Western Governors University (WGU) MKTG 6040 D381 E-Commerce and Marketing Analytics – Google Course 5 Practice Exam

A/B testing is about comparing two versions of an ad to see which performs better by isolating the specific change you made and measuring its impact on key metrics. By randomly splitting the audience and analyzing results with statistical rigor, you can determine whether the modification actually improves performance or if observed differences are just random noise. This approach reduces the surprises that can come from implementing changes, because you validate how a modification will behave before rolling it out widely. It’s not primarily about eliminating external factors, increasing budget, or eliminating testing constraints—the core benefit is predicting and controlling how changes to ads will affect results, so you avoid unexpected drops or unintended effects after a change.