What is the Experiment Design Kit?

The Experiment Design Kit is a specialized Claude Code skill designed to help growth and marketing teams structure their experimentation process from initial hypothesis to final measurement.

Can it help prevent negative impacts on revenue?

Yes, it includes specific KPI guardrails for activation and revenue metrics that trigger rollback procedures if a test negatively affects core business performance.

Does it support reporting for stakeholders?

It features a Weekly Experiment Packet template that summarizes portfolio snapshots, key wins, guardrail alerts, and pipeline impact for Marketing and Sales Directors.

How does it help with experiment prioritization?

The kit integrates RICE (Reach, Impact, Confidence, Effort) and ICE scoring frameworks to help teams rank their backlog based on potential business impact and strategic fit.

Growth Experiment Design Kit

Name: Growth Experiment Design Kit
Author: gtmagents

bygtmagents

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Automatización de Marketing

Transforms raw ideas into structured growth experiments with robust hypotheses, variant strategies, and measurement frameworks.

Acerca de

The Experiment Design Kit is a specialized framework for Go-To-Market (GTM) teams to architect, launch, and monitor growth tests directly within Claude Code. It streamlines the entire experimentation lifecycle—from framing user problems and defining RICE scores to setting KPI guardrails and generating weekly executive reports. By integrating standard operating models for sales, marketing, and RevOps, it ensures every test is data-driven, risk-mitigated, and aligned with organizational revenue goals.

Características Principales

Hypothesis and variant strategy generator with ICE/RICE prioritization scoring
Standardized GTM operating model for sales, marketing, and RevOps alignment
29 GitHub stars
Weekly Experiment Packet generation for cross-functional leadership syncs
Risk mitigation through pre-built rollback playbooks and KPI alerting rules
Automated measurement plans including primary metrics and power calculations

Casos de Uso

Protecting sales velocity with automated revenue and activation rate guardrails
Translating product ideas into testable multi-variant experiments with clear success metrics
Standardizing the experimentation process across distributed growth and marketing pods

Acerca de

Características Principales

Hypothesis and variant strategy generator with ICE/RICE prioritization scoring
Standardized GTM operating model for sales, marketing, and RevOps alignment
29 GitHub stars
Weekly Experiment Packet generation for cross-functional leadership syncs
Risk mitigation through pre-built rollback playbooks and KPI alerting rules
Automated measurement plans including primary metrics and power calculations

Casos de Uso

Protecting sales velocity with automated revenue and activation rate guardrails
Translating product ideas into testable multi-variant experiments with clear success metrics
Standardizing the experimentation process across distributed growth and marketing pods