A six step process to go from zero to running reliable A/B tests.
In this lesson, you will learn a clear six step process to go from zero to launching and analyzing your first A/B test.
Step one is research. Before testing anything, you need analytics installed and enough data to understand what is actually happening on your site. Look at traffic, bounce rate, and conversion rate. Focus on high impact pages like your homepage and pricing page where improvements will matter most.
Step two is creating a hypothesis. Based on your research, form a clear assumption about what might improve performance. For example, a clearer headline or better navigation could reduce bounce rate. It is a guess, but it should be an informed one.
Step three is installing an A/B testing tool that works with your tech stack. Once installed, you are ready to build variations.
Step four is creating those variations. Develop multiple versions that directly address your hypothesis, whether that is clearer copy, improved navigation, or a redesigned section.
Step five is launching and monitoring your test. Two key factors matter here: sample size and duration. Aim for at least one thousand tested users to avoid unreliable data, and let the test run long enough to account for different user behaviors across days or seasons.
Step six is analyzing the data. Look beyond surface level numbers and consider real business metrics. For example, more form submissions do not always mean better results if lead quality drops.
A/B testing is not a one time action. It is a continuous process of research, testing, analyzing, and improving your website over time.
