What is the purpose of A/B testing in Google Ads?

• A. To randomize audiences
• B. To compare different ad variations or bidding strategies to determine which performs better
• C. To ensure all campaigns are identical
• D. To disable underperforming ads entirely

Answer: (B)

A/B testing in Google Ads is about learning which version of an element delivers better results by making a controlled comparison. You create two variants that are the same except for one factor you want to test—such as two different ad headlines, two landing pages, or two bidding strategies. Traffic is split between the variants under similar conditions, and you measure performance metrics like click-through rate, conversion rate, and cost per conversion. After collecting enough data to be confident in the result, you adopt the winning variant to improve overall campaign performance. This approach helps you make data-driven improvements rather than guessing.

It’s not primarily about randomizing audiences in a broad sense, nor is it about making every campaign identical. It’s also not just to disable underperforming ads; the goal is to learn which variant works best so you can optimize what you run.