What does the measure of "Lift" directly compare?

The measure of "Lift" directly compares the performance of a variant experience to a baseline. In the context of testing and experimentation, lift is used to quantify the effect of changes made in a variant against a control or baseline experience. This is particularly important in A/B testing, where the goal is to determine whether a new feature or design leads to better user engagement, conversion rates, or other key performance indicators compared to the existing solution. By calculating lift, marketers and analysts can effectively evaluate the success of their changes and make data-driven decisions moving forward. This makes it a crucial metric in experimentation and optimization efforts in platforms like Adobe Target.