Step 1: Research
The first step of your A/B experiments is understanding where your business currently stands. For that, you need to collect data on the current traffic, possible problems, retention and bounce rates, etc. Tools like Google Analytics can help you determine which pages and locations users spend the most time on. It helps business owners determine the problem area on the website and target it accordingly. However, it’s important to use qualitative and quantitative data collection methods for A/B testing.
Step 2: Formulate a Hypothesis based on Research Data
After conducting the research, the next logical step is to analyze the data. Professionals in research and analysis analyze the data and find possible flaws in the websites. Once you have a clearer idea of the possible reasons, you should formulate a hypothesis and test it on parameters such as macro goal impact, setup ease, etc.
Step 3: Create Test Variations
In A/B testing, resting test variations is a critical step. A/B testing works best when each test version has only one element that is different from the other version. For example, you use the same image on social media but with a different caption or use a different headline for the same blog post.
Step 4: Divide the Audience into Random Groups
In A/B testing, the audience in groups A and B should be equal in size and random. While we may not have complete control over how the audience views the two versions, we can certainly split them into even groups. There are many marketing automation software such as HubSpot’s A/B testing Kit and Google Optimize that split traffic into different versions for efficient A/B testing.
Step 5: Run the Test
Once you have everything in place, it’s time to run the test. Make sure that you’re testing the versions simultaneously as you can’t trust the test results if the two versions were tested at different points in time.
Depending on the test type, you also need to let the test run for enough time to produce useful results. For example, if you’re testing two pieces of content, the minimum amount of time to run the test would be a month.
Step 6: Analyze the Results and Implement Changes
Last but not least, we analyze the results gathered from the A/B tests. You can use many metrics to analyze how each version performed, but choose two or three metrics that align best with your main goal. For example, when A/B tests email subject lines, the open rate can be a useful metric. Alternatively, for a website copy or blog post, bounce and exit rates tell us how the audience engaged.
It’s also important to analyze whether the results are statistically significant – big enough to warrant a change. If so, then we can go ahead with implementing the changes.
Step 7: Implement the Changes
Everything is a lesson if we can learn from it. Use what you learn from the A/B test results to use the best approach. In the marketing and advertising worlds, not much is free but A/B testing is among the most cost-efficient and effective testing approaches. You often gain invaluable feedback from the consumers without them actually participating in a test.
