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Growth Experiment Designer

Designs and prioritizes data-driven growth experiments using ICE scoring, rigorous A/B testing methodology, and growth loop analysis for sustainable product growth.

Gold
v1.0.00 activationsMarketing & GrowthBusinessadvanced

SupaScore

84.4
Research Quality (15%)
8.5
Prompt Engineering (25%)
8.5
Practical Utility (15%)
8.5
Completeness (10%)
8.5
User Satisfaction (20%)
8.2
Decision Usefulness (15%)
8.5

Best for

  • Designing ICE-scored A/B test roadmaps for SaaS activation improvements
  • Building statistical significance frameworks for growth experiment validation
  • Creating hypothesis-driven growth loop optimization strategies
  • Prioritizing conversion rate experiments using rigorous testing methodology
  • Analyzing AARRR funnel experiments with proper control group design

What you'll get

  • Detailed experiment brief with hypothesis format, ICE scoring rationale, sample size calculations, and success/failure criteria
  • Growth loop analysis identifying bottlenecks with corresponding A/B test designs for each weak point
  • Statistical framework document specifying p-values, confidence intervals, and minimum detectable effects for experiment validity
Not designed for ↓
  • ×General marketing campaigns without measurable hypotheses
  • ×Brand awareness initiatives that can't be A/B tested
  • ×Long-term strategic positioning without quantifiable metrics
  • ×Creative ideation without statistical validation frameworks
Expects

Current product metrics (DAU, MAU, conversion rates), growth stage, existing funnel performance data, and specific growth challenges to address.

Returns

Prioritized experiment roadmap with ICE scores, statistical test designs, success criteria, and measurable hypotheses for each growth initiative.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

growth-experimentsa-b-testingice-frameworkgrowth-loopsactivationexperimentationhypothesis-testingstatistical-significanceconversion-optimizationpirate-metricsnorth-star-metricgrowth-hacking

Research Foundation: 8 sources (4 books, 3 industry frameworks, 1 web)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.02/14/2026

Initial version

Prerequisites

Use these skills first for best results.

Works well with

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Common Workflows

Data-Driven Growth Optimization

Complete workflow from setting up measurement infrastructure to designing experiments to advanced statistical analysis of results

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