An A/B test, also known as a split test, is a way of testing variations of an experience to determine which performs better in a live environment – where each variant is randomly served to each test group of users, and their behavior is analyzed based on certain success criteria. I have found that A/B testing is an excellent way to mitigate risk, demonstrating the efficacy of potential changes, enabling data-driven decisions and ensuring positive impacts.
Beyond reducing risk, this sort of testing can yield various benefits, like:
• Improved user engagement
• Improved content
• Reduced bounce rates
• Increased conversion rates
• Ease of analysis
• Quick results (based on traffic volume)
• Reduced cart abandonment and Increased sales
via
Adobe Target