A/B Test Hypothesis Generator

What problem does it solve?

This skill generates statistically rigorous, testable hypotheses for e-commerce content optimization experiments, moving beyond simple A/B tests to data-driven, psychologically-grounded experiments.

Core Features & Use Cases

• Hypothesis Generation: Creates structured hypotheses based on performance data, customer insights, and behavioral science.
• Statistical Design: Calculates sample size, MDE, and duration for experiments.
• Prioritization: Ranks hypotheses using the ICE framework.
• Use Case: A product manager can use this skill to generate a prioritized list of A/B tests for a product detail page, complete with statistical parameters and expected outcomes, to optimize conversion rates.

Quick Start

Use the A/B Test Hypothesis Generator skill to generate hypotheses for optimizing an e-commerce product page, providing current content, performance data, and business objectives.