growth-experimentation
Growth Experimentation
You are a growth experimentation specialist. Build a high-velocity experimentation practice that systematically discovers what drives growth. This skill covers experiment types, hypothesis design, prioritization frameworks, statistical foundations, analysis, and building an experimentation culture.
Diagnostic Questions
Before designing experiments, clarify:
- What is your monthly active user count? (Determines statistical power and what you can test)
- What is your current experiment velocity? (Experiments per month)
- Do you have an experimentation platform? (Feature flags, A/B testing tool)
- Who runs experiments? (Dedicated growth team, product teams, everyone?)
- What are your top 3 growth levers? (Where should experiments focus?)
- How do you currently make product decisions? (Data-driven, intuition, HiPPO?)
- What is your risk tolerance? (Can you tolerate temporary conversion drops during testing?)
More from skenetechnologies/plg-skills
product-onboarding
When the user wants to design or improve new user onboarding -- including product tours, checklists, empty states, welcome flows, or progressive disclosure. Also use when the user says "first-run experience," "onboarding flow," "getting started," "stalled users," or "onboarding drop-off." For activation metrics, see activation-metrics. For signup optimization, see signup-flow-cro.
25viral-loops
When the user wants to design product-driven viral growth -- including invite mechanics, collaboration loops, embedding loops, or network effects. Also use when the user says "K-factor," "viral coefficient," "invite flow," "sharing mechanics," or "network effects." For structured referral programs, see referral-program. For growth loop design, see growth-loops.
19trial-optimization
When the user wants to optimize free trial conversion -- including trial length, trial type selection, expiry flows, or trial email sequences. Also use when the user says "trial conversion," "trial length," "trial design," "opt-in vs opt-out trial," or "trial-to-paid." For activation, see activation-metrics. For feature gating, see feature-gating.
17usage-based-pricing
When the user wants to design or implement usage-based, consumption, or metered pricing -- including credit systems, overage handling, or billing infrastructure. Also use when the user says "pay per use," "metered billing," "credit system," "usage pricing," or "consumption pricing." For broader pricing strategy, see pricing-strategy. For expansion, see expansion-revenue.
11retention-analysis
When the user wants to analyze, diagnose, or improve user retention -- including cohort analysis, churn prediction, engagement scoring, or resurrection campaigns. Also use when the user says "retention rate," "churn rate," "cohort analysis," "why are users churning," "NRR," or "how to reduce churn." For engagement loops, see engagement-loops. For activation, see activation-metrics.
11activation-metrics
When the user wants to define, measure, or optimize user activation -- including identifying the aha moment, measuring time-to-value, or building an activation funnel. Also use when the user says "activation rate," "aha moment," "setup moment," "habit moment," "time to value," or "how do I measure activation." For onboarding design, see product-onboarding. For retention, see retention-analysis.
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