growth-hacker

Designing a viral loop involves calculating the viral coefficient and structuring referral incentives to drive user acquisition. This Skill helps you model viral loops, define referral program incentives, and plan data-driven experiments to optimize activation rates for SaaS and consumer apps.

ICE prioritization scores growth experiments by Impact, Confidence, and Ease to rank user acquisition and retention tactics. You can use it here to prioritize your growth hacking roadmap, forming hypotheses and scoring proposed A/B tests to identify high-value onboarding and referral campaigns.

Calculating CAC, LTV, and churn rate requires defining specific pirate metrics (AARRR) to track user acquisition and retention performance. This Skill facilitates metric definition and modeling, enabling you to build a 30-day actionable growth plan that tracks these core metrics for your digital product.

Yes, you can use this to run A/B testing for onboarding optimization in consumer apps. It provides A/B testing guidance and frameworks to structure onboarding experiments, helping you increase user activation, reduce churn, and validate growth hypotheses rapidly.

The best way to structure a 30-day campaign is to combine acquisition channel ideas with retention campaigns and A/B testing into an actionable experiment roadmap. This Skill supports creating 30-day growth plans focused on referral acquisition and onboarding optimization while tracking CAC and LTV.

Growth hacking frameworks prioritize rapid, data-driven experimentation over standard marketing to accelerate user acquisition and retention. For a crypto trading app, this approach enables targeted onboarding and referral experiments, optimizing viral loops and activation rates with measurable metrics like LTV and churn.