A/B Test Setup

Stop guessing which UI changes actually drive conversions. Most A/B tests fail because of poor hypothesis framing, insufficient sample sizes, or mid-test interference. This skill provides the statistical rigor and structured planning needed to run experiments that deliver valid, actionable data.

What it does

• Experiment Design creates structured test plans including hypotheses, variants, and success metrics.
• Statistical Planning calculates required sample sizes and estimated test durations based on your traffic.
• Metric Definition identifies primary KPIs, secondary signals, and guardrail metrics to prevent negative impacts.
• Quality Control provides pre-launch checklists to ensure tracking and variant triggers work correctly.
• Results Documentation generates standardized templates for recording learnings and next steps.

How it works

1. Provide your current baseline conversion rate, daily traffic volume, and the change you want to test.
2. The skill generates a formal hypothesis and calculates the required sample size for statistical significance.
3. Review the variant design and the measurement plan, including guardrail metrics.
4. Use the pre-launch checklist to verify the technical setup before starting the experiment.

Frameworks & tools

Works with any experimentation stack including Optimizely, VWO, Google Optimize alternatives, PostHog, LaunchDarkly, or custom in-house feature flag systems.

Why this beats prompting it yourself

Generic AI often suggests "testing everything at once," which ruins data isolation. This skill enforces single-variable testing and strict statistical rules to ensure you don't stop tests early or reach false conclusions.

Use cases

• Validating a new checkout flow to reduce cart abandonment.
• Testing high-impact headline changes for landing page lead gen.
• Measuring the conversion impact of new product features.
• Split testing pricing models or subscription tiers.

Known limitations

Does not perform live data analysis or connect directly to analytics APIs. Requires manual input of traffic and conversion numbers to perform calculations.