both contractual (subscription) and non-contractual (e-commerce repeat order) cohort models.