What method involves testing two different versions of something, like a web page, to see which one works better?

The method described is called A/B testing. A/B testing is a controlled experiment that compares two distinct versions of something, such as a web page, an application feature, or an email, to objectively determine which version performs better based on specific metrics. In this process, one version is designated as the "control," which is typically the existing or original version. The other version is the "variation," which incorporates a specific change or set of changes intended to improve performance. For instance, the control might be a web page with a blue call-to-action button, while the variation is the exact same page but with a green call-to-action button. Users are then randomly divided into two groups, with one group exposed to the control and the other to the variation. This random assignment ensures that any observed differences in behavior are attributable to the tested changes rather than pre-existing differences among the users. Data is collected on how each group interacts with its respective version, focusing on predefined "metrics," which are quantifiable measurements like click-through rate (the percentage of users who click an element) or conversion rate (the percentage of users who complete a desired action, like a purchase). After a sufficient amount of data is gathered, the performance of the control and variation is analyzed. The key step in analysis is to determine if any observed performance difference between the versions is "statistically significant," meaning there is a high probability that the difference is real and not merely due to random chance. If the variation demonstrates a statistically significant improvement in the chosen metric over the control, it indicates that the changes made in the variation are more effective. The better-performing version is then selected for implementation, leading to data-driven optimization and improved outcomes.