SPACE-experiment-designer

What problem does it solve?

It turns vague experiment ideas into a clear, testable A/B plan, reducing risky launches and ambiguous results.

Core Features & Use Cases

• Hypothesis framing: Converts product goals into falsifiable hypotheses with measurable effect targets.
• Experiment setup: Recommends segmentation, traffic split, and controls for confounding variables.
• Metrics and statistics: Defines core, guardrail, and auxiliary metrics, then estimates sample size, runtime, and decision thresholds.
• Decision support: Provides success, failure, uncertainty, and stop-loss rules for go or no-go decisions.
• Use case: Use it when planning a homepage, checkout, pricing, or growth experiment and you need a complete, statistically sound proposal.

Quick Start

Ask the skill to design an A/B experiment for your product change, including the hypothesis, groups, metrics, sample size, stop-loss rules, and final decision criteria.