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retention-engagement

Analyze cohort data and generate prioritized retention experiments with measurement plans.

5|Updated Jan 19, 2026
Search Tags:#product management#engagement#activation#growth#retention#churn
One-click install
npx skills add https://github.com/oldwinter/skills --skill retention-engagement-oldwinter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: retention-engagement
Source: https://github.com/oldwinter/skills/tree/main/lenny-skills/product-skills/retention-engagement
Command: npx skills add https://github.com/oldwinter/skills --skill retention-engagement-oldwinter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the critical challenge of improving user retention, reducing churn, and increasing engagement and activation for a product.

Core Features & Use Cases

  • Diagnosis: Identifies key drop-off points in user journeys and analyzes retention/engagement metrics.
  • Activation Definition: Helps define and validate the "aha moment" that signifies a user has experienced core value.
  • Experiment Design: Generates a prioritized backlog of experiments to improve onboarding, habit formation, and re-engagement.
  • Use Case: A SaaS company sees high churn after the first month. This Skill can diagnose why users leave, define what "activated" looks like, and propose experiments like improving onboarding flows or introducing new habit-forming features.

Quick Start

Use the retention-engagement skill to diagnose why users churn and propose experiments to improve D30 retention.

Frequently Asked Questions about retention-engagement

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce churn and improve user retention for a SaaS product?▼

To reduce churn and improve user retention, you can analyze cohort data to identify drop-off points, define activation moments, and generate prioritized experiments for onboarding and habit formation.

What is the best way to define an activation moment for new users?▼

Defining an activation moment involves identifying the specific actions that signify a user has experienced core value. This process analyzes user journey data to validate the exact interactions leading to long-term retention.

How do I diagnose why users are churning after the first month?▼

Diagnosing first-month churn requires analyzing cohort data and user journey metrics to pinpoint exact drop-off stages. This helps identify whether onboarding friction or lacking habit-forming features causes the loss.

How can I generate experiments to increase D30 retention?▼

Generating experiments to increase D30 retention involves creating lever hypotheses from churn diagnosis, then prioritizing a backlog of tests targeting onboarding improvements and re-engagement strategies.

Can I use this approach to analyze cohort data for activation and engagement?▼

Yes, analyzing cohort data is a core function for improving engagement and activation. It helps identify key drop-off points in user journeys and validates the metrics needed to build measurement plans.

What do I need to create a measurement and execution plan for growth experiments?▼

Creating a measurement and execution plan requires cohort analysis, defined activation moments, and prioritized experiment hypotheses. These elements combine to form a comprehensive improvement pack for growth teams.

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