A/B Testing

# A/B Testing

• **Variant A (Control):** The original version of the asset.
• **Variant B (Challenger):** The modified version with one or more changes (e.g., button color, headline, layout).
• **Audience Split:** Traffic or audience is randomly divided between the variants to ensure fairness.
• **Metrics (KPIs):** Success is measured by key performance indicators such as click-through rate (CTR), conversion rate, sign-ups, or revenue.
• **Statistical Significance:** Ensures results are reliable and not due to chance.
• Changing the text on a **CTA button** ("Buy Now" vs. "Shop Today").
• Testing **email subject lines** to see which generates higher open rates.
• Comparing two **landing page designs** to maximize lead generation.
• Running different **ad creatives** to find the most engaging format.
• Provides data-driven insights rather than relying on assumptions.
• Improves conversion rates and ROI.
• Reduces risks by testing changes before full rollout.
• Enhances customer experience by aligning with audience preferences.
• Test **one variable at a time** for clarity of results.
• Ensure **enough sample size** for statistical validity.
• Define clear **hypotheses** before running the test.
• Run tests long enough to account for **user behavior patterns**.
• Use reliable **A/B testing tools** (e.g., Google Optimize, Optimizely, VWO).
• Multivariate Testing
• Conversion Rate Optimization (CRO)
• Hypothesis Testing
• Split URL Testing