What does "A/B testing" refer to?

A/B testing refers specifically to a statistical method used to compare two versions of a web page, or more generally, two variants of any product or process, to determine which performs better in terms of user engagement or other defined metrics. This involves splitting a sample of users into two groups, where one group is shown version A and the other group is shown version B. By analyzing the performance of each version based on user behavior, businesses can gain insights into which iteration leads to better outcomes, such as higher conversion rates or user satisfaction.

The effectiveness of A/B testing arises from its ability to provide empirical evidence to inform decisions, making it a vital tool in marketing, product development, and user interface design. This method allows organizations to make data-driven adjustments rather than relying on assumptions or subjective preferences.

In contrast, the other choices do not accurately define A/B testing. Generating random data is unrelated to comparing versions. Data retrieval techniques focus on how data is accessed or retrieved from databases rather than comparing variations. Lastly, a software development lifecycle methodology pertains to the processes and practices involved in developing software rather than comparing versions for performance metrics.