Learning path
Growth Product Manager learning path: everything to study, topic by topic
Comprehensive Growth Product Manager assessment covering growth foundations, acquisition loops, activation and retention, experimentation, monetization, and growth leadership.
Short answer
To learn Growth Product Manager, work through 6 modules and 20 topics in the order they build on each other. It starts with Growth Foundations, then moves on to Acquisition & Onboarding and Activation & Retention. Use the map as a checklist, or measure your level and study only what is missing.
What you will study
Topics are grouped by module. Open one to see its objectives and key concepts.
1 · Growth Foundations3 topics
Growth Mindset & Principles
Adopting a growth mindset that emphasizes experimentation, data-driven decisions, and full-funnel ownership beyond traditional product feature work
Objectives
- Articulate how a Growth PM differs from a Product PM across scope, metrics, and cadence
- Apply growth mindset principles to evaluate whether a project is worth pursuing
Key concepts
- growth mindset
- experimentation culture
- data-driven decisions
- full-funnel thinking
- growth vs product PM
AARRR Pirate Metrics Funnel
Mapping and instrumenting the AARRR funnel (Acquisition, Activation, Retention, Referral, Revenue) to identify the highest-leverage stage for growth investment
Objectives
- Instrument an AARRR funnel with event tracking that captures each stage
- Diagnose the leakiest AARRR stage and recommend the highest-leverage intervention
Key concepts
- AARRR pirate metrics
- funnel instrumentation
- stage conversion rates
- bottleneck identification
- growth diagnostics
North-Star Metric & Growth Modeling
Defining a north-star metric that aligns product value with business outcomes, and building a growth model that connects inputs to long-term value
Objectives
- Define a north-star metric that captures user value and predicts long-term revenue
- Build a growth model that decomposes the north-star into actionable input levers
Key concepts
- north-star metric
- input metrics
- growth model
- leading vs lagging indicators
- value-moment alignment
2 · Acquisition & Onboarding4 topics
Acquisition Loops
Designing acquisition loops (viral, paid, content, sales-assisted) that compound user growth beyond linear channel spend
Objectives
- Differentiate linear channel spend from compounding acquisition loops
- Design a viral, content, or paid loop with instrumentation for each loop step
Key concepts
- growth loops
- viral loops
- paid loops
- content loops
- sales-assisted loops
- compounding vs linear
Channel Mix Optimization
Evaluating channel portfolios, CAC by channel, and saturation curves to optimize acquisition mix across paid, organic, viral, and sales-assisted channels
Objectives
- Allocate a fixed acquisition budget across channels using CAC and saturation data
- Diagnose channel concentration risk and design a diversification roadmap
Key concepts
- channel CAC
- saturation curves
- channel concentration risk
- channel-ICP fit
- channel experimentation
Onboarding Flow Design
Designing onboarding flows that move new users from signup to first value with minimal friction and maximum conversion to activation
Objectives
- Design an onboarding flow that maps each step to a measurable activation signal
- Apply progressive disclosure to reduce cognitive load without hiding value
Key concepts
- onboarding flows
- progressive disclosure
- empty-state design
- signup friction
- onboarding checklists
Time-to-Value Optimization
Measuring and shortening time-to-value (TTV) — the time between signup and the first meaningful product outcome — as a leading indicator of retention
Objectives
- Define and instrument a TTV metric tied to product value, not vanity signals
- Diagnose the biggest TTV bottleneck and design an intervention with a testable hypothesis
Key concepts
- time-to-value
- first value moment
- onboarding drop-off analysis
- friction removal
- TTV cohort analysis
3 · Activation & Retention3 topics
Aha Moment & Activation Metrics
Identifying the product aha moment through behavioral analysis and defining an activation metric that predicts long-term retention
Objectives
- Identify the aha moment using retention cohort analysis and behavioral data
- Define an activation metric that is both measurable and predictive of retention
Key concepts
- aha moment
- activation metric
- behavioral cohort analysis
- retention correlation
- quick ratio of activation
Retention Curves & Cohort Analysis
Analyzing retention curves (smile curve, flattening curve), diagnosing cohort health, and designing interventions that bend the retention curve
Objectives
- Read a retention curve and identify whether it is flattening, decaying, or smiling
- Design a retention intervention with a clear hypothesis about curve shape change
Key concepts
- retention curve
- smile curve
- cohort analysis
- curve flattening
- retention by segment
Re-engagement & Habit Loops
Designing re-engagement programs and habit loops (trigger, action, reward, investment) that bring dormant users back and turn one-time users into habitual ones
Objectives
- Design a re-engagement campaign that measurably resurrects dormant users
- Apply habit loop theory to diagnose why a feature fails to form habits
Key concepts
- habit loops
- trigger-action-reward
- dormant user resurrection
- notification strategy
- lifecycle messaging
4 · Experimentation & Analytics4 topics
A/B Testing Rigor
Running A/B tests with proper rigor — hypothesis framing, randomization, sample ratio mismatch checks, and avoiding peeking and multiple-comparison traps
Objectives
- Frame a testable hypothesis with a primary metric and guardrails before launching a test
- Identify common A/B testing pitfalls (peeking, SRM, novelty) and design controls for them
Key concepts
- A/B testing
- hypothesis framing
- randomization
- sample ratio mismatch
- peeking problem
- multiple comparisons
Statistical Power & Bayesian vs Frequentist
Applying power analysis to size experiments, choosing between Bayesian and frequentist approaches, and interpreting confidence intervals correctly
Objectives
- Compute required sample size from MDE, baseline rate, and power to size an experiment
- Choose between Bayesian and frequentist approaches based on decision context and sample size
Key concepts
- statistical power
- power analysis
- minimum detectable effect
- Bayesian vs frequentist
- confidence intervals
- p-value interpretation
Experiment Velocity & Portfolio
Building experiment velocity through backlog grooming, prioritization frameworks (ICE/PIE), and portfolio balance across high-risk bets and safe optimizations
Objectives
- Build an experiment backlog prioritized by ICE or PIE scores with clear tie-breakers
- Design a weekly experiment cadence that delivers 3+ quality tests shipped per week
Key concepts
- experiment velocity
- ICE scoring
- PIE scoring
- experiment backlog
- portfolio balance
- win rate tracking
Growth Analytics Stack
Selecting and instrumenting a growth analytics stack (Amplitude, Mixpanel, Heap, warehouse-first tools) and designing a clean event taxonomy
Objectives
- Design an event taxonomy and tracking plan that avoids naming drift and event sprawl
- Choose between product-analytics vs warehouse-first stack based on team maturity and use cases
Key concepts
- Amplitude
- Mixpanel
- Heap
- event taxonomy
- tracking plan
- warehouse-first analytics
- reverse ETL
5 · Monetization & Pricing3 topics
Pricing Strategy & Packaging
Designing pricing strategy and packaging — value metrics, tiering, free-to-paid conversion, and running pricing experiments without damaging trust
Objectives
- Choose a value metric that aligns pricing with the value customers perceive from the product
- Design a pricing experiment that measures impact on both conversion and retention
Key concepts
- value metric
- pricing tiers
- packaging
- pricing experiments
- willingness-to-pay research
- van Westendorp
LTV, CAC & Unit Economics
Modeling LTV and CAC, computing LTV/CAC and payback period, and reasoning about unit economics to inform growth investment
Objectives
- Model LTV using cohort retention and ARPU rather than naive averages
- Interpret LTV/CAC and payback period to make acquisition investment decisions
Key concepts
- LTV
- CAC
- LTV/CAC ratio
- CAC payback
- unit economics
- gross margin
- contribution margin
Expansion Revenue & Upsell Mechanics
Designing expansion revenue motions — usage-based expansion, seat expansion, upsell triggers, and net revenue retention (NRR) optimization
Objectives
- Design usage-based upsell triggers that fire at moments of perceived value
- Diagnose NRR drivers and propose interventions to push NRR above 120%
Key concepts
- expansion revenue
- net revenue retention
- usage-based expansion
- seat expansion
- upsell triggers
- in-product monetization
6 · Growth Leadership3 topics
Growth Org Design
Designing growth org structures — dedicated growth teams vs embedded growth PMs, pod models, and partnering with engineering, design, and data
Objectives
- Choose between dedicated growth team vs embedded growth PMs based on company stage
- Design a growth pod model with clear interfaces to core product and engineering teams
Key concepts
- growth team structure
- dedicated vs embedded growth
- pod model
- growth engineering
- cross-functional partnership
- hiring growth PMs
PLG Strategy & Sales-Led Integration
Defining product-led growth strategy, integrating PLG with sales-led motions, and designing PQL-to-SQL handoffs at company scale
Objectives
- Define PQL criteria that sales trusts and that predict paid conversion
- Design a hybrid PLG+sales-led motion that avoids channel conflict and double-counting
Key concepts
- PLG strategy
- PQL definition
- PLG vs sales-led
- hybrid motion
- PQL-to-SQL handoff
- bottom-up adoption
Executive Storytelling & CEO Partnership
Building executive narratives around growth bets, partnering with the CEO as growth sponsor, and communicating experiment results to the board
Objectives
- Build a growth narrative that sequences experiment learnings into an exec-ready storyline
- Partner with the CEO as growth sponsor and align the exec team on annual growth bets
Key concepts
- executive storytelling
- growth narrative
- CEO partnership
- board reporting
- experiment portfolio comms
- growth strategy review
Levels: Junior, Mid, Senior, and Expert
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Frequently asked questions
Where should I start studying Growth Product Manager?
Start with Growth Foundations: Growth Mindset & Principles, AARRR Pirate Metrics Funnel, and North-Star Metric & Growth Modeling. The map orders topics by what they depend on, so each one prepares the next.
How long does a full Growth Product Manager assessment take?
A full assessment of this path takes about 45 minutes. Study time depends on where you start; a diagnostic shows which topics you can skip.
Do I need an account to use this page?
No. The map, objectives and key concepts are open. You only need an account to be measured, get your gap by topic and receive a plan.