How does this skill handle different types of experiments?

It orchestrates both quantitative (via hypothesis-testing) and qualitative (via qualitative-research) experiments to provide a holistic view of your marketing performance.

Does it execute the actual ads or emails for me?

No, it focuses on the strategic design, coordination, and synthesis of validation cycles. It is tool-agnostic and delegates specific analysis to other specialized skills.

What is the primary output of this skill?

The primary output is a clear performance signal (positive, negative, null, or mixed) and a structured iteration plan based on experimental evidence.

Can I resume a campaign after a long break?

Yes, the skill is designed for multi-conversation persistence, using an experiment tracker and documented phase files to allow you to pick up exactly where you left off.

Do I need existing data to start?

Not necessarily. While it can leverage existing data, the process begins with discovery and market research to help you build experiments from scratch if needed.

Marketing Experimentation

Name: Marketing Experimentation
Author: tilmon-engineering

bytilmon-engineering

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营销自动化

Systematizes the marketing experimentation process from hypothesis generation to data-driven iteration planning.

关于

This skill provides a rigorous framework for validating marketing concepts and business ideas through the Build-Measure-Learn cycle. It orchestrates a comprehensive 6-phase workflow that guides users through asset discovery, multi-channel hypothesis generation, and the coordination of both quantitative and qualitative experiments. By synthesizing results across multiple campaigns and data sources, it helps teams move beyond guesswork to generate actionable insights and evidence-based iteration plans within a structured workspace.

主要功能

Integration with market research agents for concept validation
Guided 6-phase experimental workflow based on Lean Startup principles
Persistent experiment tracking for long-running multi-conversation campaigns
Multi-channel hypothesis generation covering acquisition, activation, and retention
Cross-experiment synthesis to identify unified performance signals
2 GitHub stars

使用场景

Running systematic A/B tests across landing pages, ads, and email sequences
Validating a new product concept or business idea before investing in scaling
Combining qualitative customer feedback with quantitative analytics to refine marketing strategy

关于

主要功能

Integration with market research agents for concept validation
Guided 6-phase experimental workflow based on Lean Startup principles
Persistent experiment tracking for long-running multi-conversation campaigns
Multi-channel hypothesis generation covering acquisition, activation, and retention
Cross-experiment synthesis to identify unified performance signals
2 GitHub stars

使用场景

Running systematic A/B tests across landing pages, ads, and email sequences
Validating a new product concept or business idea before investing in scaling
Combining qualitative customer feedback with quantitative analytics to refine marketing strategy