{"id":116799,"date":"2023-07-31T19:10:11","date_gmt":"2023-07-31T19:10:11","guid":{"rendered":"https:\/\/userpilot.com\/blog\/ab-testing-metrics\/"},"modified":"2024-09-16T17:57:39","modified_gmt":"2024-09-16T17:57:39","slug":"ab-testing-metrics","status":"publish","type":"post","link":"https:\/\/userpilot.com\/blog\/ab-testing-metrics\/","title":{"rendered":"10 A\/B Testing Metrics To Track Results and Measure Success"},"content":{"rendered":"

What is A\/B testing?<\/strong><\/h2>\n

A\/B testing is a scientific, evidence-based method to optimize the performance of a product or landing page. It tests a variation of a product, a marketing campaign, or an ad against a control group to:<\/p>\n

1) See if it outperforms the original version.
\n2) Determine with statistical significance what elements bring better results (e.g. what headline makes a winning landing page for e-commerce companies).<\/p>\n

However, the key to making A\/B testing a worthy investment is to have a clear metric that aligns with business objectives.<\/p>\n

How to choose the right A\/B testing metrics?<\/strong><\/h2>\n

To conduct productive A\/B tests, there needs to be a structured framework and a measurable definition of success.<\/p>\n

First, you must define the testing goal by stating what you want to accomplish. Do you want to increase sales? Expand brand recognition? Or achieve revenue growth?<\/p>\n

Then, to determine the right metric for your experiments, you must follow a proper metric framework<\/a> such as:<\/p>\n