growth

Onboarding optimization identifies friction points in initial user flows and proposes actionable improvements. Map your current onboarding screens, measure drop-off stages, and test simplified pathways or faster activation triggers to shorten time-to-value and boost early engagement metrics.

Activation and retention metrics depend on your product type, but focus on time-to-first-value, day-30 retention rate, and cohort-level behavior. Define which user action signals successful activation, then design experiments tied to measurable outcomes within your analytics platform.

Yes. Analytics-informed retention uses existing metrics to segment cohorts and tailor experiments by user behavior patterns. Extract onboarding cohorts, analyze their activation events, and run targeted retention loops—like re-engagement campaigns or feature incentives—measured against baseline metrics.

A growth plan combines onboarding friction reduction, activation event optimization, and retention experiment design into one framework. Define clear success metrics for each stage, propose lightweight experiments, and measure impact on 30-day retention and time-to-activation to validate improvements.

Activation is the moment a user realizes core value—typically a key action early in the journey. Retention measures whether users return and stay engaged long-term. Both feed growth: fast activation reduces churn risk; strong retention compounds user lifetime value.

Existing metrics accelerate growth work but aren't strictly required. You can start by defining what activation and retention mean for your product, then instrument tracking incrementally. Analytics platforms like PostHog let you layer insights atop onboarding flows without building from scratch.