M02-04 · AI Product & Business Strategy

Product-Led Growth and User Experience

Teaches students to drive product growth through user experience optimization. Covers onboarding flow design and optimization, activation metrics and improvement strategies, retention analysis and intervention design, growth experiments and A/B testing, and feature adoption tracking. Students learn to use data and user behavior analysis to systematically improve the user journey from signup through long-term engagement.

30 Hours

8 Learning objectives

Evaluate Bloom's ceiling (?)

5 Competencies

What You'll Be Able To Do

Learning Objectives

Objectives

Depth

Analyze onboarding funnels step-by-step to identify drop-off points, using both quantitative data (funnel metrics) and qualitative evidence (session recordings, user interviews) Analyze
Define and measure activation metrics: identify the "aha moment" that correlates with long-term retention, and design interventions to accelerate users toward it Analyze
Conduct retention analysis: cohort curves, segment-specific retention, and identification of behaviors that predict churn vs. engagement Analyze
Design and execute growth experiments with proper hypothesis, measurement plan, control group, sample size requirements, and statistical significance thresholds Apply
Set up and interpret A/B tests for product changes, including avoiding common pitfalls (peeking, multiple comparisons, novelty effects) Apply
Track feature adoption across user segments: measure discovery, trial, repeated use, and abandonment rates Apply
Design user experience improvements grounded in behavioral data rather than assumption, including personalization, progressive disclosure, and contextual guidance Create
Identify and mitigate metric conflicts: recognizing when optimizing one metric (signup conversion) damages another (activation or retention) — Goodhart's Law in practice Evaluate

Levels: Remember · Understand · Apply · Analyze · Evaluate · Create — highest demands most original thinking.

Core Competencies

What You'll Master

Onboarding Optimization

Funnel analysis, drop-off diagnosis, intervention design, onboarding flow testing.

Activation & Retention

Defining activation metrics, retention cohort analysis, behavior-outcome correlation, churn prediction.

Growth Experimentation

Hypothesis formation, A/B test design, statistical rigor, experiment velocity management.

Feature Adoption

Adoption funnel tracking, discovery optimization, usage pattern analysis, abandonment diagnosis.

Metric System Design

Balancing interrelated metrics, identifying perverse incentives, designing metric systems that align with business outcomes.

Portfolio Artifact

What You'll Build

Growth Optimization Case Study — Student takes a product with declining activation (simulated or real dataset), conducts full funnel analysis with session recording review, identifies 3 improvement opportunities with supporting data, designs 2 A/B test experiments with complete methodology (hypothesis, metrics, sample size, duration), implements one onboarding improvement, and writes a measurement report showing projected impact with appropriate statistical caveats.

Tools You'll Use

Industry Tools, Not Toy Projects

Amplitude / Mixpanel

Product analytics platforms for funnel analysis, retention curves, and feature adoption tracking.

FullStory / Hotjar

Session recording and heatmap tools for qualitative understanding of user behavior and drop-off points.

Google Optimize / LaunchDarkly

A/B testing and feature flag platforms for running controlled growth experiments.

Google Sheets

Experiment tracking, sample size calculations, and statistical analysis for growth tests.

Figma

Design tool for creating onboarding improvements, UX redesigns, and experiment variants.

PostHog

Open-source product analytics with built-in feature flags, session recording, and experimentation.

Claude

AI assistant for analysis support, hypothesis generation, and experiment design review.