What is A/B testing and how does it work?
A/B testing is also known as split testing. It is a method used in marketing and product development to compare two versions of a product or asset. Think webpage, email, app, or other digital asset. A/B testing is a process to determine which one performs better. This involves creating two variations of the asset, with one variable changed between the two versions. The goal is to identify which variation is more effective in achieving a specific goal, such as increasing conversions, click-through rates, or engagement.
Roots in the scientific method
A/B testing is based on the scientific method. This is where a hypothesis is tested by comparing two groups under controlled conditions. In digital marketing, the hypothesis is typically related to the design, content, or layout of a webpage or email. By testing two variations simultaneously, marketers can gather data on user behaviour and preferences to make informed decisions about which version is more effective.
i.e. A/B testing of which email subject line has the highest open rate.
The process of A/B testing
1. Define the goal: Before starting an A/B test, it is important to clearly define the goal or metric that you want to improve. This could be anything from increasing conversions on a landing page to improving engagement on an email campaign.
2. Identify the variable: The next step is to identify the variable that you want to test. Try the headline, call-to-action button, images, layout, or any other element of the webpage or email.
3. Create the variations: With the variable chosen, two versions of the asset are created. One version will contain the original element and accordingly, the other version has the new element. It’s vital to ensure that only one variable is changed between the two versions, to accurately measure the impact of that change.
4. Split the traffic: The next step is to split the traffic evenly between the two versions of the asset. This can be done using A/B testing tools or by manually directing users to the different versions. Lots of email management tools offer this function.
5. Gather data: As users interact with the two versions of the asset, data is collected. Key metrics such as click-through rates, conversions, bounce rates, and engagement are usually monitored. This data is used to determine which version is more effective in achieving the defined goal.
6. Analyse the results: Once the test is complete, the results are analysed to determine which version performed better. This analysis may involve statistical significance testing to ensure that the results are reliable and not due to random chance.
7. Implement the winner: Based on the results of the test, the winning variation is consequently the new standard. This process can be repeated multiple times to continuously optimise and subsequently improve the performance of digital assets.
TL:DR
A/B testing basically allows you to test variations on a theme.
Use A/B testing to make data-driven decisions and improve the effectiveness of campaigns. Test different variations, and measure the impact on your key metrics. Consequently, marketers can identify what resonates with audiences and optimise for maximum impact. Get in touch to learn how we can make A/B testing work for you.