A/B Testing

Design, run, and analyze A/B tests for marketing campaigns and product features.

Integrations: Google Analytics

When to Use

• The user wants to test different versions of a page or campaign
• Data-driven decisions are needed for feature or design changes
• The user mentions "A/B test", "experiment", or "conversion optimization"

Steps

Step 1: Define Hypothesis

Formulate a testable hypothesis with expected outcome.

Step 2: Calculate Sample Size

Determine required traffic and test duration for statistical significance.

Step 3: Set Up Variants

Configure control and variant with tracking.

Step 4: Analyze Results

Evaluate statistical significance and make recommendations.

Output

Deliver:

• Test plan with hypothesis and sample size
• Variant configuration details
• Results analysis with confidence intervals