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A/B testing, also known as split testing, is a statistical method used to compare two versions of a product or webpage to determine which one performs better. It is a widely-used technique in marketing, web development, and product management to make data-driven decisions. Here’s a basic overview:
1. Objective of A/B Testing:
a. Objective of A/B Testing:
- Compare two or more versions of a variable to assess performance.
- Determine which version yields better results based on predefined metrics.
- Optimize and enhance decision-making in various areas such as marketing, product development, and user experience.
b. Comparison in A/B Testing:
- Involves variations of a webpage, email, ad, or other elements.
- Versions are randomly assigned to distinct groups (A and B) to minimize bias.
- Metrics for comparison are predefined and aligned with business goals.
- Common metrics include conversion rates, click-through rates, and user engagement.
- Statistical analysis is employed to identify significant differences between versions.
