How can you conduct A/B, multivariate, and split testing using prototyping and testing tools?

1 What is A/B testing?

A/B testing is a method of comparing two versions of a design element, such as a button, a headline, or a layout, to see which one performs better according to a specific metric, such as clicks, sign-ups, or purchases. A/B testing allows you to isolate the impact of one variable on your user behavior and measure it statistically. To conduct A/B testing using prototyping and testing tools, you need to create two prototypes that differ only in the element you want to test, and then use a tool that can randomly assign users to either version and track the results. Some examples of prototyping and testing tools that support A/B testing are Adobe XD, Optimizely, and Google Optimize.

2 What is multivariate testing?

Multivariate testing is a method of comparing multiple versions of a design that have more than one variable changed, such as a combination of colors, fonts, images, and copy. Multivariate testing allows you to test the interaction effects of different variables on your user behavior and measure them statistically. To conduct multivariate testing using prototyping and testing tools, you need to create multiple prototypes that differ in the variables you want to test, and then use a tool that can randomly assign users to each version and track the results. Some examples of prototyping and testing tools that support multivariate testing are Adobe Target, VWO, and Unbounce.

3 What is split testing?

Split testing is a method of comparing two versions of a design that have a significant difference, such as a completely different layout, navigation, or functionality. Split testing allows you to test the overall impact of a major change on your user behavior and measure it statistically. To conduct split testing using prototyping and testing tools, you need to create two prototypes that differ in the design you want to test, and then use a tool that can randomly assign users to either version and track the results. Some examples of prototyping and testing tools that support split testing are InVision, Figma, and UserTesting.

4 How to choose the right type of testing?

The type of testing you choose for your product engineering project will depend on your goals, hypotheses, resources, and timeline. A/B testing is ideal for testing small changes with a clear impact on a single metric, such as altering the color of a call-to-action button or the wording of a headline. It is also simpler to set up and analyze than multivariate or split testing. Multivariate testing is best for testing multiple changes with a complex effect on multiple metrics, such as changing the combination of colors, fonts, images, and copy on a landing page. This type of testing is more efficient than A/B testing when you want to test many variables at once, but it requires more traffic and time to reach statistical significance. Split testing is best for evaluating large changes that have a radical impact on the user experience, such as changing the entire layout, navigation, or functionality of a website or app. It is more reliable than A/B or multivariate testing when you want to measure the effect of design changes on user behavior like engagement, retention, or satisfaction; however, it requires more effort and resources to create and test different prototypes.

5 How to use prototyping and testing tools effectively?

Prototyping and testing tools can be incredibly beneficial for product engineering projects, but it’s important to use them effectively in order to get the most out of them. To do this, you should define your goals and hypotheses clearly before beginning the testing process. Additionally, select the right tool for the right type of testing by comparing features, costs, and limitations. Create realistic and interactive prototypes that mimic the user experience with high-fidelity prototyping tools, and test them for usability, functionality, and accessibility. When segmenting and targeting users, use tools that let you define your audience and criteria for testing. Finally, make sure to run your tests for a sufficient duration and sample size in order to calculate statistical significance and confidence level. Adjust your tests based on feedback and data collected as well.

6 How to learn more about prototyping and testing tools?

Prototyping and testing tools are constantly evolving, so it's important to stay up-to-date with the latest trends and best practices. To do this, follow the blogs, podcasts, newsletters, and social media accounts of the tools you use or are interested in. Additionally, join online communities and forums where product engineers and designers share their experiences with prototyping and testing tools. You can also take online courses, webinars, or workshops to learn how to use these tools effectively. There are many free or paid resources available that cover different aspects and levels of prototyping and testing.