growth-marketing

Design and analyze A/B tests for growth experiments using Python, SQL, and YAML.

19|5|Updated Nov 23, 2025
One-click install
npx skills add https://github.com/Nir-Bhay/markups --skill growth-marketing-nir-bhay
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: growth-marketing
Source: https://github.com/Nir-Bhay/markups/tree/main/.agents/skills/growth-marketing
Command: npx skills add https://github.com/Nir-Bhay/markups --skill growth-marketing-nir-bhay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps businesses accelerate growth by systematically identifying, testing, and scaling effective marketing strategies and product improvements.

Core Features & Use Cases

  • Experimentation Framework: Design, prioritize, and analyze A/B tests and growth experiments.
  • Funnel Optimization: Improve conversion rates across the user journey from acquisition to revenue.
  • Viral Growth: Implement strategies to encourage user referrals and organic sharing.
  • Use Case: A startup can use this Skill to brainstorm hypotheses for increasing user sign-ups, design an A/B test for a new onboarding flow, and analyze the results to determine if the change should be rolled out.

Quick Start

Analyze the provided A/B test results for the homepage button color change.

Frequently Asked Questions about growth-marketing

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

FAQPage Schema
How do I design A/B tests for funnel optimization?

Funnel optimization A/B tests are designed by formulating data-driven hypotheses, prioritizing experiments, and analyzing conversion rates across the user journey from acquisition to revenue. The framework supports strategic decisions for user activation and retention.

What is a viral loop and how does it drive user referrals?

A viral loop is a mechanism designed to encourage user referrals and organic sharing. It drives growth by systematically implementing strategies that turn existing users into acquisition channels for new users.

Can I use Python and SQL for cohort analysis and metric benchmarking?

Yes, you can use Python and SQL frameworks to perform cohort analysis and metric benchmarking. These tools enable strategic decision-making for user acquisition, activation, retention, revenue, and referral growth.

What's the best way to prioritize growth marketing experiments?

The best way to prioritize growth marketing experiments is using a systematic framework to identify, test, and scale effective strategies. This involves designing data-driven A/B tests and analyzing results to determine if changes should be rolled out.

Does this approach work for improving user activation and retention?

Yes, this approach works for improving user activation and retention by systematically testing product improvements. It enables strategic decision-making across the entire user journey from acquisition to revenue generation.