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growth-engineering

Analyze AARRR Pirate Metrics and design growth systems for products.

Updated Mar 20, 2026
Search Tags:#A/B testing#cohort analysis#user retention#product-led growth#growth engineering#AARRR metrics#referral systems
One-click install
npx skills add https://github.com/Cure-Consulting-Group/iep-and-thrive --skill growth-engineering-cure-consulting-group
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: growth-engineering
Source: https://github.com/Cure-Consulting-Group/iep-and-thrive/tree/main/.agents/skills/growth-engineering
Command: npx skills add https://github.com/Cure-Consulting-Group/iep-and-thrive --skill growth-engineering-cure-consulting-group

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, bigquery, google-cloud, numpy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a structured approach to build growth systems, including activation funnels, referral programs, lifecycle automation, cohort analysis, and product-led growth patterns, to systematically drive growth for a product.

Core Features & Use Cases

  • Growth Engineering Framework: Offers a comprehensive framework for different growth needs (activation optimization, retention improvement, referral systems, monetization experiments, lifecycle automation, and cohort analysis).
  • Context Gathering: Collects necessary project context, such as product information, current metrics, lifecycle stage, analytics stack, team maturity, and constraints.
  • AARRR Metrics Analysis: Utilizes the AARRR (Acquisition, Activation, Retention, Revenue, Referral) Pirate Metrics to build and measure growth models.
  • Activation Engineering: Focuses on optimizing the 'aha moment' to improve user activation, with strategies for time-to-value optimization, onboarding experiments, and progressive disclosure.
  • Retention Systems: Implements engagement loops and re-engagement triggers to build retention into the product.
  • Referral and Viral Mechanics: Provides guidance on designing and optimizing referral systems and calculating viral coefficients.
  • Cohort Analysis and Experimentation: Offers a framework for cohort analysis and designing A/B tests for growth experiments.
  • Product-Led Growth Patterns: Delivers strategies for freemium conversion, usage-based upgrade triggers, paywall optimization, and trial design.

Quick Start

Use the growth-engineering skill to analyze the AARRR metrics for your product and identify key areas for growth.

Frequently Asked Questions about growth-engineering

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

FAQPage Schema
How do I implement AARRR metrics analysis for product growth?▼

AARRR metrics analysis tracks Acquisition, Activation, Retention, Revenue, and Referral to build structured growth models. It automates measuring these pirate metrics to identify areas for product lifecycle optimization and growth.

What is the best way to optimize user activation and time-to-value?▼

Activation engineering optimizes the user 'aha moment' through time-to-value reduction, onboarding experiments, and progressive disclosure. This systematically improves activation rates by shortening the path to initial product value.

How do I design A/B tests for cohort analysis and growth experiments?▼

Designing A/B tests for cohort analysis segments users by shared characteristics to measure retention and engagement over time. This framework structures growth experiments to validate strategies and track metric improvements.

Does this growth engineering framework require Python and BigQuery?▼

Yes, this growth engineering framework requires Python, BigQuery, Google Cloud, and NumPy. These dependencies support automating AARRR metrics analysis, processing cohort data, and executing product-led growth strategies.

How do I build referral systems and calculate viral coefficients?▼

Building referral systems involves designing viral mechanics and calculating viral coefficients to measure user-driven acquisition. This framework provides guidance for optimizing referral programs to drive product-led growth.

When do I need product-led growth patterns for freemium conversion?▼

Product-led growth patterns are needed when optimizing freemium conversion, usage-based upgrade triggers, paywall designs, and trial experiences. This framework delivers strategies to systematically monetize products through engagement loops.

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