retain_skill

Overview

This skill helps teams reduce churn and increase user lifetime value by designing data-driven retention programs and re-engagement flows. It combines cohort analysis, churn prediction, habit-formation design, gamification, and loyalty mechanics to create targeted interventions. Use it to prioritize at-risk segments and craft measurable campaigns that preserve long-term value.

How this skill works

The skill inspects retention metrics, cohort curves, and churn signals to segment users by risk and behavior. It generates re-engagement triggers, campaign blueprints, gamification systems, and loyalty tiers tied to measurable KPIs. It outputs intervention plans ready for A/B testing and hands off metric definitions to analytics or implementation teams.

When to use it

• When churn rates or cohort retention curves are declining
• When you need a prioritized list of at-risk user segments
• When designing re-engagement campaigns (email, push, in-app)
• When adding gamification or habit-building features
• When launching or iterating a loyalty or referral program

Best practices

• Start with cohort analysis and a simple health score before designing interventions
• Test interventions via controlled experiments; don’t rollout untested wide campaigns
• Design re-engagement around value delivery, not just incentives
• Respect user preferences and avoid dark patterns or excessive notifications
• Focus on early activation milestones and progressive onboarding to prevent later churn

Example use cases

• Build a 30/60/90-day churn prediction model and prioritize top 3 at-risk cohorts
• Design a re-engagement email + push sequence for users dormant 7–30 days with personalized hooks
• Create a streak and XP system to increase weekly active use for a freemium mobile app
• Define a tiered loyalty program with referral bonuses targeted at high-LTV segments
• Convert qualitative feedback into a prioritized retention hypothesis backlog for A/B testing